cta-8-get-the-latest-contact-data-in-every-app

8 (FULL) - Contact management - get-the-latest-contact-data-in-every-app

cta-half-8-get-the-latest-contact-data-in-every-app

8 (HALF) - Contact management - get-the-latest-contact-data-in-every-app

Build your tech stack

Find and integrate the right business apps for your organization’s needs, pain points and goals.

![big data collection and management](//images.ctfassets.net/f2ysq090txql/1ffbRACWpKM7KC1lnc8l9c/4019c279725fa63e1a0d32485c69f550/chris-liverani-dBI_My696Rk-unsplash.jpg)

Most entrepreneurs are familiar with the term 'big data.' After all, [data is the lifeblood of any effective business strategy](https://blog.hubspot.com/website/data-integrity). While this might sound straightforward, there are plenty of [big data challenges](https://blog.hubspot.com/website/big-data-challenges) that many business owners are not aware of.

To start at the beginning of every data strategy, how is big data collected? And once you have it, what can you use it for and how can you manage it?

Let's take a look at everything you need to know to leverage big data for your business, from collection to management. 

---

## What is big data?

As the name suggests, the term **big data** refers to a large volume of information that can be collected, analyzed, shared, created, and much more. It can include any kind of information we create digitally, such as emails, texts, documents, videos, photos...

This term also has a layered definition that is known as the '3 V's':

1. Velocity
2. Volume
3. Variety

The term **velocity** refers to the speed at which data is acquired. For example, real-time, automated data reports may be able to provide a company with customer information as soon as a specific goal is reached.

**Volume** is the overall amount of information and also includes the sources from which you obtain it. This typically includes things like social media, email, transactions, etc.

Lastly, **variety** is a term that refers to the different types of data that you collect. Big data could include all types of data, such as audio, video footage, digital images, and financial records. 

<RelatedPost slug="big-data-for-small-businesses" />

&nbsp;

## Big data benefits to businesses

Big data might sound daunting, but the [difficulties associated with it](https://www.piesync.com/blog/top-5-problems-with-big-data-and-how-to-solve-them/) are well worth the trouble. Big data can offer a large number of benefits to businesses of all sizes.

As such, entrepreneurs need to make sure they prioritize collecting and managing it properly so they can make the most of what big data has to offer. Here are a few key areas where big data can make a difference.

&nbsp;

### 1. Optimizing sales performance 

One of the most useful benefits of big data is the possibility to [optimize sales performance](https://www.piesync.com/solutions/crm/). By collecting and analyzing sales data, you'll be able to determine the weakest areas of your business and then make the appropriate changes.

Additionally, you can take a look at your customers' past browsing or purchasing behavior and use this data to make offers that they are likely to be interested in. Information from consumer feedback surveys can also be used to determine what areas of the customer experience need improvement.

While the type of information that you collect will depend on the size of your business and your industry, you can always use this information to increase your overall number of sales.

&nbsp;

### 2. Mitigating risk

Proper risk management is essential to the long-term health and success of the business. This is particularly true for smaller companies that can't afford to make a misstep without incurring financial difficulty.

When reviewing your company's financial data, you'll gain direct insight into areas of your business practices that are particularly volatile. For instance, a particular marketing strategy may provide a significant return on investment during a single month while providing nearly nothing the next month.

You can use this data to fine-tune your strategy until it performs consistently. You'll also learn from past mistakes to avoid repeating them in the future – otherwise, you run the risk of dealing with consequences on a much larger scale as your business grows. 

&nbsp;

### 3. Streamlining your budget

You can also identify areas where your business is spending more than it should to optimize your spending.

It's not uncommon for businesses to unnecessarily spend thousands of dollars that they could reallocate toward other areas of the business. This is commonly seen with expenses involving subscription-based services, as recurring monthly payments often get buried underneath all the invoices and costs of running a business. 

Big data can also help you identify expensive processes and workflows and give you valuable insights into how to optimize them.

<RelatedPost slug="top-5-problems-with-big-data-and-how-to-solve-them" />

---

## How to collect big data

Many entrepreneurs might get lost when developing a data strategy due to the sheer amount of decisions they need to make. It's important to do this carefully and thoughtfully to [create a practical, safe and scalable strategy to manage big data](https://blog.hubspot.com/website/data-management), from collection to usage.

Once you have a solid data strategy, you can think about how to start collecting data. There's a good chance that you're already doing it: if your business is run entirely or partially online, you likely already have some tools that collect and analyze data. 

Think of your email marketing tool that stores customers' and leads' email addresses and other personal information, as well as other information like open rates, click-through rates, and more. Or your CRM, which contains a wealth of information about your customers in every stage of their journey.

Here are some more examples of how you can collect big data.

&nbsp;

### 1. Social media

How your audience interacts with you on social media can give you a significant amount of crucial data. You'll be able to determine what type of content they are most interested in, how they interact with various aspects of your page, and more.

Over time, you'll develop a stronger understanding of the type of content that your followers want to see and then leverage this opportunity to direct them to your company's website. In addition, by analyzing trends, audience behavior and customer interactions on social media, you will have plenty of quality data to inform your overall sales and marketing strategies.

&nbsp;

### 2. Website analytics

With tools like [Google Analytics](https://analytics.google.com/) or [Google Data Studio](https://datastudio.google.com/), you can analyze a wealth of information about your website to figure out what is working and what isn't on one of your company's top assets.

You will gain insights into the demographic profile of visitors, website traffic, keywords, landing page performance, conversions, and any other online data that is relevant for your business. 

For example, you can find out how many people navigate away from your store's online cart, how long they stay on each page of your website, and how they get there in the first place.

You'll even be able to gain insight into what search terms they were looking for when they found you on search engines, allowing you to target them more effectively in the future and orienting SEO and PPC campaigns, for instance.

<RelatedPost slug="best-practices-for-reliable-analytics-and-reporting" />

&nbsp;

### 3. Purchase behavior

Although this metric is often explored while reviewing your website's analytics, it's worth giving your customers' purchase behavior extra attention. After all, understanding why someone decided to spend money on you is key to facilitating a higher number of future sales.

For example, you could analyze the purchase behavior of specific segments of customers. After determining what type of products they're interested in, you can then provide them with personalized offers related to their past purchases. This could also help you predict the interests of future customers who belong to the same segments and show similar behavior.

Additionally, users who tend to abandon their carts during their online purchase process often do so in order to deliberate on the price they're paying for the goods. From here, you can provide a discount on these items in order to encourage the completion of the purchase, or send them an email to remind them to purchase the products on their cart.

&nbsp;

### 4. Customer satisfaction

If you want to offer stellar customer service and keep an eye on how happy your customers are with your company, it's crucial to measure customer satisfaction. You can do this with customer surveys that measure NPS (Net Promoter Score) and CSAT (Customer Satisfaction Score), for example. 

This is useful to predict and prevent customer churn, as well as optimizing your products, sales strategies and customer service team. It also gives your customers an easy opportunity to let you know how they feel about your products or services, which helps them feel heard and cared for.
<RelatedPost slug="12-ways-to-improve-customer-experience-with-automation" />

---

## Data management best practices 

It's essential to understand that every company has a responsibility in how they collect and manage data. It's highly unethical – and, in some cases, illegal – to collect customer data without your audience's explicit consent.

Be aware of all data protection regulations that may apply to your business, such as GDPR or CCPA, and ensure that you are complying with the law every step of the way.

Ensuring data security is also key: that means making sure that all the data you collect and store is safe and secure from unauthorized access and bad actors.

Providing transparency into your company's privacy policy and requesting explicit consent to collect, store and handle their data is absolutely critical, as well as giving customers the option to deny your access to their data. This also goes a long way in establishing trust with your customers. 

But it's not enough to convey that their data is in good hands – you need to make sure that it stays that way.

This means constantly updating your data security methods, auditing your data management tools and processes, providing adequate training to your staff that manages data, and taking any applicable measures to ensure that your data is continuously up-to-date and secure.

---

Collecting, managing and utilizing big data is a constant and important job. But when you have **accurate, integrated and up-to-date customer data**, you make everything else easier and more impactful for your organization. The better you understand big data and its uses, the more effectively you'll be able to steer your business in the right direction.

To have the highest quality data in every app and enable your departments to collaborate, [use PieSync for a two-way contact data sync between your apps](https://www.piesync.com/why/). From your CRM to your email marketing software and support platform, bring your apps together to enable a data-driven and nimble organization.

cta-10-more-reliable-data-everywhere

10 (FULL) - Data & analytics - more-reliable-data-everywhere

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10 (HALF) - Data & analytics - more-reliable-data-everywhere

Big data is a powerful tool to grow any business. Learn how it's collected, how you can manage your data properly, and how to leverage the full power of big data in your business.

Big data: how is it collected and how can you manage it?

Data & Analytics

big data collection and management

Big data: how to collect and manage it

![computer code on screen for data quality management](//images.ctfassets.net/f2ysq090txql/1US4i7NybF8H2kLPgz7h42/93d58e1ccf28c9d5061a573423c874fd/markus-spiske-qjnAnF0jIGk-unsplash.jpg)

There was a time when gathering data was a hard task. Later on, it was a challenge to integrate data, and then it seemed almost impossible to keep it clean. Nowadays, all these things are not only possible, but necessary. 

Data is a key factor in every aspect of a business, from sales, marketing and customer service to product design, finances and so much more. Processed data becomes information, the most valuable commodity for any company.

This means that in order to make informed, data-driven decisions, you need to have high-quality data to power your business. That's why maintaining **data quality** is so important.

Ensuring [data quality](https://blog.hubspot.com/website/data-integrity) means that your databases are accurate, secure and consistent throughout the data lifecycle stages. Clean, high-quality data translates into efficiency, transparency and consistency throughout a business. 

&nbsp;

## The intelligent use of high-quality data 

Perhaps one of the most common motivations to ensure data quality is personalization. According to research, [85% of organizations](https://www.edq.com/globalassets/white-papers/2017-global-data-management-benchmark-report.pdf) globally experienced more timely and personalized customer communications as a result of improving their data quality. At the same time, 75% of organizations believe that inaccurate data is undermining their ability to provide a good customer experience.

Data quality can determine operational efficiency, customer satisfaction and informed marketing decisions. [52% of organizations](https://www.edq.com/globalassets/white-papers/2018-global-data-management-benchmark-report.pdf) maintain high-quality data to increase efficiency and improve cost savings. A company that invests in the maintenance of its database will see direct benefits: 

- __Lower costs in email marketing.__ Reducing the number of emails sent to inactive users and invalid email addresses can increase opening rates, deliverability, and decrease costs on email marketing platforms.

- __Cross-selling.__ When there's detailed information about a customers' pain points, purchasing behaviors and preferences, this data can open doors for sales departments to offer an additional product or service to an existing customer.

- __Accountancy savings.__ Having up-to-date customer information makes the billing process and credit control more accurate and efficient.

