A Guide to becoming a Data Driven Product Team

A Guide to becoming a Data Driven Product Team

Product management teams that use data to drive their decision making are more successful than those that rely only on gut. You will never have all the data you need but asking the right questions helps move the culture of the organisation in the right direction. In larger companies you might have an analytics team that you can rely on. But if you work for a small company chances are that as a product manager you will have to find and analyse the data! It can be a daunting task if its the first time you’re doing it but it is worth it in the end!

START with Questions

Start with asking the right questions. This will give you a good understanding of the current state of data in your organisation.

1.What do we want to measure and why?
2.What data to we collect now?
3.Is the data we collect today useful?
4.How is the data used to drive business decisions?
5.Who uses this data?
6.How easy is it to collect the data?
7.How do people access the data today? In what form?

Talk to the different teams in your company to find the answers to these questions. They will help you get a grasp on the scope of the work required in becoming a data driven product team. Then treat it like a product. Prioritising what’s most important and start working on it first. Once you have answered the above questions you’ve completed the first step in your data journey.

DEFINE Key Product Metrics

These are metrics that help you track the success of your product. Thye can be further broken down into different areas depending on what the focus for the company is at the time. Metrics should be:

1.Easy to understand
2.Be able to tell you how the product is performing

Your organisation will want to focus on different things at various stages of its evolution. It is important that the product metrics align with the business goals of the organisation. Otherwise you will end up wasting your time and energy on things that are not important. More about product management metrics here.

Let’s look at it through an example:

Your company wants to grow revenue. It has decided to focus on new customer acquisition as the primary way to do it. You offer a free trial of your product to users. The marketing team is getting more leads to the website and sign up for a free trial. Your task is to create meaningful product metrics to report.

So you ask yourself:


What information will help the business in achieving its goal. In this case it can be many things. For example it could be number of people:

Signing up for a free trial
Logging into the product
Spending more than “x” amount of time on the product
Logging in more than once

Does the business care about all the nitty gritty details?OR


Is there something more meaningful we can derive from this data?

In this case the product metric you can report is the conversion rate of free trial to paid customers. It could be something else as well and driven by the inherent nature of your key target personas.

FIND the Right Data 

This is often the most time consuming part. How do you find the right data? Again, start with questions and chip away one by one. It will make things clearer.


What data do you need to track?
You will get this from the product metrics discussed in the above section.


Is the data already tracked somewhere?
Most organisations track a lot of things. Sometimes too many things. In the long run developing a data strategy for the entire organisation helps reduce redundancies. Let’s follow the above example. The sales and marketing teams might already be tracking some of data in the systems they use. You can get access to them and stitch the data together to calculate the product metric.


How do I track the data that is missing?
If none of the data points or only some of them are being calculated then you’ll have to do some heavy-lifting. In most situations your company will be applying either of the two statregies to track data:

Custom tracking events that your development team writes,OR
Using an application or interphase where the users can themselves setup event tracking You will have to work closely with your development team to get the data tracking setup and then convert the raw data into key metrics

COMMUNICATE the Product Metrics

You might be collecting and reporting metrics and think this is great! But no one might be looking at them . Or even worse people might not know the metrics exist! Yes this is a real possibility in any company even after you have sent out an email, announced it on slack or communicated in person.

For example, in a past role I would update metrics on a weekly basis but never got any questions from anyone. After a few weeks I started to wonder if something was wrong. Turned out that no one was actually looking at my reports! Why? Because it was yet one more application they needed to sign into. Surprise Surprise!

Lesson Learnt- Choose a medium to communicate that doesn’t add an overhead for others to access.

How you communicate will vary in each company. You have to develop it in consultation with your stakeholder. Find out what they would be most comfortable using. Experiment with different mediums to find the one that’s most effective.

The other aspect is the structure of the communication itself. It has to cater to different types of stakeholder. Some people only want to know the metric, others like to dig deeper into it. You should report:

1.The value of the metric for the current period
2.The expected/target value
3.If there is a deviation then explain the possible reasons for it
4.State any followup actions that will be taken
5.The definition of the metric
You might have had this big meeting where everyone worked together to come to what the metric means. But guess what. People forget! Its critical to state exactly what the metric stands for in each communication
6.Assumptions you have made to derive the metric
7.Links to all the data sources and how to log into them.
8.Who to contact in case there are questions

AUTOMATE the Process

You want to build a data strategy for your product team that can scale. In the beginning you will be doing everything manually. Whether it’s collecting data from different sources, stitching it together and finally sending it out. Gradually you can automate the process. Start with the things that are transactional and easy to automate. Find the right balance. Some things might not be worth automating considering the investment required.


As the needs of the business evolve the key metrics you track will also change. You should have regular feedback sessions with stakeholders to improve the process. It is important to collect and analyse data using ways that make it easily extendible. This way you don’t have to start from sratch everytime something new needs to be tracke and analyse.

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