Level Up Your Product Marketing with Behavioral Analytics Personas

Refine your product marketing by using behavioral data to identify what your high-value customers have in common.

Best Practices
August 25, 2021
Image of Mallory Busch
Mallory Busch
Product Marketer, dbt Labs
Behavioral Personas in Product Marketing

Product marketing can often feel like throwing spaghetti at the wall to see what sticks. You try to refine the process to attract and retain customers. Often this starts with what you know about your customers, otherwise known as your marketing persona. These personas reflect your ideal customer and are developed from market research and data about your existing customers.

However, traditional personas don’t consider the behavior of customers within your product. Traditional marketing personas are often based on demographics, location, or job titles. While these characteristics may indicate an increased likelihood of “stickiness,” they don’t account for all of the nuances that lead people to become high-value customers.

By bolstering your marketing personas with behavioral marketing data, you can confirm that you are targeting the right audience. You can also potentially identify new personas to target and build a marketing strategy to draw them in.

1. Start With Your Current Target Personas

Before you dive into behavioral analytics, start by recognizing the marketing personas you already have.

If you don’t have these profiles created, analyze your customers by age, geography, revenue, or engagement to uncover patterns in your most dedicated customers. Surveys, interviews, and competitor research can also inform your marketing personas. You’ll likely have more than one persona, each representing segments of your buyers that have some attributes in common.

Integrate behavioral analytics with your current personas by using a product analytics solution like Amplitude. Group your customers by your existing persona characteristics. From there, dig into the customer journey of users that fit into a specific marketing persona. By analyzing their actions, you’ll be able to assess whether your personas are high-value customers or not.

2. Confirm the Value of Your Target Personas With Behavioral Analytics

Next, create a segment in your product analytics platform that matches one of your existing marketing personas. Track the behavior of the customers within that segment to see if they are taking high-value actions, like using a specific feature or making a purchase.

You can then break this persona down further into customers who take this high-value action and those that didn’t. Grouping your customers based on the actions they take is known as behavioral cohorting.

If the findings surprise you, continue to ask more questions. For example, you can send email campaigns to the behavioral cohorts that did not take high-value actions, encouraging them to return or providing a special offer. If these efforts prove effective, you know how to reach customers within your original target persona and drive them to the same behavior. If they don’t respond, then you should further segment the customers within this persona or explore different engagement tactics.

3. Use Product Analytics to Identify New Behavior-Based Personas

After reviewing the actions of your existing personas, your next step is to find other customers who take the same actions. These customers may not be on your radar right now, but the behavioral insights you pull may prove them to be incredibly valuable.

Within your product analytics platform, create new behavioral cohorts that group high-value customers together based on the actions they’re taking. These customers are now the basis for additional marketing personas, in categories such as “taken high-value actions,” “almost there,” or “hasn’t shown much interest.” Your marketing team can target these different behavior-based personas with positioning, messaging, campaigns, and more based on their interactions with your product.

Here are some different ways to use behavioral analytics for this type of segmentation:

Perform Customer Cohort Analysis

Customer cohort analysis is the process of tracking common behaviors among users that produce revenue for your business. It’s different from analyzing all users, which includes those who haven’t paid anything to your company.

By focusing on revenue-driving customers, you can understand who is getting value from your product and what actions they take in your product. As a marketer, this helps you create product marketing campaigns that nudge “almost there” users into the same behaviors that revenue-generating customers are taking.

For example, you may identify that customers who complete all steps of onboarding are more likely to convert to—and maintain—a paying subscription. Your marketing tactics may include personalizing the onboarding experience to capture the potential user’s interest.

Check Paths for High CLV Users

Identify common actions across the customers that have the highest customer lifetime value (CLV). These customers have reached your product’s “aha moment,” and their value increases over time, whether through maintaining long-term subscriptions or repeat purchases.

By identifying the actions that these high CLV customers have in common, you can create behavior-based personas. For example:

  • Identify the early actions taken by these customers leading up to their aha moment
  • Measure the level of engagement, such as how frequently they return to the product
  • Segment the customers by their repeat use of specific product features

Through your product marketing efforts, encourage prospective users to emulate these behaviors so they’re more likely to become high CLV customers.

Analyze User Behavior by Funnel Stage

If you take a step back from your customer cohorts and instead look at all users, behavioral analytics can tell you where in the funnel these customers are dropping off. When you do funnel analysis, you are looking at events that lead to conversion drivers.

Starting with all of your potential users, you can do a breakdown and identify how far they get within your funnel. Product analytics will tell you if these users completed actions such as filling out a form, clicking a button, or adding a product to a cart. From there, you can create cohorts based on these behaviors within different stages of the funnel. Then, you can look at these users and create new marketing personas based on common characteristics.

When you know how your personas behave within your funnel, you can use marketing to drive users toward converting from one stage to the next. Whether you are looking to attract new users or push existing users into different stages, knowing the behavior that leads to conversion can help you create a more effective product marketing strategy.

Product Marketing: A Collaboration Between Marketing Personas and Behavioral Analytics

As a product marketer, your competitive edge comes from knowing how your product brings value to your customers and communicating that value to potential new customers. By using a product analytics solution like Amplitude, you can continually find and answer questions about customer behavior and find the next questions to ask.

As your product evolves over time, your customers will take new actions and view the value of your product differently. Regularly review your customers’ behaviors to refine your marketing personas. Instead of “seeing what sticks,” you’ll be set to make informed product marketing decisions based on behavioral data.

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About the Author
Image of Mallory Busch
Mallory Busch
Product Marketer, dbt Labs
Mallory Busch formerly ran the Amplitude blog, frequently named a best blog for product managers. She also created AmpliTour, the live workshop for beginners to product analytics and 6 Clicks, the Amplitude video series. She produced the Flywheels Playbook, wrote The Product Report 2021 and produced The Product Report 2022. A former developer and journalist, Mallory's written work and coding projects have been published by TIME, Chicago Tribune, and The Texas Tribune. She graduated from Northwestern University.