- __Personalized products and services.__ Data integrity provides a faithful approach to the customer. If used correctly, data can provide invaluable insights for companies to understand customers and what they expect from your products and services. 

Companies with quality data and advanced analytics capabilities have gained a significant lead over their competitors in the last few years. According to [Bain & Company](http://www.bain.com/publications/articles/big_data_the_organizational_challenge.aspx), these companies are twice as likely to be in the top quartile of financial performance in their industries. They also make and execute decisions faster.

<RelatedPost slug="automate-business-reporting" />

&nbsp;

## How to maintain a high-quality database

Organizations all over the world are increasingly relying on SaaS solutions to manage their data and increase its quality, recognizing that [data and analytics will provide a key source of opportunity](https://www.edq.com/globalassets/white-papers/2018-global-data-management-benchmark-report.pdf) in the coming years. The most urgent services that these organizations need for their data management are:

- __Removing duplicates.__ Normally, data comes from multiple sources such as web forms, emails and marketing leads. Additionally, in certain cases, contacts are being created by different departments or several agents in the same department. These factors increase the possibility of having duplicated contacts, which means that emailing services can become inefficient and generate unnecessary costs. In addition, the information in your CRM or help desk can get confusing or inaccurate.

- __Minimizing human error.__ Human error is one of the most common ways to lose information. A bad phone number, a spelling error or typo can even make you lose a potential customer. You can minimize the chances of human error by automating essential data management tasks.

- __Real-time data updates.__ Staying on top of data updates is never easy. Automatically updating data across SaaS tools means that all teams get the latest, most accurate data in their tools without the need for manual updates or imports and exports.

An integration tool like [PieSync](https://www.piesync.com/why/) can help you stay on top of your data management by syncing your software stack two ways and in real time. Get started with a free trial now for accurate, consistent and up-to-date data throughout your business.


High-quality data is a key factor in every aspect of a business. Processed data becomes information, the most valuable commodity for any company. Find out how to maintain data quality in order to make informed, data-driven decisions.

A beginner's guide to high-quality data

computer code on screen for data quality management

![Business owner collecting and managing customer data in an office](//images.ctfassets.net/f2ysq090txql/5tvFmZfAAuEtjbrqEoXjsR/4d698590bd0da293b00cc735cd490748/blake-wisz-GFrBMipOd_E-unsplash__1_-min.jpg)

Customer data is the most valuable asset in your organization. Your sales, marketing and service teams all rely on the insights you hold about your customers to deliver the right experiences at the right time, all the way from lead generation to long-term customer retention.

Maintaining an [accurate and up-to-date customer database](https://www.piesync.com/blog/ultimate-guide-to-contact-management/) is essential for delivering personalized interactions at scale: without it, there's no way for your team to remember everything they need to know about thousands of leads and customers. 

But which customer data do you actually need to collect for each department, how should you store it, and what's the correct way to use it? 

Here's our guide to customer data that will walk you through everything you need to know.

----

## The customer data to collect and use for different departments

&nbsp;

### Marketing

Marketing is where it all begins for your customer data. You're creating content and lead magnets that draw attention to your brand, using forms and other [lead gen tools](https://www.piesync.com/blog/10-best-lead-generation-tools/) like live chat to convert those visitors to contacts, and nurturing those contacts to (hopefully) becoming sales-ready leads. Here's the customer data to collect in your marketing team

&nbsp;

#### 1. The basics: name, email, business name

Marketing is usually the department that brings in the highest proportion of new leads, which means the pressure is on to make that information valuable for the rest of the customer lifecycle. This starts with the basic contact data that should be [smoothly organized in your CRM](https://www.piesync.com/blog/guide-to-crm/) as well as [synced two ways with other key apps](https://www.piesync.com/solutions/contacts-sync/) such as your email marketing platform. This keeps all customer information up-to-date everywhere, ready for everyone in any department to locate the latest insights.

&nbsp;

#### 2. Website engagement

At the early stages of a new lead's time with your business, it's important to make sure your website analytics enable you to understand how they are interacting with your business and how you can best deliver the experiences they're looking for. If you're an ecommerce business owner, for example, you could use website activity to recommend other similar products each person might like via email or retargeting ads on social media.

&nbsp;

#### 3. Segmentation data

Information that enables you to segment a contact into the right groups and lists is one of the most valuable types of data to collect early on. This can include data such as team size, industry and role. Not only can this data enable the most personalized messaging and automation, but it also helps to calculate lead scoring.

&nbsp;

#### 4. Subscription preferences

In the very first form that a lead fills out on your website, make sure there's a clear checkbox for them to opt in to marketing communications. This is a crucial part of data protection regulations, but it also enables you to send the most relevant content if you offer a range of options to subscribe to.

&nbsp;

#### 5. Lead scoring

Lead qualification data such as lead scoring is one of the most impactful ways for marketers to help out their sales colleagues. With automated lead scoring in place, points are awarded for positive metrics and behavior and deducted for negative indicators. It's the fastest way to instantly assess how likely a prospect is to buy your product and be a satisfied customer, and ideally starts as soon as a visitor converts to a lead.

Examples of lead score boosters:

- High engagement, such as webinar signups and content downloads
- High amount of time spent on your website
- Visiting high-value pages, such as pricing pages, demo pages and feature pages
- Identification as decision-maker
- High-value market or industry
- Adequate budget
- Team size matches personas
- Annual revenue matches personas

&nbsp;

Examples of lead score deductors:

- Very low engagement with website pages
- Not the decision-maker
- Market or industry you struggle to serve
- Inadequate budget
- Team size doesn't match personas
- Annual revenue doesn't match personas

----

### Sales

Salespeople create and strengthen the bridge for interested leads to become happy customers, guiding each prospect to the right product or service for them. Whether your team works with an [account-based approach](https://www.piesync.com/blog/the-ultimate-guide-to-account-based-sales/) for high-value deals or a more automated strategy that's effective at scale, customer data is crucial. Here's the data that's most important for your sales team to collect and some pointers on how to put it to use.

&nbsp;

#### 1. Deal information

For each closed deal, make sure to create a clear record of all information associated with it as soon as possible. This includes data such as billing amount and frequency, which you can easily [sync from your CRM with your accounting app](https://www.piesync.com/solutions/crm/). It also helps to make sure there's an easily accessible copy of the latest version of the contract in your CRM.

&nbsp;

#### 2. Customer lifetime value (LTV)

Calculating a customer's lifetime value is a really useful metric to forecast long-term revenue. You can measure this by multiplying their purchase value by purchase frequency over your average customer lifespan. With a CRM like HubSpot that has [calculation properties](https://knowledge.hubspot.com/crm-setup/create-calculation-properties), you can keep this updated automatically for your active customers.

&nbsp;

#### 3. Information about decision-makers

Your salespeople get an unmatched view into how each client's company functions. This includes who is involved in the decision-making process. As this same group of people will likely be involved in future onboarding sessions and upgrading discussions, make sure to store relevant information in your CRM. This helps to avoid the awkward scenario of them remembering you while you look anxiously at a blank contact record, or passing the deal to a colleague who has even less background information.

&nbsp;

#### 4. Granular, verified segmentation data

As a sales team gets to know a prospect better, it's a great opportunity to verify their contact record. Check their industry, company size and other key metrics are correct and make sure to [instantly sync this data to other apps](https://www.piesync.com/solutions/crm/) such as email marketing and automation tools that use segmentation.

&nbsp;

#### 5. Closed won and closed lost data

One of the most important metrics for salespeople to collect is why they successfully close a deal or not. Ask for standardized answers to store in your CRM and use this to optimize your product, messaging and targeting, and sales process.

<RelatedPost slug="keep-customer-data-up-to-date-everywhere" />

&nbsp;

----

### Customer service

Customer data collection doesn't finish when a deal is closed. Throughout a customer's time with your company, you can optimize and update their contact record to create the most accurate view of how your company can best serve them. Here's the best customer data to collect in your service team

&nbsp;

#### 1. Customer happiness metrics

Metrics such as NPS (Net Promoter Score) and CSAT (Customer Satisfaction Score) are incredibly useful for any organization to reduce churn and optimize customer experience with a stronger product, strategy and team. These metrics give you a snapshot into how a customer feels about your company and products at any point in time, and with repeated surveys at set intervals, you can monitor how that sentiment changes with time.

Many customer happiness metrics are extremely quick to collect. As one of the most popular examples, NPS simply asks: “On a scale of zero to ten, how likely are you to recommend our business to a friend or colleague?” You can measure NPS and CSAT with tools such as [Wootric](https://www.wootric.com/).

&nbsp;

#### 2. Support ticket data

An insightful way to gauge both individual and overall customer happiness and satisfaction towards your product and support is with your support ticket data. This includes general metrics such as ticket volume, topic and time to resolution, but it's also worth automating data properties for each customer record, such as:

- Last ticket submitted
- Number of tickets submitted

[With automation in your service team](https://www.piesync.com/blog/12-ways-to-improve-customer-experience-with-automation/), you can create instant triggers that let your team know if satisfaction scores drop below a certain threshold or a certain amount of tickets are submitted within a timeframe. Your team can then reach out fast to check how the customer is doing and reduce their likelihood of churn.

&nbsp;

#### 3. Churn risk

By combining metrics such as customer satisfaction and support ticket data, you can create a tailored formula for calculating churn risk. With a [calculation property in your CRM](https://knowledge.hubspot.com/crm-setup/create-calculation-properties), you can then automatically measure this and keep an up-to-date and intelligent view of the customers at the highest risk of churn.

&nbsp;

#### 4. Customer churn reason

It's unfortunate, but it happens: you can't keep every customer forever. If a customer does have to say goodbye, try to understand and record what's behind it in your CRM. Keep these answers standardized (such as "too expensive" or "problems with product") so you can easily create actionable reports instead of sifting through unstructured data.

&nbsp;

#### 5. Customer happiness reason

On the other hand, if a customer loves your company, learn why! Create a standardized set of satisfaction reasons that you can ask your customers with high NPS scores to choose from. 

<RelatedPost slug="how-to-capitalize-on-customer-data" />

----

Collecting, maintaining and utilizing customer data is a job you're never finished with. But when you have **relevant, accurate and up-to-date customer data**, you make everything else easier and more impactful for sales, marketing, service and beyond.

To maintain the highest quality data in every app and enable your departments to seamlessly collaborate on insights, [use PieSync for a two-way contact data sync between your apps](https://app.piesync.com/signup/). From your CRM to your email marketing software and support platform, bring your apps together for the smoothest data-driven operations in your organization.

Customer data is behind everything in your company. Learn the best practices for collecting, maintaining and utilizing customer data in sales, marketing and service.

