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5 Keys to Create a Data-Driven, Customer-Centric Mindset

Creating products that have value for the user is what matters the most for a Product Manager (PM). Understanding why users interact with the designed product, what problems they encounter most frequently, what their needs are, is part of every PM's daily routine.

This is why at BOOM we have built a customer-centric culture. Here are four main points to take into consideration for a successful product team mindset: 

Vanity 1, Usefulness 0.

Very often, the activities prioritized within the backlog are determined by internal mediation between the product team and business stakeholders, with confusing outcomes as the value for the user becomes mixed up with the value suggested by other departments. As a result, you will find yourself administering a list of features rather than a list of needs. 

So the question is, what strategies create useful products that satisfy users’ needs?

The answer lies in focusing on data more than opinion, being willing to learn everything you can about your product as fast as possible, and above all, experiment as much as you can!  

Data Beats Emotions

At BOOM we have a motto: "If you can’t measure it, it doesn’t exist at all".

Having opinions is legitimate and they are often useful for analysis. 

But with data to back them up, opinions become facts, which are rarely questioned. 

Therefore, we believe that the only element capable of guiding our choices is the data that comes from appropriately structured analysis about user needs, user behaviors, and the analysis of other data that will tell us something worth investigating. 

So how can we understand what is really important for the end-user?

And above all, how can we release value in the shortest time possible?

To this end, product discovery is what supports us.

Learn Fast.

Once a problem is observed or a need is perceived, there is a hasty tendency to ground a functionality. It doesn't matter if the information is partial or if the problem comes from a single source - what matters is having the backlog full of activities and having the tech team committed to developing them. Do you know what happens to those cases?

The tech team will have worked on features without a concrete goal, but more importantly, the users’ problems won’t be solved, leading them to abandon the product because the outputs would have been favored over outcomes. 

The alternative? Once you identify the problem at hand, ask yourself the following two questions: 1) What do we know about this problem 2) what do we not know about it? 

If the elements we don't know are far superior to the ones we do know, then a discovery phase is in order. In that case, we must keep an experimental mindset and ask ourselves: how can I validate the information I already have?

Data Insights and Data Collection

At BOOM’s product department, we have structured a continuous discovery process inspired by the ones experienced PMs like Melissa Perri and Teresa Torres developed.

First: Let's understand what we know today.

Second: What do we want to know tomorrow?

The answer lies in establishing a clear, shared and above all measurable goal.

Keep in mind that while an individual user's need is not significant in itself, it becomes noteworthy if other users express the same type of need. A problem cannot be analyzed from a single perspective as it can be the result of a series of interviews, and it is often necessary to diversify the sources in order to collect and organize as much information as possible.

When analyzing user behaviors, we look for information on how they use and interact with the product. We try to understand what users really need by collecting data and discussing it with the DWH team, who simultaneously conducts other data analyzes, combined with those collected by the Consumer Insight team.

Experiments

After combining the various quantitative and qualitative analyses of every single problem and mapping as clearly as possible, we must define the outcomes we aim to accomplish

Just like eagles’ behavior pattern, the best way to go about it is to fly to the peaks of the mountains to find out what’s going on, then descend into the valley to focus better, and only then dive down to the bottom of the valley.

In other words, the goal of these analyzes is not to plan functionalities (outputs) but to plan tactics to quickly learn as much as possible about our users. To this end, we set up a series of small experiments that can support us in our subsequent evaluations - which will make it possible to release many small MVPs by validating initial assumptions, collecting other data and improving what has already been created. 

Continuous discovery is a daily process that is paired with continuous delivery.

The harmony within a team of engineers is essential to create successful products, which is why our discovery activities are never limited to the product department. Instead, we believe in transparency and in the fact that there is not a single person appointed to generate new ideas. Smart people make it easier and more exciting to work on new products.

Interested in finding out more? Visit our tech pages!

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