A Quick Context on Problem at Hand

There was a strong outside-in perspective that advertisements were a key revenue lever for all e-commerce platforms. However, none of these platforms had built a suitable product for Small and Medium Businesses.

Our first problem was to establish the right Product-Market Fit for the SMB sellers of Meesho.

The other challenge at hand was to continue our strong offering of being lowest cost destination of all products, without a trade off on the ads revenue targets.


We achieved the product and business milestones in only 9 months, which other e-commerce platforms usually take 3 years to reach!

How did we do it?

Here are 6 hacks we used to which boosted our speed throughout:

Hack 1: A Decision Making Framework for a Faster Stakeholder Alignment

The Ads product had a significant influence on the User & Seller experience. Users were constantly exposed to Ads in their product discovery experience and sellers invested freely in Ads to expand their business.

Needless to say, teams like User Acquisition & Retention, Shopping Experience, Seller Growth, and Category Business needed to be aligned on various key decisions like where could we show the ads, what kind of supply should be exposed to Ads and so on and so forth.

Alignment on multiple such decisions across the org could significantly slow down the pace. Hence, we decided to come up with a decision making framework which all stakeholders could use.

How did we create the framework?

Based on internal and outside-in research, we created a metrics based framework with pre-defined thresholds which became the boundaries for our experiments.    
We defined multiple metrics which could be a measure of user experience.

We also identified acceptable limits for these metrics.

Pre-alignment of the framework helped in quick decision making and experimentation across org.

Hack 2:  Applied the Pareto Principle — Focus on 10X Initiatives Only

One of the key reasons for rapid growth in monetization was the steady pace of identification and execution of 10X initiatives. We did ruthless prioritization on which initiatives to pick.

Hack 3: Built Enough Conviction of Identified Opportunities through Code free initiatives

Building conviction requires a lot of primary and secondary research which can slow down the entire product development lifecycle. To mitigate this risk, we identified ways to create quick impact and validate ideas at the same time without building anything substantial.

Here's an example: Improving ROI for new sellers was a potential 10X problem identified to improve retention of sellers to Ads product. This was happening because sellers did not have a clear framework to decide which catalogs to advertise, and hence ended up investing in poor performing catalogs.

We also realised that a scalable solution for this problem would be to build a  Data Science driven model that could identify and recommend catalogs to sellers, in order to deliver the highest ROI.

Since we did not have enough Data Science or Design resources to build this quickly, we approached  the problem differently:

  • We built a basic analytical model using the views and orders data of catalogs to identify the best catalogs for a seller
  • Leveraged mass communication methods on both on and off the seller panel like PNs, SMSes, Notice Boards, etc. to promote these catalogs to sellers, as the best catalogs to advertise
Within a week, we achieved 15% increase in ROI for new sellers leading to a similar jump in Seller activation on Ads.

Hack 4: Applied the 90-50 Rule: How to achieve 90% impact by doing 50% work?

Narrowing the scope was a tricky decision. You could probably end up reducing the scope by X% and risk getting only 10-20% impact.

The aim of scope reduction was to reduce the time to create impact but at the same time it needed to find a balance against trading off only low impact initiatives. Making these decisions required a strong understanding of the User, Product and Business functions.

For example: CPC bidding was a 10X initiative that we identified. Outside-in research showed that average time to build and scale CPC bidding is almost a year!
We identified many aspects of CPC bidding like Bidding controls, type of bidding auction, etc — which could be done away with for our sellers and help in a faster adoption of feature without reduction in impact.

Hack 5: Sought External Help — Reused Tech capabilities that are already available within the teams

We leveraged pre-existing capabilities like Search Listing Ads, Personalisation, Listing Frameworks without creating an Ads specific framework from scratch. This saved us time as well as helped in faster integration with existing system.

Hack 6:  Built a Self Sufficient Cross Functional Team with A Common Goal

From the onset, we expected few challenges around resourcing, and how relying only to the central product and tech pods could lead to high friction on prioritisation, time as well as expertise.

The pod ways of working at Meesho came in handy, where we had built a team which had the right set of skills, expertise as well as 1 common goal.

This team had functional experts from Data Science, Design, Product & Engineering. We also borrowed dedicated POCs from other teams like Feed and Seller Growth, and Product — which significantly improved our product velocity over the course of the year.

Final Outcome of Speed Over Perfection:

We overachieved our Ads targets by 40%, and accomplished launch and scale of Ads product within 9 months straight! We continue to work on similar ways to achieve great speed at Meesho.

If you would like to become a part of such amazing 0 to 1 experiences, please visit our career site to check out our openings!

Written by: Prasanna Arunachalam

Illustrated by: Shoumita Dhar, Aastha Shah