The customer data guide for businesses: what to collect, maintain and use

Business owner collecting and managing customer data in an office

Customer data: what to collect and how to put it to work in your company

![Build a data driven company best practices](//images.ctfassets.net/f2ysq090txql/18iKXH3Z4HLI4HnKVGC5TO/f06209fd17145c497cfc2868e7cd481f/campaign-creators-NIjzLb8SHfA-unsplash-min.jpg)

Data is a core part of our company DNA here at PieSync. Which you can only expect, really: we exist to help our customers [connect their own data](https://www.piesync.com/why/)!

We've built our company on good data principles and processes from the start that have enabled PieSync to scale effectively with data by our side.

But what exactly has this looked like, and how can you use our learnings to strengthen your own data analytics and reporting? Let's talk you through our best advice.

---

## 9 best practices for reliable analytics and reporting

1. Make the decision to focus on data
2. Find analytics apps that work for you
3. Figure out your core KPIs
4. Use segmentation
5. Divide your data between dashboards
6. Set clear targets for the year
7. Have standardized processes
8. Create a clear overview of the full funnel
9. Do occasional manual checks

&nbsp;

### 1. Make the decision to focus on data

When you have a strong foundation for data management and reporting in place – and you hire for and nurture data literacy – you remove the likelihood of bad data trickling through. 

It starts with __making the decision__ that data is important to your business. This will influence how you hire and train your team and the tools you invest in.

Having multiple eyes on your data also increases accuracy and reliability, as there's more chance of an inconsistency being picked up.

&nbsp;

### 2. Find analytics apps that work for you

As PieSync has grown, we've found that Google Analytics doesn't give us the accuracy we need after the sign-up stage in our customer journey.

To make our reporting more reliable, we switched to [Chartio](https://chartio.com/) to visualize data that we collect via SQL scripts we write inside our team.

Why Chartio? We love the scope for building highly customizable interactive charts and creating the exact outcomes we want with SQL.

Whichever analytics tool you choose, make sure it's cloud-based and you can configure it for maximum accuracy. Simple and accurate analytics beat complex and unreliable analytics every time.

Here are some other great options of tools to [automate your reporting workflows](https://www.piesync.com/blog/15-ways-to-automate-your-ecommerce-business/) with reliable data:

<RelatedPost slug="automate-business-reporting" />

&nbsp;

### 3. Figure out your core KPIs

Ruben, our growth marketing and data visualization pro at PieSync, shares his advice for effective and reliable data analytics:

> "You need to figure out the core KPIs for your company, team, and people. If your reporting is too extensive, people will get overwhelmed and won't use it. You need to decide what's really relevant and who needs to use each dashboard."

By balancing clear and concise data with detailed insights when you need them, you put your company in the best position for tracking and making use of performance data. It's all about finding that __balance between simplicity and complexity__.

<RelatedPost slug="more-reliable-business-data" />


&nbsp;

### 4. Use segmentation

We can't talk about effective data management without mentioning segmentation. __Segmenting your customer data__ enables you to [sync your apps](https://www.piesync.com/why/), send the most personalized emails and create automated workflows that deliver exactly the right content.

When it comes to your performance data, segmentation gives you access to the most insightful analytics.

By slicing and dicing your data, you can drill down into detailed analytics for every area of your organization. It's your best way to understand exactly what's working and what needs work throughout your team and funnel.

&nbsp;


### 5. Divide your data between dashboards

By dividing our data between different dashboards, we can:

* Give everyone a centralized view of the key company analytics
* Give individual teams and roles more in-depth, relevant and segmented insights

__On our company KPI dashboard__, we display only the top-level KPIs that are important for everyone. We keep these top-level KPIs to 5-10 to avoid overwhelming the team with too many numbers.

When you're in the PieSync office in Ghent, these KPIs are always visible on the TV screen. And when we're working remotely, we often share updates via Slack channels to keep everyone up-to-date with how we're performing against the month's targets.

__Our other main dashboards are divided by channel__. As one example, we have a dedicated dashboard for in-depth organic traffic insights. 

By dividing our data between dashboards for top-level KPIs and in-depth channel insights, we have a quick overview of performance and an easy way to understand changing trends.

&nbsp;


### 6. Set clear targets for the year

Our goal-setting process at PieSync is simple. We create clear goals for the year, divide these by month, input these into a sheet, and link this to Chartio.

We then break up these goals into smaller chunks, including by channel. This enables us to easily monitor conversion rates per channel and understand if results are coming from referrals, organic traffic, email marketing, social media, or any of our other key channels.

&nbsp;

### 7. Have standardized processes

Once you have good frameworks and KPIs in place as well as a focus on data integrity, your next step is to make sure you're collecting data in a standardized way. For our team, this means using the same tools and similar processes (such as SQL scripts for Chartio) to collect analytics.

&nbsp;

### 8. Create a clear overview of the full funnel

For our data analytics to be the most effective, we need a comprehensive view of the entire customer journey: from marketing to conversion and on to customer satisfaction. Ruben explains:

> To manage and track everything, you need to have a complete overview of the full funnel.

Having such a broad range of data also helps our team to reach company-wide and individual goals. We can see exactly how we're performing as a company and team, and having a dashboard to show you how close you are to your goals can be a real motivator.

One metric we track in-depth that's specific to PieSync is the popularity of our connections. We pay attention to which connections are bringing in new trials and customers, which ones our customers love, and which new apps are taking off fast. 

As well as creating the clearest overview of your funnel, think about the metrics that are specific to your organization that will help you deliver the best possible customer experiences based on data-driven insights.


&nbsp;

### 9. Do occasional manual checks

To check our data processes are working soundly at PieSync, sometimes we ask multiple people to pull the same data and compare results.

As there are so many ways to query something in SQL, if we get the same results this is a good sign for our data accuracy. It also removes our dependence on highly standardized processes and the need to follow exact steps to get accurate results.

----

To help you build a more data-driven organization, [use PieSync to connect customer data between your apps](https://app.piesync.com/signup/). With a two-way sync ensuring the latest changes are reflected across all business apps, you can enrich data in every app and make your insights more reliable. [Get started with a free trial](https://app.piesync.com/signup/) to get the most out of your customer data.

Data is a core part of our company DNA here at PieSync. Here are some of the best practices we follow for the most reliable analytics and reporting.

9 tactics for reliable data & analytics we follow at PieSync

man typing on laptop while looking at data chart

Build a data driven company best practices

![Using Google Analytics and questioning data accuracy](//images.ctfassets.net/f2ysq090txql/7jayYncTmsMvie5mu5xGIA/26da2db465bdc4a8ea90ce9809cb001e/campaign-creators-pypeCEaJeZY-unsplash__1_-min.jpg)

Despite huge investments in data, most executives __don't trust their business data__. According to a survey of over 2,000 data and analytics decision-makers by [KPMG and Forrester Consulting](https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2016/10/building-trust-in-analytics.pdf), only 38% of respondents have a high level of confidence in their customer insights, and only one-third trust the analytics they generate from their business operations.

The stats shout loud and clear that if you struggle to trust your business data, you're absolutely not alone. However, this doesn't make it any less important to fix it.

Untrustworthy data has repercussions across your entire organization. You run the risk of:

* Pivoting strategies based on incorrect assumptions
* Lacking a clear picture of business performance and ROI
* Delivering poor customer experiences
* Reducing job satisfaction for your team because of manual tasks and frustrations
* Being hesitant to share important insights across the team

Instead, __every business's goal should be data integrity__. Data integrity refers to the quality and reliability of your business data, including how precise, consistent, timely and well-preserved that data is.

With high data integrity, your business can also benefit from the surge in [opportunities that big data brings](https://www.piesync.com/blog/big-data-for-small-businesses/).

Here's our guide to what to do when you can't trust your reporting data. Learn how to turn things around long-term, so your data spend isn't spoilt by leaky processes and frameworks.

---

## How to make your data more trustworthy

It might sound obvious, but if your business has been wrangling with unreliable data for some time, to create a different outcome you __need to do things differently__. 

Fixing untrustworthy data requires changes to your organization's:

* Processes
* Mindset
* Skillset

Let's explore the best ways to make your data more trustworthy so you can benefit from accurate and timely analytics that pave the way for informed decisions.

&nbsp;

### 1. Go back to basics

To make your data more trustworthy, let's go back to the very beginning. Imagine you're starting your database entirely from scratch with a clean slate. Now answer these questions:

* What data do you need to collect?
* What format do you need to collect it in?
* What data __don't__ you need?
* What's the clutter or noise you would like to avoid?
* How do you need to integrate your apps?

You can use these valuable insights to inform:

* New processes for data collection, management and [integration](https://piesync.com/connections/)
* What to clean up and prune from your database
* How to educate your team and increase data literacy in your organization

Once you're clear on what needs to happen, start creating an action plan to put it into place and make your data more trustworthy.

<RelatedPost slug="more-reliable-business-data" />

&nbsp;

### 2. Follow the data trail back to the source

Whenever you're faced with unreliable data, follow the trail back to the source. Where did the inaccurate data originate?

This includes looking at form fields and checking for consistent and standardized data collection. It also means making sure that Google Analytics tags are set up correctly, or that your SQL scripts for your business intelligence platform are flawless. 

If this stretches your tech knowledge, perhaps because the person who implemented your systems has left the company, consider bringing in a data specialist to help you out. You could also get their help simplifying your data processes so it's more manageable in-house going forward.

&nbsp;

### 3. Tick the boxes for data best practice

No matter the industry or company size, there are some best practices that every company should follow for trustworthy data. These include:

* __Consistency__ – Maintain the same format across systems by using consistent and standardized fields and collection processes. When you integrate your apps, [use customizable field mapping](https://www.piesync.com/help/features/new-customizable-field-mapping/) to ensure that the right data is synced to the right places. Here's an example of mapping fields between [Mailchimp and Copper CRM](https://www.piesync.com/mailchimp/copper/) to ensure a seamless sync with [PieSync](https://www.piesync.com/why/):

![Connect Mailchimp and Copper data](//images.ctfassets.net/f2ysq090txql/2tVpolQKugzKlybU2J7yeZ/26a1dcadf247fcbe17f445124d35e1e1/Screenshot_2020-06-04_at_16.36.54.png)

&nbsp;

* __Completeness__ – For each piece of data, you need to know the full picture. A few examples are the source of your marketing leads, sales history for your customers, or conversion path for new deals. Is your data complete? 

* __Centralized and enriched data__ – Rather than having fragmented and incomplete data spread across several systems, maintain one centralized database with the most up-to-date and trustworthy information. This can be your CRM for your customer data, and a system like [Chartio](http://chart.io/) or [Supermetrics](https://supermetrics.com/) for your company performance data. [Create two-way integrations](https://www.piesync.com/solutions/crm/) between your centralized database and connected apps to enrich your data everywhere.

* __Access control__ – Set permissions and policies that ensure only the right people see certain data. This is about balancing accessibility and transparency with security.

* __Validation__ – 28% of customer and prospect data is suspected to be inaccurate in some way, according to [Experian](https://www.edq.com/blog/highlights-from-our-2020-global-data-management-research/). For accurate data, you need a method for checking and validating it. This can include automated processes for checking for anomalies and missing fields, backed up by some manual checks.

* __Real-time updates__ – For the best results from your data, it needs to be up-to-date. Look for real-time updates when choosing a business intelligence system and a data integration solution.

* __Quality sources__ – Make sure you know where all of your data is coming from and that you can guarantee its integrity. Maintaining a neat and tidy database that you know you can trust beats having highly advanced data sets that you struggle to make sense of or control.

* __Cleanliness__ – Considering B2B data decays at a rate of [70% per year](https://biznology.com/2015/02/b2b-data-decay-list-rental-buyer-beware/), your database needs frequent clean-ups. It's important to [freshen up your data](https://www.piesync.com/blog/top-4-clean-data-tips-for-your-database/) by removing duplicates, inaccuracies and other data that's turned from value into clutter.

* __Security and protection__ – Maintaining high security is crucial for data protection regulations such as GDPR in Europe, but it's also just a basic principle for being a trustworthy brand. It's also absolutely crucial if you want valuable data at your fingertips (and only yours).

* __Integrations__ – According to [an IDC survey](https://www.entrepreneur.com/article/286084), over 80% of business leaders surveyed agreed that problems arise because they have different internal systems and applications that don’t ‘talk’ to each other. You can fix this by adopting [an integration platform like PieSync](https://www.piesync.com/blog/what-is-ipaas-a-guide-to-getting-started-and-best-practices/).

&nbsp;

### 4. Document processes

One common trap that organizations fall into is __relying on one person to set up and manage their data processes__. When that person leaves the organization, chaos is often unleashed. 

You can avoid this by creating clearly documented processes that are stored in your company wiki, Google Drive or a tool like [Notion](https://www.notion.so/product). And remember: overly complicated processes might end up doing you more harm than good. The simpler your processes, the better...

&nbsp;

### 5. Simplify everything

Complexity is often the root of bad data you can't trust. For complex data analytics to work successfully, you need the time, resources and knowledge to back it up. 

For most organizations, it's more effective to __keep your data and reporting as simple as possible__ instead. 

Simplifying your data means:

* Only collecting the data you need
* Organizing data consistently and in standardized formats
* Avoiding complicated workflows and systems
* Reducing your reporting dashboards
* Avoiding multiple systems for the same job
* Creating documentation that's clear and easy to understand
* Amending processes so anyone can quickly understand them

To make your data the most trustworthy, ask yourself: where can you simplify your data collection, management and [integration processes](https://blog.hubspot.com/website/5-common-data-integration-challenges-and-how-to-solve-them)?

<RelatedPost slug="automate-business-reporting" />

&nbsp;

### 6. Keep the sunk cost fallacy in mind

You've invested a lot of money, you have complex systems in place... and you don't want to throw that away. So instead of starting afresh, you build on top of what you have – and hope it will cover up what's underneath.

[Investopedia](https://www.investopedia.com/terms/s/sunk-cost-trap.asp#:~:text=Sunk%20cost%20trap%20refers%20to,money%20they%20have%20already%20invested.) describes the sunk cost fallacy, or the sunk cost trap, as "a tendency for people to irrationally follow through on an activity that is not meeting their expectations. This is because of the time and/or money they have already invested."

This is all too common when it comes to business data and analytics.

If you keep building on unsound foundations, it will come back to bite you. Begin by understanding exactly what you're dealing with and the problems at hand. Bring in a second opinion here if you need it. Then, make as unbiased a decision as possible about what you need to do to increase data integrity. 

Over the long term, it might be easiest to go back to the drawing board, create a much more straightforward and accurate strategy, and trash what you had in place before.

&nbsp;

### 7. Communicate with stakeholders

While concerns over untrustworthy data are often valid, sometimes you or your organization's stakeholders *still* don't trust your data when everything is sound.

If this is the case, clear communication is your way forward. Explain why your business analytics data is trustworthy and how it's set up to ensure reliability. Answer questions to help stakeholders understand how data is collected, managed and integrated between your apps. Also, encourage concerns to be voiced so that you can explore their validity or irrelevance together.

----

As your next step to making your data more trustworthy, use PieSync to integrate your contact data between your apps, enrich data everywhere, and create a centralized hub that's instantly updated when anything changes. [Get started with a free trial now](https://app.piesync.com/signup/).

Untrustworthy business data is all too common, but that doesn't mean it's harmless. Learn what to do when you can't trust your business data.

What to do when you can't trust your business reporting data

man typing on computer while looking at graphics and charts

Using Google Analytics and questioning data accuracy

Nimble

![IT team working with laptops in a coworking space](//images.ctfassets.net/f2ysq090txql/PX3Vf0fiMYs9450IRlBQ1/5dabb9783b0b03ff968f35bc134318b9/annie-spratt-608002-unsplash.jpg)

_How can your IT business optimize its operations? One important step is syncing data between your key apps. Learn how to create a strong data management strategy in this post by Richard Tubb, one of the top experts in the global IT Managed Service Provider (MSP) community._

----

How many [cloud-based apps](https://www.piesync.com/blog/the-saas-guide-the-tools-and-trends-shaping-tech-in-2020/) do you use in your IT solution provider or managed service provider (MSP) business? Five? Ten? Fifty? You probably use more apps than you realize.

As the former owner of an MSP business myself, the most important apps in our stack were:

- A customer relationship management (CRM) tool
- A professional services automation (PSA) tool
- An accounting package

Each tool was super important to our business. We needed to track our prospects (marketing), turn them into clients (sales), provide services to those clients (service delivery) and bill those clients for the work we’d done (accounting).

If that process was to work efficiently, each app needed accurate data from the other apps we used. This is easier said than done!

Many IT businesses I work with spend an inordinate amount of time manually moving data from one app to another - often bringing along the typos and mistakes that come with manual input. This leads to inefficiency at best and costly mistakes at worst.

“What’s the first sign of madness? Keeping multiple bits of the same data in different applications and updating it (manually) on different systems”, says [Chris Timm](https://twitter.com/tegwin) of [Sondela Consulting](https://www.sondelaconsulting.com/), a business consultant for MSPs.

So just how can you successfully link your IT business's cloud-based applications so that they are serving you? Let’s take a look.

&nbsp;

## Why you need to sync data between apps

If you want to avoid manually uploading data between the multitude of cloud-based apps you use, you need to make sure those apps talk to each other. This means __syncing data between them__.

This is sometimes done via a manual process, or exporting data from one app and importing into another. But it’s best if you look for [automatic processes](https://www.piesync.com/why/): systems where changes in one app are automatically synchronized with another.

> “It's important to ensure that data is synced across different platforms to maintain consistency and data integrity. It makes you more efficient as you only have to update it in one place and the other systems are updated accordingly” – Chris Timm of Sondela Consulting

Think of the relationship between your Remote Monitoring and Management (RMM) tool and your PSA tool.

If you had to manually add each new workstation and printer to your PSA configuration, you could spend a long, long time keeping data between your RMM and PSA up to date.

Yet this is what many IT businesses spend their time doing.

When we spoke about this painful scenario, Chris Timm shared with me: “Not keeping data synced (automatically) across applications is like re-inventing the wheel every time you work”.

The most progressive MSP businesses don’t handle their app data in silos. They __understand the value of automatically sharing it between apps__.

<RelatedPost slug="6-ways-to-optimize-your-saas-stack-with-piesync" />

&nbsp;

## Synced data makes you more efficient

Syncing data between apps [make your staff more efficient](https://www.piesync.com/blog/small-business-guide-to-contact-management/) by keeping everything up-to-date at all times.

If your MSP business has linked its RMM and PSA tools and a client adds a new workstation, then your RMM tool discovers it and automatically adds that workstation configuration to your PSA tool.

The PSA tool then makes that data available to Service Delivery, avoiding the embarrassing scenario of a client calling your helpdesk, only to be told: “Oh, we didn’t know about that PC...”

Very importantly, once your PSA tool knows about a workstation, it can then tell your accounting package to bill for work effectively.

This is hugely important. In my work with IT businesses I see an *enormous* amount of lost revenue where MSPs are simply not billing for workstations they are supporting for their clients.

For me, this is the number one reason that IT companies need to [sync data between their cloud apps](https://www.piesync.com/connections/) - to __increase their billable revenue__.

<RelatedPost slug="contact-management-for-productivity" />

&nbsp;

## Keeping every department in sync

Setting up automatic synchronization between different apps means that every department in your business is aware of the latest data.

> “When you sync data across multiple applications, it keeps every department of your company up to date by ensuring that data is never duplicated across teams” – Chris Timm of Sondela Consulting

Within my business, we use [Nimble CRM](http://tubb.co/TubblogNimbleCRM) to track sales opportunities and leads.

Thanks to [PieSync](https://piesync.com/why), any new contacts we enter into [Nimble automatically get synchronized into Google Contacts](http://piesync.com/nimble/google-contacts/) - and any contacts we enter into Google Contacts are synchronized to Nimble CRM too. It’s a two-way process! 

Once a prospect has been converted into a client, there’s no retyping data. The new client's info is automatically available to the PSA tool, [ConnectWise](https://www.piesync.com/connectwisemanage/), thanks to data synchronization.

When you’re ready to bill that new client, the accounts package, [Xero](https://www.piesync.com/xero/), automatically has all the information it needs, thanks again to data synchronization.

No missed billing. No mistyped data. __Just a set of applications that work together__. It’s so simple, yet so effective.

&nbsp;

## A strong tech stack is a connected stack

Take five minutes to do a quick audit of your IT businesses. List the cloud-based apps you use to manage your business on a day-to-day basis.

How many of these apps are synchronizing their valuable data to the other apps you use?

If you’re not synchronizing data, and instead are relying on manual methods, then you should expect to lose time and miss revenue opportunities.

Instead, realize that this data is the lifeblood of your business and needs to be freed from the [silo it is currently trapped in](https://www.piesync.com/blog/data-silos-what-they-are-what-causes-them-and-how-to-fix-them/).

Synchronize your data and watch the efficiency of your business rise, along with your profits!

#### [Get started with a 14-day free trial of PieSync to connect your apps and enrich your customer data on every platform.](https://app.piesync.com/signup/)

Reliable and up-to-date data is crucial for any IT business. Learn how to optimize your organization's data with data syncing between your key apps.

Why your IT businesses should sync data between its cloud apps

IT team working with laptops in a coworking space

 How IT businesses can sync data between their apps automatically

![Person managing business data to make more reliable](//images.ctfassets.net/f2ysq090txql/3O0vdUb4Adf4PfaXH9Z9jf/9e069076c656a47897628abea6b7cc27/brian-jones-xLBNRz5Fy78-unsplash-min.jpg)

Your business data is the lifeblood that runs through your organization. It powers automated workflows, gives customer service reps the full story every time the phone rings, and informs decision-making. 

[Even small businesses can benefit from the rise of big data](https://www.piesync.com/blog/big-data-for-small-businesses/) by optimizing their organization's data and creating processes to put it to work. According to [Experian](https://www.experianplc.com/media/news/2020/the-cost-of-data-debt-rises-as-businesses-face-the-challenge-of-low-data-literacy/), eight in ten businesses believe data is one of their most valuable assets.

When your business data is reliable and accurate, it's smooth sailing. But when errors, duplicates and question marks surface... it's not so pretty. When you can't trust your business data, problems quickly arise and multiply in every area of your organization. 

Businesses lose as much as 20% of revenue due to poor data quality, shares [Kissmetrics](https://www.ringlead.com/blog/10-stats-about-data-quality-i-bet-you-didnt-know). Back in 2013, HBR also talked about the ripple effect of unreliable data as part of ["Data's Credibility Problem"](https://hbr.org/2013/12/datas-credibility-problem):

> "When data are unreliable, managers quickly lose faith in them and fall back on their intuition to make decisions, steer their companies and implement strategy. They are, for example, much more apt to reject important, counterintuitive implications that emerge from big data analyses."

To get the best results as a data-driven organization, here are some of the best practices to strengthen the foundations and make your business data the most reliable it can be.

---

## 9 ways to fix unreliable data and increase accuracy
&nbsp;

### 1. Improve your data foundations

Data debt – the cost attached to poor governance of data in a business – is a significant problem for many organizations, and 36% of businesses say data literacy is crucial to future-proof their organization, shares [Experian](https://www.experianplc.com/media/news/2020/the-cost-of-data-debt-rises-as-businesses-face-the-challenge-of-low-data-literacy/). 

Making your business data more reliable doesn't just happen by magic: it requires strong frameworks, processes and a data-literate workplace. As early in your business journey as possible, ensure that you have:

* A strong CRM system to [centralize all contact data](https://www.piesync.com/solutions/crm/)
* Processes to organize and segment data
* [Integrations between apps](https://piesync.com/)
* Formal data literacy programs in place to educate your team
* A clear strategy of how you will use and maintain the data you collect

Remember the old proverb: the best time to plant a tree was 20 years ago, the second best time is now. The same goes for getting your data in order!

<RelatedPost slug="6-ways-to-optimize-your-saas-stack-with-piesync"/>

&nbsp;

### 2. Look at where new data is coming from

Just like reliable data, messy and unreliable data doesn't happen accidentally. There's always a source. To make your business data more reliable, follow the trail back to where data is coming from. 

How is data being added to your CRM? Are there forms or manual imports that are causing bad data to clutter your database? Are different team members importing conflicting data in different ways to multiple apps?

<RelatedPost slug="small-business-guide-to-contact-management"/>

&nbsp;

### 3. Optimize forms and data collection channels

Once you have identified how new data is entering your apps, take some time to optimize these data collection channels. 

To collect valid and reliable data, make sure that these factors are true for every piece of data you collect:

* You actually need to collect the data
* You are collecting it in a consistent and standardized format between apps
* You have clear permission to collect it based on data protection regulations
* It will be stored and organized in the right app for the right purpose

&nbsp;

### 4. Break down the silos

A recipe for unreliable data is having [data silos](https://www.piesync.com/blog/data-silos-what-they-are-what-causes-them-and-how-to-fix-them/). A data silo is a collection of data that one department has access to but others do not.

The negative effects of data silos are bad news for performance and productivity for any organization: they include a lack of transparency, efficiency, collaboration and trust.

To remove data silos, use a central CRM between departments, [connect data between the apps in your tech stack](https://piesync.com/why/), and focus on building a culture of collaboration between departments.

<RelatedPost slug="data-silos-what-they-are-what-causes-them-and-how-to-fix-them"/>

&nbsp;

### 5. Segment your data

Good business data is organized, adds value to your company and is collected with explicit permission from users. To make your data more organized, segmentation is your friend.

Segmentation can look like __labels, tags, list memberships, groups or other properties__ that tell you more about each contact and divide your database into clear categories of preferences, demographics, buying history and more.

When you integrate your data between apps using an iPaaS (Integration Platform as a Service), you can [create syncs based on your segments](https://www.piesync.com/blog/how-to-use-if-then-rules-for-a-more-productive-business/) and connect the right data two ways between your apps.

&nbsp;

### 6. Clean up your databases

To make your business data more reliable, [clean up any messy data](https://www.piesync.com/blog/top-4-clean-data-tips-for-your-database/) as soon as possible. This means fixing or removing:

- Incorrect data
- Outdated data
- Duplicate data

According to [SiriusDecisions](http://www.prweb.com/releases/2008/12/prweb1753164.htm), on average it costs about $1 to prevent a duplicate, $10 to correct a duplicate and $100 to store a duplicate if left untreated.

To help prevent duplicates and other bad data, create company-wide standards for data entry and maintenance, then [sync data from the most accurate source to your other apps](https://www.piesync.com/why/) and create a holistic view of your database. It's also valuable to set up and document processes to standardize and verify new data.

<RelatedPost slug="4-ways-to-fix-and-prevent-duplicate-contacts-for-cleaner-data"/>

&nbsp;


### 7. Connect your apps to integrate data

The most effective data management strategies __connect data between apps__. This removes data silos, creates an integrated view of all of your data and syncs up-to-date data to the right places as soon as anything changes.

The easiest way to achieve [quality data integration](https://blog.hubspot.com/website/5-common-data-integration-challenges-and-how-to-solve-them) is with a zero-code [iPaaS solution](https://www.piesync.com/blog/what-is-ipaas-a-guide-to-getting-started-and-best-practices/) that connects the dots between all of your key business apps, from your CRM to your email marketing system and customer support software. [You can do this with PieSync](https://app.piesync.com/signup/).

![Customizable contact sync with iPaaS](//images.ctfassets.net/f2ysq090txql/5ZVmOJjYaJcmcO897ITCrN/7f40476dd5a44da9c273599e347efab6/Customizable_contact_sync_mapping_infographic-c5d90308ac2590bfac0dbafc138c0ddf.png)

&nbsp;

### 8. Create accessible reporting dashboards

Instead of hiding your data insights away on private dashboards, make them transparent to the right people in your team. For many KPIs, that means your whole team.

Organizations with the most effective and reliable data typically choose a limited number of impactful KPIs and make these very visible inside the team. 

Not only does this help your team to be invested in company, team and individual performance, but it increases the odds that errors and discrepancies in your data are picked up on. *The most reliable data has eyes on it. *

<RelatedPost slug="automate-business-reporting"/>

&nbsp;

### 9. Schedule regular maintenance

Maintaining data quality in your business isn't a one-time job: it requires continual upkeep, cleanups and optimization. If your organization has a dedicated operations manager, part of their job role can be to monitor and optimize data quality. But in any case, it's worth making data integrity and literacy part of your company DNA – or part of every team member's day-to-day role.

This means creating the foundations for healthy data to flow into your organized and undergo regular cleansing, alongside processes to fix problems and automate integration. 

By optimizing data reliability, you can ensure your company can receive the most accurate results and insights from your database both now and further down the line as data integrity keeps gaining importance. 

----

For the most reliable data, [use PieSync to connect your business tools](https://app.piesync.com/signup/) and enrich your data in every app. With automated two-way syncs between apps including your CRM and email marketing tool, you're in the best position to manage your data holistically, perform regular health checks, and create an updated 360-degree view of your customer data.

Maintaining data quality and integrity requires clean data collection, integration and optimization. Here's how to get it right and fix unreliable data.

9 ways to make your business data more reliable

data analyst working with spreadsheet on laptop

Person managing business data to make more reliable

![Leverage big data as a small business](//images.ctfassets.net/f2ysq090txql/6wwewkhDzN0iChUcXgk4aS/13a875ba931dd4e0327f93ce6f907b82/pietro-jeng-n6B49lTx7NM-unsplash.jpg)

The amount of data in the world is growing exponentially. By the time you finish reading this page, [90 million texts](https://www.domo.com/assets/downloads/18_domo_data-never-sleeps-6+verticals.pdf) will be sent and received. 350,000 Instagram posts will be uploaded. 1.2 million Skype calls will be made. 21 million GB of traffic will be received on the internet. 

Big data is everywhere, from the Netflix shows we watch to the social media we browse. But did you know that big data can also benefit your small business?

61% percent of companies say that big data drives revenue because it [delivers deep insights into customer behavior](https://www.capgemini.com/resource-file-access/resource/pdf/big_fast_data_the_rise_of_insight-driven_business-report.pdf). With this valuable intelligence, you can delve deeper into the collective psyche of your customers – and find out what consumers _really_ think.

Imagine you could guess what customers purchase – and when and how. Big data isn’t a crystal ball, but it can certainly help you make smarter, faster decisions about the future of your business.

---

## What is big data?

In the simplest of terms, big data is "big" amounts of data. It can be structured, unstructured or semi-structured. It can be collected and shared and analyzed. 

Big data is all of the information that we create. Emails. Texts. Tweets. TikToks. It’s data that passes from digital devices to routers to servers to clouds and back again. 

To [quote](https://www.ringlead.com/blog/20-inspirational-quotes-about-data) the famous computer programmer Daniel Keys Moran: 

> "You can have data without information, but you cannot have information without data."

Here’s a [helpful definition of big data](https://www.investopedia.com/terms/b/big-data.asp) from Investopedia:

> "Big data refers to the large, diverse sets of information that grow at ever-increasing rates. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered. Big data often comes from multiple sources and arrives in multiple formats."

Big data isn’t perfect, but it’s one of the most powerful weapons in any marketer’s arsenal. Leverage big data in your [small business](https://www.piesync.com/blog/make-your-business-more-organized/), and you can move more customers through your sales and marketing funnels. It’s as simple as that.

<RelatedPost slug="top-5-problems-with-big-data-and-how-to-solve-them" />


Here are some eye-watering facts about big data:

- Big data could add more than [6 million jobs](https://www.disruptordaily.com/7-facts-know-big-data/) to the American economy.
- Data production will be [44 times higher](https://www.modeln.com/blog/10-interesting-facts-big-data/) in 2020 than it was in 2009.
- Humans generate [2.5 quintillion data bytes](https://techjury.net/stats-about/big-data-statistics/) every 24 hours.
- Google processes more than [4,000 search queries every single second](https://www.disruptordaily.com/7-facts-know-big-data/) –that’s 3.5 billion searches a day, or 1.2 trillion a year.

---
 

## The benefits of big data for small businesses

It’s important to note that big data on its own won’t do much for your organization. However, the right technology systematically extracts large data sets from various sources so you can find patterns, trends and correlations in this data. 

The best analytics tools provide you with deeper insights into your business operations and replace many of the manual methods associated with data analysis.

Read on for some of the main benefits of using big data in your small business.

&nbsp;


### 1. Big data cuts costs

Big data can have a significant impact on cost-cutting in your organization by identifying expensive processes and redundant workflows. With the latest data, you can find areas of your business to scale up or down. This can have long-term financial benefits.

