Making decision-making easier for D2C brands
MY ROLE
Product Designer
TEAM
1 Product Designer (me), 1 PM, 4 Engineers
YEAR
Pre-Diwali 2023
Project Summary
I helped D2C brands act faster on their data by designing a feature that turned reports into simple marketing ideas and insights.
We did this by using existing data and framing it in short, easy-to-understand sentences.
Problem statement
Merito’s reports gave users detailed data, but users still had to work out what it meant. We wanted to move from just showing numbers to helping them act on insights.
THE USERS
Making data easier to read for D2C brands
Merito’s target customers were D2C brands scaling from 0 → 1.
Even with data in one place, founders and marketers still spent hours analysing reports, leaving less time to actually grow the business.
My role in the project
As the Product Designer, I worked with our engineers and data scientists to make data easier to read and act on.
I studied how users explored reports, listened to product calls and went through support tickets to understand how they made decisions.
Then translated this data into a feature called "Boost."
SQUARE ONE
Understanding the problem
From research, we found that users spent a lot of time analysing reports before taking action. Many also didn’t fully understand “workspaces.”
Since changing the workspace model would take time, we built a new feature instead.
The brief: Help users act faster on data.
STRATEGY
Turn data into customised marketing ideas
We wanted the reports to feel more helpful, not just a list of numbers.
Since we already had the data, we shaped it into short ideas and insights that told users what was happening and what they could do next.
See, analytics can be descriptive, prescriptive or predictive. We focused on the prescriptive side.
This approach also opened up new ways to help users discover insights like - which product worked best as a first purchase for retention.
GUIDING PRINCIPLE
Upfront value
We wanted to give value right away, so every flow and piece of information was planned around that idea.
We also added a simple way to track sales against targets.
An earlier hiccup: users didn’t get how some reports helped them. I suggested showing popular reports to fix it (ik, wrong call, realised later).
Deploying the first draft
We had about 50 brands at the time.
Core branding was done as "Decision Hub", and it was a big step for Merito because it moved beyond traditional reporting for the first time.
We wanted to ship fast and test the idea.
Flow - Decision Hub
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FEEDBACK
It was too much
Users felt overloaded. There were too many options and the interface felt heavy at first glance.
So we simplified it. We moved from decision-based flows to metric-based insights, reduced the categories. Reworked the user journey granularly.
The interface now had two parts:
1. Ideas (suggestions linked to reports)
2. Moves (quick updates triggered by thresholds)
Two weeks later, it was live as "Boost."
Flow - Boost
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Boost-ed the feedback!
A key part of Boost was letting users vote on ideas and insights. Up if useful, down if not. We received about 20 feedback votes within two weeks of release.
Later, when we built WhatsApp reports, we automated messages with new ideas every Monday and Thursday, and attached insights to the reports.
Impact
Boost picked up quickly at launch. It drove 18% of all usage and was one of the top three features in the first two months.
After that, things slowed down. We couldn’t update the ideas, so people knew what was coming and stopped using it as much.
And when new channels came in, we never added their data to Boost.
Even so, Boost still became Merito's second-best acquisition tool, helping over 750 brands join by November 2025.
Metrics we tracked
Since Merito was still early-stage, we focused on usage and activation rather than long-term retention. The key metrics were:
Unique user clicks
Unique company clicks
Inactive users reactivated
Votes on ideas & moves
P.S. Read about how I built the WhatsApp daily reports here.
