The perfect blend of product and data | Day-to-day tasks, tools used, & skills required

I’m a Product Analyst at a B2B e-commerce firm in India. I work in the Credit arm — we give credit to Small and Medium Enterprises. From my past experience in product roles (job, internships, projects) I can say that my current job is a fair representation of the role of a Product Analyst in general. In other words, the role of a Product Analyst in other organizations will be quite similar to the description I’ve given below.

Throughout this article, I’ll use interesting graphs and charts, just as I do in my job. Let’s get right to it.

In today’s day and age, data-backed decisions are considered stronger and are being given preference over decisions based on intuition/gut. To enable your organization to take data-backed decisions, you need to first ensure the following:

• Data Instrumentation — you are capturing the right data from your product/service
• Data Format — whether data is in the right format
• Data Staleness — how stale/fresh the data is

Even after you have the right data, it is important to present it in a format that makes sense to the viewer and helps the person derive insights and take decisions based on the data. Do bear in mind the fact that data might not be able to carry you to the last mile — the nature of some problems is such that intuition and experience will be the guiding light.

As described in the above donut chart, my day is divided into 6 parts broadly:

1. Defining problem statements, breaking them down, and thinking of solutions. In most cases, the solution is a query and a corresponding dashboard. But before writing a query one needs to think of the data — which tables to look in and what all filters to include.
2. Writing an SQL query. In my case, I write queries on DataBricks and our company’s own Data Platform. It is important to follow best practices — write optimized queries and write them in a way someone else can understand.
3. Dashboarding. Once a query has been written, the data needs to be presented visually to stakeholders. This can be done by building dashboards on tools like Tableau, Google Looker Studio, Python libraries, etc.
4. Spending time to analyze the dashboards and derive insights. In my opinion, this is something that distinguishes a good product analyst from a bad one. When I joined as a product analyst, I just created the charts and left the task of deriving insights to other people (product/business teams). But now I specifically devote time to deriving useful insights from the chart. The logic is simple — since I have made the visualization, I know the intricacies of it and might be able to extract hidden information and useful trends from it, better than other people can.
5. Product Analytics. The data from the app and website provide precious information about user behavior and can be leveraged to take decisions for the app and website. For example, introducing a new feature on the app is a job half done. We need to also analyze how users are adopting that feature and whether that feature is providing some value to the users.
6. Meetings. As expected, this forms the most time-consuming part of my day. This includes presenting and discussing problem statements, data, and the corresponding actionable from the same.

Apart from all this, there are many ad-hoc tasks — discussing problems with the team, reading emails, assisting software engineers in instrumenting features, assisting the business team with critical information, etc. Every week, I devote some time to upskilling and learning new tools. This, I believe, is essential if you wish to stay at the top of your game.

Every day I interact with a number of people, partly because I am working on a number of problem statements parallelly, each with a different team.

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