The true cost savings associated with big data depend on the size and scope of your small business. However, real-world examples prove the cost-saving capabilities of big data analytics.

One real estate company, for example, cut costs by [15 percent](http://tech.co/big-data-small-business-2015-01) when they incorporated big data into their business model. After comparing maintenance charges for contractors with other vendors, they discovered big data provided them with significant financial benefits. In particular, big data analytics allowed them to identify and reduce invoice-processing errors and automate many service schedules.

How much will you save with big data?

&nbsp;


### 2. Improve customer service

Big data drives [better customer service](https://www.piesync.com/blog/9-ways-to-improve-customer-care-with-technology/). With real-time insights into your customer base, you can discover how consumers think and behave – and make changes to your business as a result. 

Personalized customer service derived from big data analytics will help you engage with customers on a deeper level and provide customized service that drives sales.

"Big data is poised to help marketers reach and engage customers and prospects in ways that businesses are only now starting to understand," [says business journalist Allen Bernard](https://www.cio.com/article/2385922/how-big-data-can-improve-marketing-and-customer-service.html), writing for CIO.com. "Enterprises that don’t embrace analytics may soon see embattled customers voting with their wallets."

Customer service is more important than ever, and more small businesses are using big data to retain consumers. Why? Just a 5 percent increase in [customer retention](https://www.piesync.com/blog/12-ways-to-improve-customer-experience-with-automation/) generates more than [25 percent of profit increases](https://www.providesupport.com/blog/5-ways-big-data-will-improve-customer-service/).

&nbsp;

### 3. Identify (and solve) problems

With big data, you can finally answer all those nagging questions: why do customers abandon their carts? When are customers likely to make a purchase? 

Data analytics tools can give valuable insights into customer behavior as they move through your funnels.

Although data analysis isn’t an exact science, it provides you with the tools you need to solve a wide range of complex problems in your small business. As well as tracking customers, you can solve issues associated with suppliers, investors and other clients. With real-time reports, you get a 360-degree overview of your business, and you can make smarter decisions going forward.

Research shows that, on average, most small businesses only analyze [12 percent of their data](https://blog.qlik.com/10-eye-opening-stats-about-the-growth-of-big-data). However, small businesses can leverage this by focusing on the data they already have, organizing and integrating it, and implementing new analytics processes.

&nbsp;

### 4. Increase in revenue

Big data increases revenue in various ways. Analytics provide you with in-depth intelligence into the customer lifecycle, and you can identify new ways to encourage sales. 

Good data might give you the confidence you need to launch a new product or diversify your business, and this could prove lucrative. 

On average, companies that incorporate big data into their business generate a profit increase of [8 percent](https://www.entrepreneur.com/article/325923). Do the same, and it could be the best investment you make in your small business this year.

"Most people used to think that big data was only for big business. But, as time goes on, it is clear that this technology is for everyone," [says Entrepreneur](https://www.entrepreneur.com/article/325923).

&nbsp;

### 5. Manage your team

Big data also makes it easier to manage the team in your small business. You can identify employees that provide you with the most value, for example, or employees who require additional resources or training. This is because analytics systems generate insights that help you [increase productivity](https://www.piesync.com/blog/work-from-home-productivity/) and keep employees happy.

"The value that big data brings to managing employees is in identifying and analyzing the relationship between engagement and retention," [says employee engagement website Hppy](https://gethppy.com/employee-engagement/big-data-key-effective-employee-engagement). "How and why people are engaging with what they do, how does that translate into the business metrics, and what you can improve to retain them."

Combined with [a great team culture that inspires engagement](https://www.piesync.com/blog/how-to-build-a-strong-team-culture/), the tech stack you use can make all the difference when it comes to managing your team. With an Integration Platform as a Service (iPaaS) like PieSync, you can [connect your cloud-based apps](https://www.piesync.com/connections/) for enriched data and the broadest range of insights.

<RelatedPost slug="what-is-ipaas-a-guide-to-getting-started-and-best-practices" />

----

## How small businesses can leverage big data

Remember: big data is only one slice of the pie. It’s the processes and solutions that collect, store and analyze all your data and act on these that best serve your business.

So, how can your small business leverage big data for the best results?

&nbsp;

### Use your CRM intelligently

You probably already use a CRM to manage your customer information, but you're not necessarily getting the best results from the data inside it. 

Before diving into other analytics tools, fully explore the data you already have in your CRM. Here are some valuable questions to ask as you do so:

* What do we know about the people we serve?
* How can we leverage this data to deliver the most value?
* How can we use this data to provide [a more personalized experience](https://www.piesync.com/blog/why-marketing-personalization-is-so-important-and-how-to-use-it/)?
* What automations and new processes can we power with this data?

&nbsp;

### Explore other analytics solutions

A CRM can only tell you so much about your prospects and customers. With big data analytics solutions, however, you can analyze all the data inside your CRM (and other programs in your tech stack) and find patterns in all this data. 

G2 Crowd shortlists some of the [best big data solutions](https://www.g2.com/categories/big-data-analytics) on the market, including [Azure Databricks](https://azure.microsoft.com/en-gb/services/databricks/) and [Splunk](https://www.splunk.com/). 

However, if you want a more accessible data strategy, start with the apps you already have and look into a platform such as [Clearbit](https://clearbit.com/) to help fill the gaps in your data and enrich what you know about your contacts.

Big data software needs to be user-friendly and flexible enough for everyone in your team who manages data. It also needs to be tailored to your budget and requirements. As a small business, you likely won’t benefit from a data program designed for the world’s biggest multinationals.

&nbsp;

### Integrate your data

Any data solution is only as good as the data it uses, and out-of-date and inconsistent information won’t provide you with any useful insights. You need to make sure your data is synced and integrated.

By deploying an integration solution like PieSync, you can [keep your contact database consistent and up-to-date between apps](https://www.piesync.com/) in order to ensure your customer data is well-integrated across your app stack. You can sync contacts in real time and streamline contact management.

&nbsp;

### Create insightful reporting

Once you have interesting data at your fingertips, you need a way to visualize it. With clear reporting, you can easily make deductions and share your insights with other team members and stakeholders.

<RelatedPost slug="automate-business-reporting" />

&nbsp;

### Act on your data 

Once you have useful data in your business, what can you do with it? The short answer: __automation, personalization and customization__.

Here are some of the most impactful ways to take advantage of big data as a small business:

* Personalize your emails
* Segment your email lists
* Use SEO research to influence your content strategy
* Use dynamic or smart content on your website based on device, geography, lead status, or other properties to customize content
* Send the most relevant content to a prospect based on their preferences
* Trigger internal workflows based on customer actions to provide the best service
* Create A/B tests for emails and automatically send the best content
* Pivot your company or team strategies to match what's performing best
* Deliver the most relevant advertising and channel your spend to top-performing channels and campaigns
* Automatically organize contacts into the most relevant groups and lists in your CRM

----

Big data can benefit your business in various ways, from increased sales to better team management. 

However, you need to leverage all this data properly to optimize your workflows and grow your small business to its full potential.

Regardless of the big data processes and tools you choose, it’s important to keep your contact database up to date. Otherwise, you'll be limited in the results you can get from your customer data.

PieSync keeps your contact database consistent between apps so you have better, more accurate data everywhere. [Start with a free trial here](https://app.piesync.com/signup/).

Big data isn't just for huge corporations. Here's how your small business can benefit from big data and make the most of the advantages.

Big data: how small businesses can leverage the benefits

Leverage big data as a small business

Autopilot

![data-driven decisions](//images.ctfassets.net/f2ysq090txql/1aAXH5geG0pdASsYfZ8Z9C/d6af78a39898ddebd2fb54d790310c51/Depositphotos_201321560_l-2015.jpg)

How big is your business database? From the moment someone becomes interested in your product or service and long after the purchase, you are collecting data – and it can multiply fast.

Thanks to cloud-based platforms, even small businesses have access to a broad variety of tools to gather massive amounts of information. But it's easy to fall into a "more is better" trap when really the quality of your data is most important of all.

After all, collecting large amounts of information is less of a challenge than [managing data efficiently](https://www.piesync.com/why/) and [ensuring its quality](http://piesync.com/blog/more-reliable-business-data/). Then, and only then, can business owners make data-driven decisions such as how to:

* Pivot your business to match consumer demand
* Offer the best customer experiences
* Introduce new products
* Personalize marketing content
* Scale effectively
* Channel your budget

Let’s examine the two biggest obstacles of data management and how to use technology to overcome them so you can make more data-driven decisions.

---

## The main obstacles of data management

&nbsp;

### 1. The overwhelming amount of data from different sources

According to the [2020 Blissfully Report](https://www.blissfully.com/saas-trends/2020-annual-report/#spend), the average small business uses 102 different apps and a mid-market business uses an average of 137 apps.

Your marketing team needs at least one tool for lead generation, email marketing and automation. Meanwhile, your sales team uses a CRM and your accountancy team manages your finances with another piece of software. Then there are apps for smooth business operations like GSuite or Outlook, your ecommerce store, surveys platforms and VoIP. 

All these applications contain relevant customer and lead data from interactions with leads, prospects or customers at different stages of their journey. 

When you are choosing applications for your SaaS stack, you might choose to go for all-in-one solutions to reduce complexity and connect various data sources to offer a wider scope of customer data. For instance, marketing automation software [Autopilot](https://www.autopilothq.com) can take over your lead generation, capture, scoring and nurturing throughout the customer journey.

Integrated systems or hubs exist for other areas of your business like sales, finance or ecommerce. But as your business grows, you'll likely adopt more tools on top of them to add functionality and handle additional customer touchpoints.

These tools have their own way to store data and the problem is that most of them are not really “talking to each other”. The lack of communication between apps leads to a major data management challenge for businesses of all sizes: data silos.


<RelatedPost slug="more-reliable-business-data"/> 

&nbsp;

### 2. Data silos 

Cloud software has made a lot of things easier for businesses: you can work anywhere, stay up to date on every device, and not rely on hardware updates.

But even when you are using cloud-based applications across your business, most of them are not natively integrated.

As a result, little fragments of customer data are isolated within these applications. When that happens, __you have a data silos problem__.

<RelatedPost slug="data-silos-what-they-are-what-causes-them-and-how-to-fix-them"/> 

[Data silos](https://www.piesync.com/blog/data-silos-what-they-are-what-causes-them-and-how-to-fix-them/) can be kryptonite for businesses. They make it impossible to have a 360-degree view of your customers when your data is isolated. Since each one of your teams is looking at their own particular subset of data, decisions will rarely be aligned and definitely not driven by the data that matters to everyone.

![perspective](//images.ctfassets.net/f2ysq090txql/53QDSOJssmr8mEpRK6k4eV/ccbe2d377df2102d876106a6f01eec0f/data_silos.jpg)                                       

Even when there is good communication between teams, sharing quality data has its structural challenges. 

