userpilot.com Open in urlscan Pro
2600:9000:206f:6200:1b:ae42:a40:93a1 Public Scan

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Submitted URL:
https://t.dripemail2.com/c/eyJhbGciOiJIUzI1NiJ9.eyJhdWQiOiJkZXRvdXIiLCJpc3MiOiJtb25vbGl0aCIsInN1YiI6ImRldG91cl9saW5rIiwia...
Effective URL:
https://userpilot.com/blog/behaviroal-product-management/?__s=e74snph6p1a8yv6gedos&utm_source=drip&utm_medium=email&ut...
Submission: On November 17 via api (November 17th 2022, 4:23:13 pm UTC) from US — Scanned from DE

Form analysis
6 forms found in the DOM

GET https://userpilot.com/blog/

<form id="form" action="https://userpilot.com/blog/" method="get" data-hs-cf-bound="true">
  <input id="popup-search" type="search" name="s" placeholder="Search">
  <button id="popup-search-button" type="submit" name="search">
    <svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:svgjs="http://svgjs.com/svgjs" version="1.1" width="512" height="512" x="0" y="0" viewBox="0 0 56.966 56.966" style="enable-background:new 0 0 512 512"
      xml:space="preserve">
      <g>
        <path xmlns="http://www.w3.org/2000/svg"
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    </svg>
  </button>
</form>

POST #

<form method="POST" action="#" id="poptinFormSubmit616a658c4a50a" data-hs-cf-bound="true" role="form">
  <div class="draggable resizable poptin-form-link-button poptin-form-link-button2 ui-selecting moved" id="poptinForm2ndlinkbtnText"
    style="line-height: 40px !important; left: 337px !important; top: 109px !important; color: rgb(58, 58, 60) !important; font-size: 20px !important; text-align: center !important; width: 291px !important; height: 39px !important; z-index: 10 !important; outline: 0px !important; cursor: pointer;"
    tabindex="152" data-z-index="10" data-editor-id="35" data-btnurl="https://userpilot.com/userpilot-demo" data-btntarget="_blank" data-bg-2color="rgb(233, 123, 152)" aria-label="Sign up for FREE!" role="link">
    <div class="froala-editor-link fr-box fr-inline" dir="auto"
      style="background: none 0% 0% / auto repeat scroll padding-box border-box rgb(233, 123, 152) !important; border-radius: 0px !important; font-size: 20px !important; line-height: 39px !important; box-shadow: none !important; height: 39px !important; cursor: pointer;"
      data-changed="1">
      <p style="cursor: pointer;"><span style="color: rgb(255, 255, 255) !important; cursor: pointer;">Sign up for FREE!</span></p>
    </div>
  </div>
  <div class="draggable resizable moved ui-selecting"
    style="text-align: center !important; font-size: 36px !important; line-height: 1.2 !important; left: 230px !important; top: 37px !important; width: 509px !important; height: 56px !important; z-index: 4 !important; cursor: auto !important; outline: 0px !important;"
    tabindex="151" data-z-index="4" data-editor-id="102" aria-label="Want to build product experiences

&nbsp;in minutes, code-free?">
    <div class="froala-editor-text fr-box fr-inline" data-hold-style="strong" dir="ltr" style="position: absolute !important; font-size: 24px !important; height: 68px !important; cursor: auto !important; color: rgb(255, 255, 255) !important;"
      data-font-size="22px">
      <p style=""><span style="font-size: 22px !important;">Want to build product experiences</span></p>
      <p style=""><span style="font-size: 22px !important;">&nbsp;in minutes, code-free?</span></p>
    </div>
  </div>
  <div class="draggable froala-image-wrapper ui-selecting moved" id="draggable" style="z-index: 4 !important; height: 139.875px !important; width: 284px !important; left: 0px !important; top: 33px !important;" data-width="374.781" data-height="185"
    tabindex="-1" data-editor-id="107" data-z-index="4"><img style="opacity: 1 !important; height: 139.875px !important; max-height: 185px !important; width: 284px !important; max-width: 284px !important;"
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"
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POST #

