This post is for our Paid Subscribers. If you haven’t subscribed yet,
Clarifying Questions
Q: Are we talking about online purchases broadly -- across all categories and platforms -- or are we focused on a specific vertical such as fashion, electronics, grocery, or a specific platform type such as a marketplace (Amazon/Flipkart), a D2C brand site, or a social commerce platform (Instagram Shopping, Meesho)?
A: I will frame this as a product problem for a horizontal marketplace (think Amazon India or Flipkart) rather than a single-category D2C site, because the horizontal marketplace context surfaces the broadest and most interesting set of consumer challenges. On a single-category D2C site, the product assortment is curated and the brand’s quality is relatively consistent; the consumer challenges are narrower. On a horizontal marketplace, the consumer is navigating thousands of sellers, wildly varying product quality and description accuracy, a complex return and refund ecosystem, and a fulfilment network with significant variance. The most impactful PM work in e-commerce is on the horizontal marketplace -- that is where the consumer challenges are systemic rather than boutique.
Q: Which stage of the purchase journey should we focus on -- discovery, evaluation and decision, checkout, or post-purchase? Or should we take a full-funnel view?
A: Full-funnel, with the explicit acknowledgment that the pain points are not evenly distributed. In my experience, the highest-severity problems are concentrated in the evaluation and decision stage (where information quality and trust drive conversion) and the post-purchase stage (where fulfilment failures, return friction, and customer service quality determine long-term retention and LTV). Discovery has been heavily optimised by SEO, personalisation, and recommendation algorithms. Checkout has been significantly streamlined by saved payment methods, one-click purchase, and EMI options. The evaluation and post-purchase stages remain the primary sources of consumer frustration and deserve the deepest solutions.
Q: What is the user geography and digital maturity assumption?
A: I will anchor in India, specifically Flipkart’s context, because it is the most interesting design challenge. India’s e-commerce market crossed $70 billion in annual GMV in 2023 and is projected to reach $150 billion by 2030 (Bain and Company, 2023). But the consumer maturity is highly heterogeneous: urban metro buyers (Tier 1 cities: Delhi, Mumbai, Bengaluru) are sophisticated e-commerce users who have been buying online for 7-10 years, are comfortable navigating complex catalogues, and primarily worry about product quality, delivery speed, and returns. Semi-urban and Tier 2-3 city buyers are more recent online shoppers (first online purchase within the past 3-5 years for many), are more reliant on vernacular-language product descriptions, have higher anxiety about payment security and delivery reliability, and are more likely to make their first-ever purchase in a category online (meaning they lack the baseline product knowledge that a metropolitan buyer brings). These two consumer profiles have meaningfully different pain points, and a well-designed solution must address both.
Q: Are we solving for mobile-first users, desktop users, or both?
A: Mobile-first, unambiguously. India’s e-commerce is approximately 85% mobile app-driven, and the Tier 2-3 buyer profile I described almost exclusively uses a smartphone as their primary (and often only) internet device. The solutions I design must work within the constraints and opportunities of a mobile app context -- camera access, voice input, push notification patterns, offline capability, and data-light design for users on 4G with variable connectivity.
Q: Should my solutions focus on product features the PM can build within the marketplace platform, or should they include seller-side policy and ecosystem changes?
A: Both, because the most chronic consumer problems on horizontal marketplaces are caused by seller-side behaviour (inaccurate listings, slow fulfilment, unhelpful return policies) that no amount of consumer-side feature work can fully compensate for. A PM on a marketplace product must think in terms of ecosystem design -- the incentive structures and tooling you give sellers affect the experiences consumers have. I will include both consumer-facing features and seller-side policy and tooling changes where they are necessary to solve the consumer problem at its root.
Product Description
My name is Ananya Krishnamurthy. I am a Product Manager at an e-commerce technology company in Pune, where I have spent three years building buyer-side trust and conversion features for a mid-sized Indian marketplace. I bring a practitioner’s perspective to this question -- I have seen the data on where buyers drop off, what drives returns, and what separates a loyal repeat buyer from a one-time user who never returns after a bad experience.
India’s e-commerce market is large, fast-growing, and structurally complex. Flipkart (owned by Walmart since 2018, approximately 55% stake) is the largest Indian e-commerce company by monthly active buyers, with approximately 400 million registered users and approximately 100 million annual transacting buyers as of 2023. Amazon India is its primary competitor with approximately 80-85 million annual transacting buyers. Together, these two platforms account for approximately 60-65% of India’s e-commerce GMV. The market is served by over 5 million third-party sellers on Flipkart alone, with wildly varying levels of operational sophistication -- from large national brands with dedicated e-commerce teams to one-person operations in Tier 3 cities with a smartphone, a product, and a Flipkart seller account. The average order value on Indian e-commerce platforms is approximately Rs 800-1,200 (roughly $10-15), which is lower than in the US or China, meaning that the margin for error on each order is small and the economic impact of a bad experience (a return, a replacement, a customer service escalation) is proportionally high relative to the transaction value.