In its [B2B Marketing Benchmark Report](https://content.marketingsherpa.com/data/public/reports/benchmark-reports/BMR-B2B_Marketing.pdf), MarketingSherpa indicates that 61% of B2B marketers send all leads directly to sales; however, only 27% of those leads are qualified. Many sales teams are accidentally spending time on leads that their marketing colleagues have already identified as cold.

When native integrations are not available, the best way to have the right data in the right tools is __through third-party integration services.__ 

Ray Popoola, Motivational Coach at [Mindgroup Coaching Academy](https://mindgroup.ch), uses [PieSync to integrate Autopilot](https://www.piesync.com/autopilot/), Google Contacts and his CRM: 

> “When it comes to data, I want to avoid manual labor. Touching customer data can only lead to errors. Having PieSync syncing my business platforms in the background improves the quality of the information and saves me time. With PieSync I know I’ll have access to the data I need in all my tools.” 

Many of Mindgroup’s new leads are captured on their website and stored on Autopilot, where they'll start their customer journey.  

Additionally, Ray uses his phone to contact new and existing clients. If Ray didn’t have a sync between Google Contacts and Autopilot, it would be an anonymous call. 

> “Thanks to PieSync, when a client calls we already know who this person is and what they bought. I already have the contact information available on my mobile. That makes the conversation a lot easier and it generates a better experience for the customer.”

Thanks to the [two-way sync](https://www.piesync.com/why/) Ray set up, the information collected during the phone call can also be immediately added directly to Google Contacts and Autopilot.

![autopilot google contacts crm](//images.ctfassets.net/f2ysq090txql/4CoqdDWoxNz9mHvVdamxvj/3e0c205a5f600af0344a0791c34b2f89/autopilot_google_.png)

---
      
## Data syncing in action 

Before PieSync, Ray's customer data was isolated in different apps. This was affecting his ability to [align his marketing and sales efforts](https://www.piesync.com/solutions/sales/), which is essential for business owners to make informed decisions that grow their business. 

Data synchronization can make this alignment a lot easier by having: 

1. The right marketing leads and their qualification data [in the CRM](https://www.piesync.com/solutions/crm/).
2. The right customer attributes collected by the CRM available [on the marketing tool](https://www.piesync.com/solutions/marketing/).

Let’s examine an effective way to have [Autopilot and a popular CRM like HubSpot](https://www.piesync.com/autopilot/hubspot/) in sync. 

Every time a lead engages with your marketing content, such as by filling out a sign-up form or downloading an ebook, your marketers collect information that helps you know a little bit more about each lead. It allows you to qualify them.

After identifying a sales-ready lead, you need to act fast to optimize their chances of conversion. With PieSync, you can easily hand over this lead to the right person within your sales team so they can actively follow up and help convert them to a customer. 

In this sync, if a contact is in Autopilot with a certain lead status, it'll be synced two ways with HubSpot where the status is also updated:

![hubspot autopilot](//images.ctfassets.net/f2ysq090txql/2iuJoP1qyQfiNLSd9Ki1lR/f1925d0ac7fca1fa1c7a15f82d7ce66c/hubspot-autopilot.png)


<RelatedPost slug="keep-customer-data-up-to-date-everywhere"/> 

---

## Integrated data is essential for data-driven decisions

Collecting massive amounts of data is no longer the problem. Today’s challenge is managing data efficiency and avoiding data silos. 

Integrated systems and [synchronization solutions](https://piesync.com/) allow you to have the right information available in the right tool at the right time. Then, and only then, can you have a clear and complete view of your customers. This enables you to use data to illuminate the best path forward rather than making decisions based on gut feeling or past experience alone.

Additionally, data synchronization brings your different teams closer together and aligns their view of the customer. Having your tools “talking to each other” can also leverage something very valuable for all businesses: time.

Is it difficult to set up a sync? Not at all! Here's an example of how to sync contacts in Autopilot with your other apps:


<Embed src="https://www.youtube.com/watch?v=6S6GWI8OFXg&t" />

#### Ready to start connecting your apps? Empower your marketing and sales apps with the knowledge collected by your CRM and other business tools via PieSync. [Try it for free today.](https://app.piesync.com/signup/)

To make data-driven decisions, you first need effective data management. Here's how to get it right so you can grow and adapt with better data.

How to enable data-driven decisions by integrating your data

team-making-data-driven decisions-with-integrated-data

How to enable data-driven decisions by integrating your apps

![what are data silos and how to fix them](//images.ctfassets.net/f2ysq090txql/6BtpDspt9pFQU8NIp6wiyZ/eba878ee9ac59149a0ab50c824ed2a1f/taylor-vick-M5tzZtFCOfs-unsplash.jpg)

Many businesses suffer from data silos – often without even realizing it. Instead, you might notice the side effects, such as disconnected departments, confused employees and reporting taking _much, much longer_ than it should. 

But what is a data silo? Why are they bad? And how can you fix them and ensure they don't come back?

### What’s a data silo?

A data silo is a collection of data that one department has access to but others do not. This can lead to a lack of transparency, efficiency and trust within the organization and quickly cause business performance to dwindle. Data silos also drain your resources as you pay for extra data storage and the cost of inefficiency.

By integrating your organization's data and fixing silos, you can solve pressing issues holding your company back _and_ put your team in the best position to grow and thrive.

### What data silos look like

While data silos aren't always obvious, they can be behind some of your company's most stubborn problems. These can include lack of cooperation between departments, a slow pace of work and trouble with reporting.

Some of the most common signs of data silos include:

* Team members not knowing where to find the right information
* Having to check several places to find the right data
* Lost confidence in data accuracy
* Too much money spent on data storage and volume-based software
* Data not matching up across business tools
* Lack of transparency in how other departments are performing

### What causes data silos in businesses?

Although they can be caused by using the wrong tools or processes, data silos can also be a side effect of otherwise positive things, such as improving your business tools or experiencing business growth. No matter the cause, they need to be identified and fixed. Here's what might be causing data silos in your company:

#### Company culture

If your company's departments aren't used to collaborating on projects, reporting to each other and setting common goals, silos can easily arise.

#### Using the wrong technology

A company's first tools aren't always right for the long term. Using the wrong tools or being stuck with outdated paper systems and spreadsheets can leave your team unequipped to manage a growing amount of data.

<RelatedPost slug="10-of-the-best-sales-and-marketing-tech-stacks"/>

#### Using the right technology incorrectly

Having a top-of-the-range tech stack doesn't guarantee that your team will use the tools to their full potential or that data silos won’t ever come up. Using tools incorrectly or non-collaboratively is a quick way to create silos in businesses.

#### Scaling your company

As your company grows, data silos can become inevitable. The amount of data you have multiplies, you introduce new tools, and your team might also increase – which can all leave your data in a mess.

That said, even though siloed data can be part of the package for growing teams, it **doesn't mean you can't identify silos and fix them fast**.

---

### How to remove data silos (and avoid them in the future)

To break down data silos, you need to find the best way to organize your data, connect it between departments and prevent new problems coming up. Here are a few best practices for removing data silos and avoiding them in the future.

#### 1. Know the data everyone needs access to

To avoid and fix siloed data early on, make sure your company is clear on the data each department needs access to. This **includes data from outside their own department**.

Your sales reps might want to see how many qualified leads your marketing team is bringing in. Your marketers might want access to the feedback that clients are giving Account Managers.

Continually ask how you can give each role access to the data that will help them do their best work.

#### 2. Using a central CRM between departments

A customer relationship management (CRM) tool is at the heart of most successful businesses. It's where you store all contact data, track customers throughout their journey with your business and collect crucial insights to report on company performance.

When used well, your CRM is the go-to place for anyone in your company to find out information about any contact in your database.

<RelatedPost slug="the-best-crms-for-small-businesses-pros-cons-and-what-you-need-to-know" />

#### 3. Clean up your data – and collect better data

The results you get from contact management systems comes down to the quality of data in each tool. This includes contact details, communication histories, customer information and any other data you’ve collected about your database over time.

Create a company-wide plan to [clean up each department’s data](https://www.piesync.com/blog/top-4-clean-data-tips-for-your-database/) and make it easier for anyone to find what's important, accurate and relevant.

Next, identify where you're collecting new data so you can keep things cleaner in the future. This might include forms on your website (e.g. newsletter sign up forms, demo request forms), webinar signup forms, [lead generation tools](https://www.piesync.com/blog/10-best-lead-generation-tools/) and contacts from events or tradeshows.

For each place you're collecting data, make sure that:

* Form fields correctly match the properties they're connected to and are standardized. E.g. is ‘first name’ unintentionally being mixed with ‘full name’?
* Forms are user-friendly and people know what data they need to give you.
* You have settings in place to reject incorrect data, such as emails without the correct formatting.
* All data is synced to the right tools and the right people have access.


#### 4. Improve the connections within your tech stack

A connected tech stack is a healthy tech stack. You need to make sure your tools play nicely together, otherwise you'll have messy data to deal with. To connect your business tools, you can:

* Use native integrations offered between apps, usually listed on their integration pages.
* Use PieSync to [create two-way syncs between hundreds of apps](https://www.piesync.com/) and keep data flowing between your apps in real time. One popular use case is to have your [CRM contacts correctly synced](https://www.piesync.com/solutions/crm/) to your email marketing tool for segmented email lists, for example.


#### 5. Focus on collaboration

Fixing and avoiding data silos requires a **collaborative culture** between and within all departments. This starts at the top management level and trickles down to all functions. See if you can answer yes to these questions:

* Does your team have regular inter-departmental meetings?
* Do you have cross-departmental reporting dashboards in place? 
* Are all team members encouraged to work collaboratively rather than in silos?

To free your company from data silos over the long term, it starts with making sure you have a collaborative environment, organized operations and integrated tools. Then you’ll be in the best position to bring your departments together and reach higher levels of performance across the board.

To integrate your customer data between apps, get set up with a PieSync free trial and [start syncing your data two-ways between your key business apps](https://app.piesync.com/signup).

Data silos cause many of the problems that growing companies face – and can affect performance across the board. Here’s how to recognize, fix and avoid them.

Data silos: what they are, what causes them & how to fix them

what are data silos and how to fix them

![big-data](//images.ctfassets.net/f2ysq090txql/5ABOQVKXIWykgWWs2wMAA2/b390e9e4aa5ed2059059daaecce49046/big-data.png)

Pioneers are finding all kinds of creative ways to use big data to their advantage. Insights gathered from big data can lead to solutions to stop credit card fraud, anticipate and intervene in hardware failures, reroute traffic to avoid congestion, guide consumer spending through real-time interactions and applications, and much more. 

The benefits of big data are felt by businesses too. [61% of companies](https://www.capgemini.com/resource-file-access/resource/pdf/big_fast_data_the_rise_of_insight-driven_business-report.pdf) state that big data is driving revenue because it is able to deliver deep insights into customer behavior. For most businesses, this view of their existing data means gaining a 360-degree view of their customers.  