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 * How exactly does behavioral product management work?
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 * Types of behavioral analytics product managers should track
 * How can you collect behavioral data?
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Product Management


BEHAVIORAL PRODUCT MANAGEMENT: PRODUCT MANAGERS GUIDE

Adina Timar
November 14, 2022

9 min read




CONTENTS

 * TL;DR
 * What is behavioral product management (BPM)?
 * How exactly does behavioral product management work?
 * What are behavioral analytics?
 * What is a behavioral product manager?
 * Behavioral product manager vs traditional product manager
 * Types of behavioral analytics product managers should track
 * How can you collect behavioral data?
 * How to leverage behavioral product management when building products
 * Conclusion

Are you wondering what behavioral product management is? Or how behavioral
product managers are different from traditional product managers?

If so, you’re in the right place as these are some of the questions we’re
exploring in the article!

Are you ready to dive in?


TL;DR

 * Behavioral product management (BPM) leverages what we know about human
   psychology and product usage data to design products that deliver positive
   user value.
 * BPM focuses on developing products that satisfy user needs and desires and
   change user behavior. Anticipatory design is the example of the first, while
   the hook model of the latter.
 * By definition, behavioral product management is very consumer-centric.
 * BPM is a proactive and structured approach. Behavioral product managers
   select appropriate data tracking metrics and develop a detailed data analysis
   plan prior to product launch to assess its performance accurately.
 * Behavioral Product Managers are aware of the gap between what users say and
   what they do. As a result, they rely more on tracking user behavior data
   rather than qualitative user feedback.
 * They also use existing research and translate behavioral science insights for
   other team members.
 * Behavioral PMs are great data product managers. They develop strict
   procedures for collecting and analyzing data.
 * BPMs set very specific user behavior goals they want them to achieve. The key
   behaviors tend to be more general in traditional product management.
 * Behavioral PMs recognize and embrace the need to make decisions for users to
   improve their experience.
 * Monitoring and analyzing engagement along the user journey help assess
   product usability and ease of use. The insights can reveal friction points
   and ways to optimize the happy path and make the product more intuitive to
   use.
 * Product usage tracking and session recordings give you a detailed picture of
   how users engage with each part of the product.
 * Presenting different price plans together is a proven way to boost sales, and
   is one example of BPM application.
 * Simplifying product UI and removing unnecessary choices reduces cognitive
   overload and helps users succeed.
 * User segmentation and in-app guidance can further simplify the user
   experience by introducing the relevant features at the right time.
 * Automation, for example through templates or shortcut buttons, is another
   example of a BPM application to help users achieve their goals.
 * Want to know how Userpilot can help you track and analyze user behavior
   in-app? Book the demo!

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WHAT IS BEHAVIORAL PRODUCT MANAGEMENT (BPM)?

Behavioral product management (BPM) is all about applying the science of human
psychology to product design.

Successful behavioral product management manages to leverage behavioral
economics and behavioral science insights to build products that on one hand,
meet the needs of the users better and on the other, influence the user
behavior.

You are right to think that traditional product management does that as well.
However, BPM takes it to another level. It’s more systematic and detailed in its
application of the principles and processes.


HOW EXACTLY DOES BEHAVIORAL PRODUCT MANAGEMENT WORK?

People like to think of themselves as logical and rational creatures but we’re
often far from that. While we’d like to believe that all our decisions are based
on facts and evidence, we often rely on emotions and rules of thumb.

Despite our irrationality and tendency to fall for simplifications, we are very
predictable. BPM takes advantage of that.

Anticipatory design is a good example.

But it’s very effective in improving customer satisfaction not only because it
gives users what they need and when they need it. It also recognizes people’s
need to feel important and understood.

The hook model, on the other hand, is a great instance of a behavioral product
management application to change user behavior. It gives teams tools to create
addictive user experiences so that they keep coming back to use the product.

The Hook model.

Both examples put the customer in the center which is another characteristic of
behavioral product management.

To make it possible, BPM uses the right tools, like behavioral maps or
psychological performance indicators, to set goals and measure product
performance in a proactive and methodical way to make the product attractive.


WHAT ARE BEHAVIORAL ANALYTICS?

Instead of relying on user feedback, behavioral product management uses
predominantly actual user behavior data.

Why is that?

What people say and what they actually do very often differ a lot. That’s
because people may not be aware of what really drives their behavior.

What’s more, they may not be able to express what they really think.

For that reason, tracking and analyzing user behavior can give you more reliable
insights.

And modern analytics tools allow you to track such data very easily. For
example, in Userpilot, you can track not only user clicks but also form fills
and hovers, which reveals a lot about user interactions with your UI.

Userpilot allows you to track clicks, hovers and form fills.


WHAT IS A BEHAVIORAL PRODUCT MANAGER?

A behavioral product manager is a role that uses a combination of user behavior
data analysis, behavioral economics, and behavioral science to perform
traditional product management responsibilities.


BEHAVIORAL PRODUCT MANAGER VS TRADITIONAL PRODUCT MANAGER

Both traditional and behavioral product managements aspire to build products
that feel intuitive to use and satisfy user needs. However, they approach
product design and development differently.

Traditional PMs often use qualitative research methods like user interviews to
make roadmap decisions more than BPMs. The latter prefer to harness user
behavior data and the existing body of knowledge for decision-making. They are
more aware of the discrepancies between what users say and what they do.

Actual user behavior is what they use to create user persona, which in
traditional product management could be arbitrary and defined by demographics
rather than actual behavior.

To be able to make reliable decisions based on data, BPMs need to be great data
product managers. They develop rigorous protocols for collecting, logging, and
analyzing data and promote them across their organizations. Traditional product
managers may not always be as religious about it.

When it comes to goal-setting, behavioral PMs focus on changing user behavior
and set very specific key behaviors they want users to perform. Traditional
product managers are more likely to use general key behaviors and focus on
short-term goals that don’t always translate into lasting change.

Finally, behavioral product managers show the confidence to make product
decisions for their users in their best interests. Traditional product managers
may want to give users more scope to make their own decisions and more choices,
which can be overwhelming.


TYPES OF BEHAVIORAL ANALYTICS PRODUCT MANAGERS SHOULD TRACK

Out of all the possible metrics and analytics, which of them should behavioral
product managers pay particular attention to? Let’s check out some of them.


USER JOURNEY DATA ANALYSIS

Tracking and analyzing how users engage with the product at different
touchpoints in the user journey can help you verify what users say about UI
usability and intuitiveness in their feedback or interviews.

As mentioned, Userpilot allows you to easily track user engagement with
different UI elements, like the actions needed to reach the activation point.
You can next group specific key behaviors into one custom event for ease of
tracking.

Custom Events in Userpilot.

Once you have that in place, you can analyze trends. The trends overview in
Userpilot allows you to filter your events by user segments, time period, and
company.

Features and Events dashboard in Userpilot.


FRICTION POINTS AND THE HAPPY PATHS

Following users, as they make their way through the product allows you to find
friction points that either slow down the user or make them drop out altogether.

This often happens when the happy path doesn’t match human behavior.

Happy Path.

Consistent tracking of user behavior allows you to identify ways to optimize
your happy path to make it clearer and more intuitive to follow.


HOW CAN YOU COLLECT BEHAVIORAL DATA?

Product managers are spoilt for choice when it comes to tools and techniques
they can deploy to collect behavioral data.


TRACK PRODUCT USAGE DATA

In short, tracking product usage data tells you who engaged with which parts of
the product.

We’ve already mentioned Userpilot as a possible tool that allows you to track
user engagement with specific UI elements and group them into custom events.

Next, you filter the data by a range of detailed characteristics, like
individual user or event occurrence for ease of analysis.

