Guide to Behavioral Analytics

This guide on Behavioral Analytics dives into the topic, what it is, how it works and more. At the end you will have a foundational understanding of the topic.

This post contains:

• What is behavioral analytics?
• How does behavioral analytics work? 
• Web analytics role in behavioral analytics
• What departments is behavioral analytics used in? 
• How effective are behavioral analytics? 
• Different types of behavioral analytics
• Behavioral analytics in the marketing mix
• Privacy concerns of behavioral analytics
• What about third party vs first party cookies
• Behavioral analytics role in bot & fraud detection
• Usage in product analytics
• Usage in eCommerce
• How can behavioral analytics increase conversion rates. 
• What does a good process for behavioral analytics look like?
• The future
• How Nudge can help

What is behavioral analytics?

Behavioral analytics is the process of collecting data on how people are behaving within a given digital experience. Behavioral analytics is at type of digital analytics. Typically this is measuring customers in a customer journey, but can also be users within a web application. 

Think about behavioral analytics as adding an extra dimension to the level of knowledge about your customers. It’s a high fidelity view.

Behavioral analytics is synonymous with big data, because of the sheer volume of data it can create. Each individual customer is now providing a lot of data points, which require new tools for analysis. To deal with this, behavioral analytics platforms like Nudge, create insights from behavioral data, to help analysts shift from insight to action faster.

How does behavioral analytics work? 

Each behavioral analytics tool may function slightly differently. Typically it involves installing tracking code or javascript on the experience that customers engage in. This tracking code, then measures each customer by firing events as they take certain actions. The analytics system then processes that data and shares it in an online dashboard. 

Metrics can include things like device, location, pages they visited in their journey, attention, scroll, buttons clicked, actions taken, traffic sources. 

These can be presented in aggregate, or tied into a CRM or CDP which shows each customer journey on an individual level. Both are useful for different purposes. 

What are the common Behavioral Analytics Metrics?

The most common metrics marketers are using for behavioral analytics:

• People, how many real people are consuming your content.
• Attention, seeing how much attention people pay to your content.
• Bounce, whether people are engaging with your content or not.
• Avg Scroll, the average scroll on each piece of content. And drop off, what parts of the experience are causing people to drop off.
• Social engagement, seeing how many shares your content creates.
• Conversion rate, the rate at which people take action after consuming your content.
• Time of day, seeing what time of day is best for your audience to engage.
• Day of week, fine tuning and seeing what days of the week there are pockets of demand.

Read more:

• Guide to Website Analytics

Web analytics role in behavioral analytics

Digital transformation has meant that web analytics play an expanding role in behavioral analytics. As more and more of the customer journey is now a digital experience or process. Web analytics provide a feedback loop on how customers are engaging in those digital experiences. And metrics around what they are doing, the contexts in which they engage and how successful they are. 

This expanded use case has stretched the capabilities of older analytics systems and created opportunities for newer platforms. That better capture customers behaviors with their metrics. And provide insight by sorting through the data for their customers.

What departments are behavioral analytics used in? 

Behavioral analytics is used all throughout data-led organizations. It spans from marketing, to product, sales, customer support and finance. They can even be used for fraud or bot detection when it comes to cyber security. 

In marketing

Behavioral analytics provides insight into the customer journey. This transparency helps uncover how effective marketing initiatives are, which then enables marketers to make better decisions with their marketing resources. 

In sales

Profiling where and how customers are getting stuck in the purchase journey. Or using behavioral analytics to profile cohorts of users that need extra attention, or are about to convert. Are just some examples of how behavioral analytics are used in sales. 

In Finance

Behavioral analytics can play a role in Finance, by helping weed out bot traffic, and providing return on investment measurements. Which further aid the allocation or budgets and justifying expansion of existing budgets. 

In Cyber Security

Behavioral analytics help to detect unusual patterns in web experiences, which could be caused by fraud, bots, bad actors or a combination of all three. Things like CAPTCHAs can help in this regard as well. A key challenge is detecting, are these real people. 

In Customer Support

Behavioral analytics when linked with customer data, can help yield what is causing a particular issue with a customer. Helping lead to faster and more efficient problem resolution.

How effective are behavioral analytics? 

Behavioral analytics provide a high fidelity view of customers and their behaviors. The accuracy is very high and representative of most users. Nearly ever use can be captured. Near 100% data collection can be obtained in many use cases. 

Limitations of behavioral analytics can be, that users need to engage in a digital experience. Processes outside of that may fall to the wayside. 

Other limitations include:

• Customers may employ blockers to stop tracking
• Privacy concerns may limit data collection
• Accessibility demands may not be reflected
• Edge case use cases

Different types of behavioral analytics

There are different types of behavioral analytics:

• Web analytics that provide a view of how the customer is engaging.
• CRM or CDP which provides a view of each individual customer and their journey.
• Feedback analytics, which provides insight from users feedback, either through interactive forms or data collection from other sources, such as surveys or reviews.

Behavioral analytics in the marketing mix

Marketing has often been the department leading organizations into digital experiences. As such, they are usually a high user of behavioral analytics.

Behavioral analytics enables marketers to:

• Better understand their customers & preferences
• Identify areas of improvement in the marketing mix
• See how marketing strategies are performing
• As KPIs for their teams
• To justify existing or to create new budgets
• Prioritize investment in improvements in the digital experience
• Articulate and show ROI of their efforts
• To identify how marketing drives customers through to sales

Analytics plays a very important role, and behavioral analytics provides an extra view of exactly what customers are doing. 

It can be used for:

• A/B tests
• Funnel measurement & optimization
• Content marketing
• Usability analysis
• Traffic & PPC optimization 
• User segmentation

Example of a behavioral analytics dashboard

Privacy concerns of behavioral analytics

Privacy can be a concern when it comes to behavioral analytics. Customers may not want to be tracked to the degree that companies would like to. As such, compromises need to be made and expectations need to be set with customers. 

Apple has found, that giving users choice and respecting their privacy is the happy medium. Which is what Apple Tracking Transparency (ATT) is all about. Many firms adopt opt-in practices for their data collection, to provide that choice to their users. 

Regulators have also provided different guidelines, depending where in the world customers are visiting from. Such as GDPR and CCPA. Companies need to be attentive to these guidelines. 

What about third party vs first party cookies

First party cookies have been rapidly adopted by the industry, to ensure that cookies cannot be used to track users around the web. This has lead to changes in analytics infrastructure for companies adopting behavioral analytics. 

Third party cookies can lead to data loss, an incomplete view of the customer, with end users blocking the cookies. Or the browser they use blocking it for them. 

Behavioral analytics role in bot & fraud detection

Bot & fraud detection is an expanding scope for companies, with more of their infrastructure now accessible online. 

Behavioral analytics helps to profile bad actors, as their behavior tends to be out of the norm. They can pick up behaviors like: 

• When someone is accessing a lot of webpages
• Not truly engaging in pages
• High velocity of engagement in webpages
• Accessing pages in a non friendly manner. 

Cohort analysis is the easiest way to find these, as customers tend to exhibit behaviors in a consistent manner. 

Usage in product analytics

Behavioral analytics helps uncover how users are using your product. With many companies expanding their digital experiences, these are new processes, which are still being tested and improved. So behavioral analytics can help identify points where users are dropping off, where they’re engaging a lot and in turn opportunities for improvement. 

For example, behavioral analytics may identify where or what is causing users to drop off at a certain page. Then teams can go and fix that part of the process. 

Usage in eCommerce

Behavioral analytics and eCommerce go hand in hand. Simply because eCommerce is all digital and the teams behind them are data savvy. Behavioral analytics provides a richer view of the customer and what leads them to make a purchase. 

Without behavioral analytics, eCommerce teams would have a simplistic view of the customer. And may and go improve the wrong thing.

For example, behavioral analytics, can uncover how product descriptions are contributing to conversions, or what parts of the page are most engaging. Actions which may have been hidden by traditional analytics. 

How can behavioral analytics increase conversion rates?

Conversion rates, capture the rate at which customers are completing desired actions. Behavioral analytics combined with conversion data enables firms to:

• Build a blueprint of converting users
• Contrast this blueprint with users that don’t convert, to find opportunities to improve
• Get a richer view of the customer

Then they can reduce activity on low converting behaviors and focus on the higher converting behaviors. 

What does a good process for behavioral analytics look like?

Creating a measurement plan is a fairly common process. For behavioral analytics, you want to establish an effective process to get the most out of your data:

1. Identify what is it you are trying to achieve
2. Select the metrics which help reflect that objective.
3. Install analytics, and QA it.
4. Collect data and create a report.
5. Distribute the findings & insights.
6. Take action.
7. Rinse/repeat.

Some pro tips are to also:

• Create an ideal customer blueprint, in theory and then from the data
• Establish benchmarks for behaviors.
• Embrace cohort analysis, for greater insight
• Keep the customer at heart
• Ensure stakeholders understand the analytics and what they mean

The future 

The future of behavioral analytics includes things like: 

• AI, greater use of AI to identify trends in the data and make predictions. AI components will also be used as part of the experience, to make it more seamless. 
• Enhanced personalization from behavioral analytics data. 
• Less data collected, as firms become more refined in their approach, less data will need to be collected. 
• Better customer journeys & syncing with CRM, especially for B2B and high value purchases, behavioral analytics will become more intertwined in these processes. 

Behavioral analytics will remain the customers advocate, providing that all important feedback loop to brands. Customers speak with their feet and behavioral analytics their voice.

How Nudge can help with Behavioral Analytics

Nudge is an analytics platform that seeks to capture customer engagement with your digital experience. It collects metrics on behaviors like engagement, scroll, drop off, engagement rate, conversion rate, attention, bounce rate. Collectively they provide a high fidelity view of the customers behaviors.

This data can then be viewed and analyzed in its online dashboard. Where extra analysis can be obtained, exploring geography, traffic sources, devices, customer journeys, top pages.

Further the platform creates insights from all of the data it collects. To help companies go from insight to action faster. The platform is easy to use, even for juniors on the team, and makes reporting a breeze. What good is data, if you don’t act on it? Nudge helps make it easy, so it is actionable.

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