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Beyond data: Developing product intuition from qualitative user behavior

Beyond data: Developing product intuition from qualitative user behavior

About Rishabh Srivastava

Rishabh is the founder of Data Narratives, a data intelligence tool for enterprises. He previously started Loki.ai, a bootstrapped data APIs company for data in Asia.

I was incredibly excited in October 2021. We had been crafting a data research platform for analysts since August 2021, and Data Narratives was finally out in the wild! I thought that my product would be a hit and solve a pain point that many had keenly felt

But when I rolled it out, most people just went, “So… what does this do exactly?”

The limits of quantitative data analysis

In the words of a friend, my product “looked like it was built by an engineer”. It did the job – but was clunky, unintuitive, and difficult to use for most users.

Flash forward 6 months, and we have a far better product. Our average session duration is up 12x, unique visitors are up 100x, and we have powered data discovery and analysis for 8 large enterprises across 3 countries since then.

We had to unlearn a lot of bad habits to get here. I am extremely data-driven in everything I do, but we ran into the limits of quantitative data analysis as we got more usage from our product. We knew that our session duration was low, but didn’t know why. We knew that users weren’t using “power” features, but also didn’t know why. Quantitative data analysis was a great way for us to figure out where the problems in our product were. But it didn’t tell us how we could solve them.

Qualitative Analysis and Product Intuition

Once we realized that quantitative data and product analysis were necessary but not sufficient for building a great product, we started investing in qualitative research. We got on calls with users to see how they were actually using the product, and asked them questions while they were working on the product. We learnt two surprising things:

1. What was obvious to us was often invisible to users

Features that were second nature to us (we are power users of our own product) were not even visible to first-time users. We help users search for economic data, and have a dashboard feature to help them save data that they’ve found into dashboards.

The more we tested (using Betafi), the more we realized that users could not figure out even the most basic features of our product.

2. Testing made concrete the problems that were previously invisible to us

The best part of testing was discovering user needs that we had not even thought of. We took notes furiously as beta users tried our app, and learnt about the jobs to be done that they wanted to do but weren’t able to with our product.

Having structured notes from 100s of conversations like this significantly helped us build intuition about our product – in ways that looking at Google Analytics just could not. Product validation frameworks are useless without taste. Being able to viscerally understand how users were using our product was insanely important in helping us ask the right questions of our users and of ourselves.

Diffusion of learnings in the team

Until November, I was the only person involved in developing the product. And with the benefit of 100+ customer interviews, I had the benefit of understanding product usage in ways that the incredibly smart people who joined later on did not.

Weirdly, that ended up being much less of a problem that I had anticipated. The old adage in programming is that Code Wins Arguments. But code doesn’t help you get alignment on how to build a great User Experience. Surprisingly – customer usage video does solves arguments.

An example: I was having a discussion with our designer on how, exactly, we could improve the date range selector on the Betafi. As much as I am a fan of reasoning from first principle, the discussion was not going anywhere.

But this clip of a user struggling to change the date range solved it immediately. Any time your user literally says “Huh?!”, you know that you have a suboptimal user experience.

A combination of notes and clips like this has been an incredibly useful way to diffuse product learnings across our small team of 4.

Protip: use the same hashtags across user sessions, it REALLY helps in staying organized when you have loads of sessions.

I am still a big believer in data driven decisions (as the name Data Narratives suggest), but also better appreciate how qualitative conversations help build product intuition. With more users on the product, we also watch videos of customers using the product using tools like Clarity, but continue to use Betafi to get feedback on our upcoming features at the design stage.

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