Userpilot supports you with very detailed data filters.


PAIR USAGE DATA WITH SESSION RECORDINGS

Want to collect even more detailed data about user engagement?

Try session recording.

Tools like Hotjar enable one to record every single move that the user makes
within the product. It’s not only each action or clicks that they make but how
they get there as well.

Session recording in Hotjar.

When you combine it with heatmaps illustrating user engagement with each part of
your app or website, you can get a pretty detailed picture of your UI strengths
and weaknesses.


HOW TO LEVERAGE BEHAVIORAL PRODUCT MANAGEMENT WHEN BUILDING PRODUCTS

There are a few fairly easy ways product teams can use BPM to drive value for
users and for the business.


APPLY PRICING PSYCHOLOGY TO ACQUIRE USERS

How you structure and present your pricing has a huge effect on your sales.

For example, presenting different pricing plans side by side has proved to
increase sales.

Why does it work?

There are many factors at play here. For example, it leverages Gialdini’s
contrast principle. When a user sees one option is considerably cheaper than the
other, they feel like they’re getting a good bargain, even if it offers limited
functionality compared to other available products.

Userpilot pricing plans.

Limited-time offers, like those that are common around the festive period, are
another example. They create a sense of urgency so that they commit to the
purchase before the opportunity is gone.


SIMPLIFY THE UI

Do you remember the Fogg behavior model? One of its premises is that the more
difficult it is to use the product, the less likely your users are to do it.

What’s more, giving the user a lot of features or different choices is not
always the best choice to enhance customer experience. A cluttered interface and
complex functionality are often too much to handle for many users, especially in
the long run.

To reduce the risk of cognitive overload and product usage fatigue, and make the
product easier to use, remove what’s not important.

As most users only use about 20% of product functionality, gradually prompt
users to discover features that are relevant to their use cases and jobs to be
done.

You can easily do that using tooltips and other UI patterns.

UI patterns in Userpilot.


USE BEHAVIORAL DATA TO DRIVE ADOPTION

To take the best advantage of UI patterns and onboarding flows to drive positive
customer value and improve adoption, you need to make them relevant to specific
user groups.

For that, you need detailed user segmentation.

If you can group your users according to criteria such as individual feature
usage, content engagement, or survey responses (like in Userpilot), you can
target each of them with bespoke in-app messages and guidance to help them
activate and adopt features.

Detailed user segmentation in Userpilot.


AUTOMATE REPETITIVE TASKS

If you use a product on a regular basis, there’s nothing more frustrating and
tiring than going through the same process again and again.

And there’s no reason for your customer to be subjected to that.

User behavior analysis allows you to identify patterns in how users engage with
the product. As a result, you can automate usage and value extraction by cutting
out unnecessary steps.

What are some good examples of repetitive task automation?

Let’s start with the login process. Instead of making users log into your
business accounting system or project management tool manually every single time
they use it, why don’t you enable Single Sign-On (SSO)?

Or even better, give them the option to stay signed in all the time.

SSO in Miro.

The online purchase process is another place where you can make your users’
lives easier. By allowing them to store their address and payment details in the
account, you make it easy to complete the purchase.

You can go even a step further and include a ‘buy now’ button as Amazon does.

Buy now button in Amazon removes friction from the purchase process.

Templates are another good way to eliminate mundane and repetitive activities.

Why should users start from scratch every time they want to create an email, an
onboarding checklist, or a roadmap?

You can use your user data to single out the most frequent JTBDs and provide
them with a selection of themes and templates that will let them complete them
in less time.

Of course, don’t forget to give users the option to create their own templates.

Themes in Userpilot.


CONCLUSION

Behavioral product managers apply human psychology principles and product usage
data to create products that satisfy users’ practical and emotional needs
better.

If you would like to see how Userpilot can help you collect and analyze user
behavior data so that you can leverage it to improve the behavioral design of
your product, book the demo!

Sign up for FREE!

Want to build product experiences

 in minutes, code-free?



Thank you!




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