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Until not very long ago, many organizations defined business strategies based on isolated figures used by isolated teams. Unfortunately for them, that approach just won’t cut it anymore. Instead, we are fastly moving to a world where data will be the critical asset for businesses, and handling it accurately will be essential to survival. Thus, product analytics has become the must-have tool to put that data into context, helping teams determine what indicators are the most valuable when measuring the impact of a product. But that is easier said than done.
In reality, most organizations struggle to make the right moves when choosing what and how to measure product impact on end-users. At the same time, key decision-makers often can’t seem to find a way to make analytics truly collaborative across teams.
The result: a patchwork of metrics and reports that, even when they provide the groundwork for product enhancements and marketing strategies, lack the context that ties them to the individual users. Add data privacy regulations into the mix and you have a recipe for disaster: no context, no oversight, and potentially, no compliance to the regulatory framework.
The solution, however, is quite simple: distribute data into individual user profiles, while retaining control of your data. This will not only put individual behavior in the context of a single user but will also provide insights for all the groups that the user belongs to, letting you turn this data into more accurate metrics that make sense for your teams — and your business.
Basically, creating individual profiles makes you stop treating data as isolated datasets and instead gives them a name and a face that you can track. By doing so, not only will you get a fast and insightful overview of the entire customer journey, but you will also humanize data.
And how do you go about this, you ask? Two words: User Profiles. Let’s delve deeper into those two concepts.
Understanding user behavior and segmenting your user base by demographic properties enables you to build the queries that will guide your strategies.
However, it is quintessential that you retain a level of understanding and of control over the processing of the database because user identification is one of the reasons-to-be of data privacy regulations, like GDPR.
Here’s where user identification goes a long way. Imagine you can link that micro-segmented data with the level of activity in your application (e.g., number of sessions), the overall interest of your users (e.g., views on certain pages), behaviors (e.g., clicks or events performed), and VoC tools, and combine them all into an individualized profile. Wouldn’t that give you a snapshot of the user’s entire experience with your app?
Additionally, creating such hubs for user intelligence enables the synergy between teams and, depending on the product analytics solution, allows the potential integration with CRM, Customer Support, or messaging platforms.
Using user profiles allows you to have an overview of the user journey and find out which factors may have affected the user experience. From this, you can infer hypotheses that you can test in micro-segmented groups from a few users and reach conclusions. These will then guide the actions or the decisions each team must take for any new feature, development, or targeting strategies.
That said, these actions or decisions will look completely different depending on who needs them and for what purpose. So it will come down to determining the product analytics strategy that will provide the most accurate insights with the least amount of effort for each situation that may affect the customer journey.
The easiest way to build this strategy is to combine micro-segmented user data with more analytics features, which provides you with the ability to experiment with data, measure it, and track what you need.
And, in case you don’t know where to start, keep in mind the scenarios below:
Combine User Profiles with a cohort and a hook:
Whenever users do something in your app, you can program their behavior to lead them somewhere. For example, a particular user enters a cohort by creating a new cart and completing a purchase (or not, maybe they decided to never finish the checkout). You design the hook to send them an email summarizing their purchase, to send them a survey, or you can redirect them to an NPS® landing page.
Combine User Profiles with a funnel and a push notification:
Define the steps that users need to complete (or not) and then be targeted by a personalized push message. For example, if your user downloaded your app, started using it, but left a process halfway through, reach out to them to remind them to finish it or even offer them a discount if they do.
Combine User Profiles with a cohort and a data formula:
Since a cohort is based on user behavior, you can use any metric related to these actions to create new customizable metrics that are relevant to your operations. For example, you can know how many users have a much higher level of engagement, know the percentage they represent over the entire user base, and track the evolution of this metric.
Combine User Profiles with a cohort and a data segmentation feature with reporting functionalities:
Slice and dice the user profiles belonging to certain cohorts by filtering them and incorporate the insights into the reports measuring the business metrics. For example, group users that have premium accounts and filter them by those who have performed a certain event this week. Then, use that data to create a report and track the performance of that event week by week.
Combine User Profiles with a cohort and remote configuration feature:
Use groups of users as testers of potential changes to the appearance or behavior of your app. For example, set up an experiment with certain audience groups and see which app behavior/appearance change determines a basic plan user to become interested and move to a premium plan.
The role of analytics is not to compile data from all of the aspects that make a user journey unique (unless your resources are endless) but to turn them into actionable insights that will, in the end, give the user what they need and want, and ultimately keep them coming back for more.
When you’re in full control of your data and have an analytics tool with powerful micro-segmentation capabilities, you can create more accurate queries that can be as extensive as your desire for innovation.
The examples above are only a few ways for individualized User Profiles can be combined to: