Product Analytics for Growth Marketing

Are you a Marketeer and you love nailing the targeting of your messages?

Traditionally, Product Managers use product analytics to analyze feature adoption and decide the product's roadmap. However, also Marketeers can significantly improve their effectiveness using the insight by

  • identifying key features which drive conversion and stickiness

  • pinpointing places in the customer journey where to upsell premium capabilities

  • singling out customer segments and their behavior patterns


Killer features rarely exist. As a Marketeer, how often have you asked your fellow Product Manager what are the key (killer) features of the product you are trying to promote? You need to know what features to highlight on the product web page, which features to cover in that promotion video, and which topics to cover in the upcoming blog series. Furthermore, to convert prospective to paying customers during a product evaluation, you need to know which features create perceived value in the first hours. 

Product analytics allows you to determine which product functionality is used daily providing actual value. That should be something you describe on the product web pages. This can be done predominantly with most-used-features charts.

There is one killer feature of product analytics for marketeers! Wouldn’t it be great to report to your manager that a recent activation activity has not only led to how-much views on a YouTube view or a blog post but to an actual change of customer behavior on the product? 
Product analytics solutions can show the real impact of your marketing activities by showing whether the number of interactions with a feature increases after your activation actions. 

Qt Insight Dashboard Most used

Image: Screen capture of UI path analysis in Qt Insight

Product analytics during product trials can establish which features people are trying out. You might want to present these features in a product promotion video as a faster way than hands-on-evaluations to demonstrate that the product delivers the perceived value. The features people try out during the evaluation often influence the decision to buy or not. Hence, they deserve special attention from UX Designers, Product Managers, and Marketing Managers.


Many digital solutions do have a freemium option today. Converting customers from the freemium version to a for-pay option makes or breaks entire businesses. But conversion messages to promote premium features need to be placed carefully in the proper context and in a suitable place in the customer journey. Otherwise, conversion messages are perceived as unnecessary noise and disturb the usage flow. UI path illustrations can pinpoint potential places when customers might be receptive to conversion messages. In-product messaging might be placed well whenever customers use a feature related to a premium feature, especially when customers circle back to the same related feature, potentially looking for additional capabilities.

Qt Insight User Flows Smartphone

Image: Screen capture of UI path analysis in Qt Insight


Your customers might be different from the ones you thought. As a Marketing Manager, you should have defined your buyer personas for your Go-To-Market strategy. But based on what information have you drafted these personas? How many of your future customers have you really met in person? Product Analytics can help you with user profiling. Product Analytics solutions typically work with anonymous data for privacy reasons and give you no direct indication of things like age, gender, spending power, etc. However, product analytics solutions can provide data that can be correlated to meaningful groups. 

The following Product Analytics data can help to make conclusions on the customer profile: 

  1. Geography/country information: Is the user in a country with a high or low Gross Domestic Product (GDP? This can give you information on the potential spending power of such users.
  2. Device type/screen resolution: The device type can indicate age, gender, and spending power. A MacBook user is likelier to have decent spending power for your desktop application. An end user with an embedded device running a larger screen is likelier to spend additional money on a subscription-enabled premium feature. 
  3. Utilization rates can also serve as a base for user profiling: Based on the total number of sessions, session length, and the number of interactions, you can extrapolate who are power users. 

More focus on customer experience necessitates the use of analytics. Freemium business models can only be optimized with analytics. Consumer segmentation can be augmented with analytics. The success of your customer activation activities can only be proven with product analytics. When are you getting ready for more insight?

If you want to know more about product analytics, especially Qt Insight, Qt's product analytics solution for embedded devices and desktop applications, don't hesitate to find out more on our product web pages here.

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