A report by [CapGemini](https://www.capgemini.com/resource-file-access/resource/pdf/big_fast_data_the_rise_of_insight-driven_business-report.pdf) agrees, stating: 

> “Digital customer experience is all about understanding the customer, and that means harnessing all sources – not just analyzing all contacts with the organization, but also linking to external sources such as social media and commercially available data. For the digital supply chain, it is about collecting and interpreting the data from connected devices.”

Many SMEs use CRMs, in collaboration with social networks and marketing platforms, to store and analyze customer data. 

So, for many organizations, the biggest problem is figuring out how to get value from this data. Only 27% of the executives surveyed in the CapGemini report described their big data initiatives as successful. 

This indicates that there is a huge gap between the theoretical knowledge of big data and actually putting this theory into practice. 

So what's the problem?

---

## Top 5 big data problems

&nbsp;

### 1. Finding the signal in the noise

It’s difficult to get insights out of a huge lump of data. Maksim Tsvetovat, big data scientist at [Intellectsoft](http://www.intellectsoft.net/) and author of the book _Social Network Analysis for Startups_, said that in order to use big data properly, "There has to be a discernible signal in the noise that you can detect, and sometimes there just isn’t one. 

"Once we’ve done our intelligence on the data, sometimes we have to come back and say we just didn’t measure this right or measured the wrong variables because there's nothing we can detect here." 

So one of the biggest issues faced by businesses when handling big data is a classic needle-in-a-haystack problem. Tsvetovat went on to say that, in its raw form, big data looks like a hairball, and scientific approach to the data is necessary. 

>"You approach it carefully and behave like a scientist, which means if you fail at your hypothesis, you come up with a few other hypotheses, and maybe one of them turns out to be correct."

&nbsp;

### 2. Data silos

Data silos are basically big data’s kryptonite. What they do is store all of that wonderful data you’ve captured in separate, disparate units, that have nothing to do with one another and therefore no insights can be gathered from this data because it simply isn't integrated. 

Data silos are the reason you have to crunch numbers to produce a monthly sales report. They’re the reason that C-level decisions are made at a snail's pace. They’re the reason your sales and marketing teams simply don’t get along. They’re the reason that your customers are looking elsewhere to take their business because they don’t feel their needs are being met, and a smaller, more nimble company is offering something better.  

And the best way to eliminate data silos? It's simple: [integrate your data](https://www.piesync.com/solutions/contacts-sync/).

&nbsp;

### 3. Inaccurate data

Not only are data silos ineffective on an operational level, they are also fertile breeding ground for the biggest data problem: inaccurate data. 

According to [a report from Experian Data Quality](https://www.edq.com/globalassets/whitepapers/the-impact-of-bad-contact-data-quality.pdf?utm_medium=email&utm_campaign=The+Impact+of+Bad+Contact+Data+Quality&utm_source=eloqua&sf_campaign_id=701i00000010mJl&elqTrackId=afb94c578fdc48c399823cd6d88d630c&elqaid=1440&elqat=2), 75% of businesses believe their customer contact information is incorrect. If you’ve got a database full of inaccurate customer data, you might as well have no data at all. The best way to combat inaccurate data? Eliminating data silos by integrating your data.

&nbsp;

### 4. Technology moves too fast

Larger corporations are more likely to fall prey to data silos, for such reasons as they prefer to keep their databases on-premises, and because decision making about new technologies is often slow.

One example cited in the CapGemini report is that stalwarts like telcos and utilities “...are noticing high levels of disruption from new competitors moving in from other sectors. This issue was mentioned by over 35% of respondents in each of these industries, compared with an overall average of under 25%.” 

In essence, traditional players are slower to adopt technological advances and are finding themselves faced with serious competition from smaller companies because of this.

Big data is also fast data. Paul Maritz, pivotal chief executive officer of the EMC Federation, wrote that, 

>“If you can obtain all the relevant data, analyze it quickly, surface actionable insights, and drive them back into operational systems, then you can affect events as they’re still unfolding. The ability to catch people or things ‘in the act’, and affect the outcome, can be extraordinarily important.” 

The ability to make fast decisions and quickly act on insights gained on big data is an advantage SMEs have over large corporations.

&nbsp;

### 5. Lack of skilled workers

CapGemini's report found that 37% of companies have trouble finding skilled data analysts to make use of their data. Their best bet is to form one common data analysis team for the company, either through re-skilling your current workers or recruiting new workers specialized in big data. 

You need to find employees that not only understand data from a scientific perspective, but who also understand the business and its customers, and how their data findings apply directly to them.

<RelatedPost slug="big-data-for-small-businesses" />

---

## Data integration is key

Data integration is absolutely essential for getting the full advantage out of your big data. Data integration addresses the need for eliminating data silos so you can obtain deeper insight from big data. 

In the book _Big Data Beyond the Hype_, the authors found that “...we see too many people treat this topic as an afterthought — and that leads to security exposure, wasted resources, untrusted data and more. *We actually think that you should scope your big data architecture with integration and governance in mind from the very start*.” 

Not only will this save the janitorial work that is inevitable when working with data silos and big data, it also helps to establish veracity. In other words, it will increase the trustworthiness of your data, which will underpin the authority of any insight you gain from analysing your data. 

[![Problems with Big Data PieSync](https://blogassets.piesync.com/wp-content/uploads/2016/06/IBM-quote.png)](https://blogassets.piesync.com/wp-content/uploads/2016/06/IBM-quote.png)

The first step to integrating your data is to [clean up your data](https://www.piesync.com/blog/top-4-clean-data-tips-for-your-database/). Big data consultant Ted Clark, from the data consultancy company [Adventag](http://www.adventag.com/data), said:

>"80% of the work data scientists do is cleaning up the data before they can even look at it. They’re data custodians rather than analysts. Anything you've done more than three times, you should automate - it might take longer the first time but the other times you will save time and focus on an analysis."  

---

## How to clean and maintain your data

&nbsp;

### 1. Remove duplicates

If you’re using multiple channels to capture data, such as through your website, customer care centre and marketing leads, you’re running the risk of collecting duplicate information. There are tools to help you remove duplicate data - for instance, if you work with Google Contacts, you can merge your contacts.

&nbsp;

### 2. Verify new data

Set company-wide standards on verifying all new captured data before it enters the central database. Put in checks to see if the customer isn’t already in the system, or that they’re not in the system under a different name or under their email address.

&nbsp;

### 3. Update data

Keep your data updated. You can do this by using parsing tools, which scans all incoming emails and updates contact information as it comes to hand.

&nbsp;

### 4. Implement consistent data entry

Ensure that all employees are aware of company-wide data entry standards. For instance, each customer record has to have first and last names.

---

A foolproof way of keeping your contact database up-to-date and consistent between apps is to make sure your data is synced and integrated. With PieSync you can sync all your contacts two-ways and in real time to take the hassle out of contact management. [Get started with a free trial now](https://app.piesync.com/signup/).

&nbsp;

[![cta2](//images.ctfassets.net/f2ysq090txql/23IT0hAlE6XN7Y6dnc2v5k/bb6a3ec14c84698d88460d7945516935/CTA_Library__1_.png)](https://app.piesync.com/signup/?utm_source=piesync&utm_medium=blog&utm_campaign=cta2)

Big data analysis is full of possibilities, but also full of potential pitfalls. Read on to figure out how you can make the most out of the data your business is gathering - and how to solve any problems you might have come across in the world of big data.

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Mixpanel

Our connector for Mixpanel has been equipped with the ability to connect to the eu.mixpanel.com - if you happen to have your data stored specifically within the EU territory. 

mixpanel regio

EU based Mixpanel accounts

[HubSpot CRM](http://hubspot.com/piesync) is an all-round customer relationship management tool that offers an incredible range of features for all businesses, from small startups to large enterprises. This complete CRM platform helps companies increase leads, accelerate sales, streamline customer service, and much more.

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HubSpot

[Available since today](https://www.hubspot.com/marketing-contacts), the HubSpot Marketing Hub features __marketing contacts__ - contacts that are able to receive marketing emails and be targeted with ads. In contrast, __non-marketing contacts___ cannot be marketed to... but also do not count against your contact tier. 

This means that you can now, with much greater comfort, store __all of your contacts data__ inside of HubSpot Marketing Hub. 

The PieSync filters & mappings now also reflect this new feature in HubSpot.


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HubSpot Marketing Contacts available in filters and mappings

Constant Contact is a marketing platform, giving your team the tools to create highly effective email marketing, social media campaigns, online surveys, and event marketing. Availability of hundreds of templates and extensive resources will make your lists grow!
Don't have Constant Contact, start your [free trial](http://www.constantcontact.com/signup.jsp?pn=piesync) now.


constantcontact

Constant Contact

We've applied a considerable update to our [Constant Contact sync](https://www.piesync.com/constantcontact). 

As Constant Contact are in the process of refreshing their user interface -  rolling this out throughout the next months - we already wanted to make sure the elements in our sync correspond to the new field and naming conventions. 

It's more than a happy accident that this unlocked a whole series of new sync functionality for you! Custom fields and more!

constancontact updated field mappings

Custom fields for Constant Contact and more

Contacts+ is the most powerful fully-connected contact management platform for professionals and enterprises who need to master their contacts and be awesome with people. Contacts+ cross-platform suite of Apps and APIs enhance contacts with 360-degree insights, while keeping them organized, in-sync, up-to-date, and safe.


Phone & E-mail

Sync Phone & Email apps you use everyday to automate your business and be more productive. {{ connectorCount }}+ Phone & Email contact sync integrations currently available. Click on your favorite app to get started.

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Contacts+

Nimble shows you detailed customer profiles in just a single view so you can get to know your customers in person. Sales and marketing features, activity management tools and a responsive social listening system will make sure you have all the insight you need!


nimble

For many of its [CRM connectors](https://www.piesync.com/connections/crm/), PieSync applies ownership automatically, [or at least gives you control through the rules as to how it should be transferred in the sync](https://www.piesync.com/help/faq/can-i-sync-contact-owner-source-fields/). 

Two popular supported contact management tools, namely Nimble and Contacts+, featured a concept of ownership since quite some time, but only recently have we updated our sync connectors for you to control this too.

Use the sync rules to control ownership. Set up multiple rules if you need multiple owners synced with one another. [More info](https://www.piesync.com/help/faq/can-i-sync-contact-owner-source-fields/).


ownership in nimble and contactsplus

Sync ownership

[Google Contacts](https://contacts.google.com/) is a free, easy-to-use contact management tool that allows you to organize your contacts in a simple interface with fields and segmentation. It has native integrations to other Google products such as Google Calendar, Google Drive and Gmail.

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Google Contacts

If you are using the 'Star' feature in Google Contacts I bring good tidings to you.

You can now include rules in your Google Contacts sync to take into account the fact that someone is starred or not!

The PieSync Blog