The consumer’s experience of online purchasing has improved dramatically in India between 2015 and 2023: payment UX (UPI has revolutionised digital payments, with zero-cost immediate transfers that are simpler than card payments), delivery speed (same-day and next-day delivery is standard in metro cities for Flipkart’s own logistics network), and product assortment (effectively every product category is now available online). However, the structural challenges that remain -- trust gaps, information quality failures, return friction, and post-purchase anxiety -- are disproportionately felt by the newer, less experienced buyers in Tier 2-3 cities who represent the growth opportunity for the next 150-200 million e-commerce buyers in India. Solving for these buyers is where the largest business impact and the most interesting PM challenge sits.
Define Goal
The core problem is that online purchasing requires consumers to make a buying decision based on incomplete, imperfect, and often inaccurate information -- product photos that do not match the actual product, specifications that are misrepresented or missing, reviews that may be manipulated, and delivery estimates that turn out to be aspirational. The result is a fundamental trust deficit: consumers are uncertain whether the product they receive will match what they saw on the screen, whether it will arrive when promised, and whether they can return it without a painful process if it does not. This uncertainty is the single biggest driver of cart abandonment (estimated at 70-75% of all initiated shopping sessions globally, per Baymard Institute), repeat-purchase suppression, and low average order values among newer buyers who are afraid to spend more until they have validated the platform’s trustworthiness with a small test order.
The goal I want to focus on is: reduce the post-purchase negative experience rate (defined as returns driven by “not as described,” “wrong item delivered,” or “quality does not match listing”) by 40% within 18 months, while simultaneously reducing the consumer’s perceived purchase anxiety at the evaluation stage, measured by a 15-point improvement in pre-purchase confidence NPS.
North Star Metric: Repeat Purchase Rate at 90 Days. I define this as the percentage of first-time buyers in a given cohort who make at least one additional purchase within 90 days of their first order. This metric is North Star because it integrates the quality of the entire purchase experience -- discovery, evaluation, checkout, delivery, and post-purchase resolution -- into a single outcome signal. A buyer who had a good experience on their first order (received what they expected, on time, with a smooth resolution if anything went wrong) comes back. A buyer who had a poor experience does not. The 90-day window is calibrated to the Indian e-commerce consumption pattern: a buyer with genuine intent to repurchase will typically do so within 90 days for most product categories. The current estimated baseline for first-time buyer 90-day repeat purchase rate on major Indian marketplaces is approximately 28-32%; the target is 45% within 18 months.
User Segmentation
I segment buyers based on their e-commerce experience level and purchase behaviour, as these determine the nature and severity of the challenges they face.
Experienced Metro Buyers (Tier 1 cities, 5+ years of online shopping, approximately 30-35% of active buyers): Typically aged 25-40, shop online for the convenience and selection, are comfortable comparing multiple products and sellers, rely heavily on user reviews and ratings, and have a baseline expectation of 1-2 day delivery. Their primary pain points are in the evaluation stage (difficulty assessing actual product quality from photos and specifications, particularly for electronics, fashion, and home goods where variance between listing and product is high) and in the post-purchase stage (return and refund processes that are technically available but often frustrating in practice, particularly for marketplace sellers rather than Flipkart’s own fulfilment). These buyers have high lifetime value if retained -- their 12-month average spend on the platform is estimated at Rs 12,000-18,000 -- but are also the most likely to migrate to a competitor if a specific experience failure is not resolved well.
Semi-Urban First-Generation Buyers (Tier 2-3 cities, 1-3 years of online shopping, approximately 40-45% of active buyers and the primary growth segment): Typically aged 22-38, have made 3-10 lifetime online purchases, are still building the mental model of how online shopping works, and have acute anxiety about product quality (will it look like the photo?), payment security (will my money be safe?), and delivery reliability (will it actually arrive?). These buyers often purchase online because a product is unavailable in their local market, not primarily for convenience -- meaning the stakes of a failed purchase are higher (no alternative source). They are highly influenced by social proof (WhatsApp recommendations from family and friends, video reviews on YouTube) and are more likely to use cash on delivery (COD) as a risk mitigation strategy for their first few orders in a category. Their 12-month average spend is lower (Rs 4,000-7,000) but their CAC is also lower because many come through organic word-of-mouth, and their LTV potential is high if the first 2-3 experiences are positive.
Occasional and Category-Specific Buyers (all geographies, purchase frequency of 1-3 times per year in specific categories, approximately 25-30% of buyers): These buyers use online shopping for specific, planned purchases -- a smartphone upgrade, a festival-season clothing haul, a large-appliance replacement -- rather than as a regular shopping habit. Their pain points are concentrated in the high-stakes evaluation moments: when spending Rs 20,000-50,000 on a product they have never bought online before, the information quality, trust signals, and post-purchase guarantee terms matter enormously. These buyers are the most likely to abandon the cart at the final payment step due to last-minute anxiety, and the most likely to make their purchase offline at a physical store if the online experience does not adequately resolve their concerns.
I will focus the primary solution design on the Semi-Urban First-Generation Buyer segment, as this is where the growth opportunity and the product impact potential is highest. Many of the solutions that address this segment’s acute trust and information needs will also benefit Experienced Metro Buyers; the converse is not true.
Pain Points
Synthesising buyer research, support ticket analysis, and published e-commerce consumer studies:
