How to identify the key problems to solve while building products- Part 2

The art of problem discovery in product management

This blogpost is part 2 in a 2-part series on problem discovery in product management.

• In part 1, we concluded with the following structured approach for discovering problems.

• In this part 2, we will leverage this structured approach and figure out key problems to solve in a Meesho (Lowest price e-commerce marketplace) case study

Meesho’s Lower price over convenience problem

Meesho is known to be the lowest price ecommerce platform. In 2021, Meesho was catering to both reseller and end-consumer personas through its platform. Now it is an end consumer focussed ecommerce marketplace.

Ecommerce platforms in India have a major returns problem (people change their mind and return the product even when the right product is delivered) that increases prices due to high logistics costs.

To reduce prices for the consumers, Meesho wanted to remove return costs that sellers add to the prices and offer consumers a lower price where they can return only if the seller is at fault.

Metric to move:

• Orders/ Active User
• Return% Reduction
• % Avg. Price Reduction (6%)

Here, while the strategy to reduce prices by removing return costs is clear, what the possible consumer challenges are that can come during implementation were not clear.

Ambiguity: How do we proceed?

Step 1: When in doubt, go to users

As a naive product manager, I believed that if we offer a lower price to customers, we would be able to convince them to give up returns. We spoke to user about their apprehensions around not having returns when seller fault is not there:

All the users we spoke to (20+) gave us the following learnings unanimously:

• Users have strong apprehensions if they are not able to return when they don’t like the product even if they get lower prices
• Not being able to return for not liking a product might make them leave the platform as consumers expect that to be a basic convenience

Step 2: Understand the why behind the problem (Analysis, Research & Hypotheses Building)

We tried to understand what is leading to such a strong need for the return convenience even where the product is neither wrong/ different nor defective

Further deep dive helped us uncover the following insights:

• Online shopping has a shortcoming on touch/ feel (comfort) and fit for fashion categories which is why users want the convenience of returns in cases where they are not sure of these parameters
• Users would be willing to try the lower price with returns only for seller fault if they are sure of the quality/ material of the product

Step 3: Validating the hypotheses to strengthen the insight

These insights gave us hope that there is merit in trying an approach where users have the lower price for products with only seller fault returns and also an optionality to return for not liking the product.

With the optionality, there is hope that a cohort of users will try the lower price and retain better if they like the product and also get a significantly lower price for it.

To validate this insight, we did prototype testing that also helped us shape the product solutioning for this problem. We introduced the return optionality just before ordering (at the time of add to cart)

Prototype Testing to validate the insight

Learnings from the prototype testing (15+ users):

• Explaining the trade-off between the two options is going to be difficult to explain to all users
• Paid return after order will not work well with users as they expect this convenience to be part of the payment they are giving while ordering
• Getting users to adopt lower price when they are not sure of quality will be a challenge and can lead to poor experience as the user will not be able to return the product
• Having a return option at the time of ordering (and not later) and an alternative lower price option can work and that too if users are able to understand the offer and are also confident about the quality

Step 4: Prioritising the refined key problems

Key problem to solve: While offering lower prices for seller fault only returns, explaining the trade-off between lower price and return convenience to the users is absolutely critical to enable users to make an informed decision.

If the users are confident about the quality of the product and are able to understand the offering, they are likely to take the lower price choice which can increase their delight as well as reduce returns.

We also took a conscious decision to de-prioritise the quality comprehension problem (subjective and long-running problem) as a part of this product stream and start offering lower prices with only high quality sellers for the initial versions.

Quality comprehension was later taken as a horizontal problem statement to help users better understand product quality on Meesho.

Next Steps: Deciding what to build to effectively solve the key problem (Product Solutioning) i.e. Comprehension of the Price-Convenience trade-off

Outcome: After a series of failed experiments and further multivariate UX design experiments to drive comprehension, we got a winning solution i.e. Calling out ‘Only wrong/ defective item returns’ as the lower price choice

Multivariate testing to explain lower price-return convenience trade off to users

The ultimate solution resulted in an additional 100,000 orders daily on the platform and a reduction of over 7% in return rates

Key takeaways for Product Managers to do effective problem discovery

• Problem discovery is more ambiguous and hence the harder part of product management (as compared to product solutioning or product delivery/ execution); do spend enough time on it to be sure of the key problem
• We can put a structured approach to problem discovery; although to build conviction, we may need to gather evidences from multiple sources e.g. in one case talking to users was enough but in the other we built prototypes to validate our insights
• Product management is more art than science; it requires strong product sense/ judgement when we don’t have hard data to take decisions e.g. removing quality comprehension from case 2 scope helped us built the product with less variables and we solved the key problem effectively
• To get better on the product sense/ judgement part, we need to

1. Deeply understand our users and how they use our product
2. Be curious to understand the why behind the problems (first principles thinking)

To conclude, within the realm of product management, problem discovery emerges as an art demanding both structured methodologies and adaptive flexibility. By delving into user needs, forming hypotheses, and validating insights, product managers can navigate ambiguity and find those key problems that if solved effectively, can truly create massive impact for both the users and the business.