Companies that leverage customer behavioral data perform better than companies that don’t.

The difference is more dramatic than you might think. According to Gallup, companies that apply the learnings from behavioral data analysis enjoy 85% better sales growth.

But what is customer behavioral data, and how can you actually collect and leverage it to help your business?

What is Behavioral Data?

Customer behavioral data is any data that provides insight into how customers interact with a brand and its products at every stage of the customer journey.

While in the past, data about consumer behavior had to be carefully collected through physical observation. Most customer journeys now occur mostly or entirely online. This opens up a wealth of digital behavioral data that companies can collect and analyze.

This data spans the entire marketing funnel, customer journey, and lifetime. Behavioral data can be used to measure things such as how users respond to different advertising messages or which user segments are most likely to make repeat purchases.

The specific data points available will vary from company to company, but every company with an online presence can collect data about aspects of their customer experience and use it to analyze customer behavior trends.

Why is Customer Behavioral Data So Important Today?

Advances in behavioral science have led to a better understanding of how customer behavior can be interpreted.

At the same time, advances in behavioral data science and machine learning have led to powerful predictive analytics tools becoming available and affordable for everyone.

Big data is no longer just a trend or a buzzword. Building a data-driven culture is critical since being able to work with data and pull real insight from marketing and product analytics is now table stakes for success in most industries.

Consider user segmentation. If a company collects zero behavioral data, behavioral segmentation is impossible. The more data is collected and analyzed, the more granular user segmentation can become.

Being able to understand user segments in detail is of critical importance to marketers, product designers, managers, and almost everyone else because there are so many touchpoints along a user’s journey where understanding who that user is can be helpful.

For example, good user segmentation helps drive recommendation engines that use predictive modeling to recommend products based on what similar users have liked. This has the power to help convert potential customers, and turn one-time customers into repeat ones.

Getting this kind of targeted customer experience right relies on effectively collecting and analyzing online behavioral data.

How Can You Use Customer Behavior Data to Deliver Personalized Customer Experiences?

Personalization is one of the most powerful ways you can put your customer data to use. Knowing who your customers are, what they like, and how they respond to specific messaging can help you convert more potential customers and unlock a greater customer lifetime value.

You can see this kind of personalized experience in action on eCommerce sites that recommend related products based on what you’re looking at, and on streaming sites that recommend TV shows based on what other viewers with habits like yours have liked.

You probably also see it frequently in your email inbox. Although you may not be aware of it, many companies track when users typically open their emails and the time that email sends at the moments when data analytics shows that a specific user is most likely to engage.

Precisely how you accomplish this will depend on your business, the data you collect, and the behavioral insights your analysis uncovers. But any effective personalization strategy has to start with collecting quantitative data.

Ways in Which You Can Use Behavioral Data to Make an Impact on Your Business

The first step is to take stock of what data you’re collecting, and what other data might be useful for you to connect for your analysis. Ideally, you want to be collecting data from all of the major touchpoints along the customer journey.

In the marketing funnel, this will include social media engagement data, advertisement click rates, user data, traffic, and engagement data from your site. Who’s following your accounts? Which users that click your ads are converting?

Further down the funnel, this would include transactional data: who is purchasing, what are they purchasing, when are they purchasing it, what drove them to purchase, etc.

Once a potential user is on your site, A/B tests are a valuable tool for gathering behavioral data sense they allow you to see precisely how customer behavior changes as a result of the changes you make. Small changes on your end can lead to big changes in human behavior.

Once users have converted, you should be collecting as much data as possible about how customers use the product. For example, this could be app usage data or data collected from surveys about how customers are using offline products.

This data informs how product analytics work, but don’t use it_ only_ for optimizing your product. How customers engage with the product is part of their overall pattern of behavior. Your product analytics manager should always be involved in your broader behavioral data science work.

Finally, don’t forget to collect data about how, when, and why customers stop using your product. Ideally, the work you’ve done at earlier stages, such as segmenting users into granular persona groups, can help inform this.

For example, you may find that while two types of users frequently buy a product, only one of those two types regularly becomes a repeat user. You could use this information to build or tweak your recommendation engine to offer different recommendations to the two groups.

Of course, that’s just the tip of the iceberg. Let’s take a look at three major ways collecting and analyzing this kind of data can impact your business which will help you grow in terms of both customers and revenue.

Understand the Customer Journey and Improve Acquisition

Customer behavior data is critical to effective marketing strategy. The internet has made data tracking easier, but it has also made the customer journey more complicated. A potential customer might interact with your brand across a dozen different platforms before buying.

Behavioral science and behavioral data analytics can benefit your customer acquisition strategy in many ways.

For example, different platforms and different messaging are likely to work better for different customer segments. Once you have identified those segments by their online behavior through your analysis, you can engage in more precise marketing campaigns and targeted advertising.


This can increase incoming leads, lower acquisition costs, or both! It can also increase velocity to purchase — when you understand a customer’s behavior, it’s easier to get them excited to buy — and potentially even help you upsell additional goods or services.

Increase Customer Retention and Reduce Churn

Once you’ve converted a potential user into a paying customer, behavioral analytics can also help you figure out how to keep them happy. Improving customer satisfaction and retention is another huge benefit of good customer behavioral analysis.

Product analytics will necessarily play a large role at this stage. If you don’t yet have a comprehensive strategy or a product analytics team, don’t worry! You can learn a lot just from reading product analytics books.

The basic idea is that the more data you have about how, when, and why customers use your product, the easier it becomes to keep them using it.

Netflix offers a good example here. In the app itself, Netflix recommends things to watch based on your past behavior as well as the habits of users like you. But Netflix also reaches out with personalized messages at carefully chosen times to keep you engaged.

They might ask you to review a show you’ve recently finished, or remind you not to forget about a show you started watching. To keep you happy and subscribed, Netflix is constantly analyzing your data and personalizing its in-app experience and marketing accordingly.

Behavioral data can also help you reduce churn by identifying the behaviors that precede it so that you can attempt to re-engage with customers before they disappear.

For example, imagine you have a software product, and you’ve learned that a particular segment of users often churns after attempting to use one of its features.

Once you know that, you can reduce churn by preemptively emailing those users with instructions to help them use the feature.

Drive Customer Growth and Expansion

Customer behavior analysis can also drive your company’s broader growth by helping you better understand who your products appeal to.

If you have a real understanding of your customers and how they behave, you can reach new audiences effectively using what you know about the customers who’ve found you in the past.

If you don’t have that user behavior data, you’ll only be able to guess or hope that a big-budget, broad-strokes marketing campaign will reach at least some of the right people.

Ultimately, that’s what customer behavior analysis is all about: making your operations more efficient and effective by helping you target, captivate, and retain the right customers without wasting money on other audiences.

John Wanamarker famously said that half his marketing budget was wasted; the trouble was that he didn't know which half.

But a lot has changed in the century since. There is now a plethora of customer behavioral data available online, and powerful data tools available for tracking and analyzing it.

With customer behavioral analysis, it is now easier than ever to identify the elements of your strategy that are truly working, and correct the elements that aren't.