Data # New product research from what is on the shelf Live listings show the range, pack sizes, price bands and reviews already in a category. They do not measure demand, so a gap is a question to test with shoppers, not proof that a product will sell. Map what exists first, then test the empty spaces with real buyers. ![](https://rewalto.com/_next/image?url=%2Fbrand%2Fog%2Fguides-new-product-research.png&w=3840&q=75) In this guide 1. [Start with the decision, not the data](#start) 2. [What live listings can show you](#what-listings-show) 3. [A gap is not demand](#gap-is-not-demand) 4. [The Indian context: pin codes, quick commerce and launch timing](#quick-commerce) 5. [What a useful research report contains](#report) 6. [Before you commission anything](#next) 7. [Testing a gap before you build on it](#testing) 8. [Common questions](#questions) [Explore datasets](https://rewalto.com/data) By [Varun Mahajan](https://rewalto.com/about), FounderPublished 24 September 2026Last updated 18 October 2026Part of the [brand playbooks](https://rewalto.com/use-cases/brands) guide ## Start with the decision, not the data Product teams usually arrive at research with a half-formed idea: a new variant, a different pack size, a product for a segment the brand does not yet serve. The research is only useful if it is tied to a decision someone has to make, such as whether to take the idea forward, which format to test first or how to price it. Write the decision as a sentence before collecting anything. For example: should we launch a smaller pack of this product for quick-commerce, and if so at what price band? That sentence tells you which listings to look at, which apps matter, and what would change your mind. ## What live listings can show you Shopping apps are a large, public, constantly updated catalogue of what is being sold. A careful read of it in one category shows a good deal: which brands are present, which pack sizes they sell, how prices are spread across those sizes, what claims appear in titles and descriptions, how many reviews and what ratings the leading products carry, and which products have recently appeared. Price per unit deserves special attention. Comparing a 100 g pack with a 250 g pack on shelf price says little. Converting each to a price per 100 g or per kilo shows where the price bands are and where a pack size would sit in them. The same logic applies to price per serving or per wash where that is how shoppers think. Reviews are useful in a specific way. What shoppers praise and complain about in a category, in their own words, points to what the existing products do not yet satisfy. Read a set of reviews across the leading products for repeated themes, rather than relying on one vivid comment. - Range: brands, formats and pack sizes already sold, and where the assortment is thick or thin. - Price bands: shelf price and price per unit across the range. Step 1 Define the category The listings, pack sizes and price bands already live. Step 2 Read live listings Range, price bands and reviews already in the category. Step 3 Map the gaps Where the existing range is thin, not where demand is proven. Step 4 Test with shoppers A gap becomes a hypothesis to validate, not a launch decision. A gap in the shelf is a question to test with shoppers, never proof a product will sell. ## A gap is not demand This is the most important limit in the whole exercise. Seeing that no product occupies a particular pack size, price band or claim does not mean shoppers want one. There may be no product there because nobody wants it, because it is uneconomic to supply, or because it has been tried and withdrawn. A listing shows that something is offered. It does not show how much of it is sold. Treat each gap as a hypothesis. Something like: shoppers in this category may want a lower-sugar option under a given price. Then test it with methods listings cannot replace: talking to shoppers, a small trial, a look at your own sales in adjacent products, or retailer feedback. Reports that present a shelf gap as a proven opportunity are overreaching, and a product team is right to ask what evidence sits behind that word. Similarly, listings are not a sales forecast. A category crowded with well-reviewed products may still have room, and a sparse one may be sparse for a reason. ## The Indian context: pin codes, quick commerce and launch timing In India, the shelf a shopper sees depends on location. A quick-commerce app serves an assortment from the dark stores near a pin code, so the range in one neighbourhood can differ from another. If your launch idea depends on a city or a type of area, check the shelf there rather than assuming a national picture. Marketplaces and quick-commerce apps also behave differently. Marketplaces carry a long tail of sellers and pack variants. Quick-commerce apps carry a narrower, faster-moving range. A pack size that looks absent on one may be present on the other. Decide which channel your launch will use first and study that shelf most closely. Finally, look at what has arrived recently. A category in which several new products have appeared in the last few months is telling you something different from one that has not changed for a year, though what it means for you is a judgment to make with your own knowledge of the category. ## What a useful research report contains Whether you build it in-house or commission it, a report you can rely on has a few features. Every chart can be traced to the rows it was drawn from, so a colleague can check a number. Observed listings are kept separate from interpretation and from anything estimated. The limits are stated: the apps and pin codes covered, the dates, and what was not looked at. And it ends with a short list of next questions rather than a verdict. A useful category review keeps recorded products, pack sizes, prices and reviews separate from assumptions about demand. Put source listings beside each finding and list the questions that still need interviews or sales data. For underlying records, check the [data catalogue](https://rewalto.com/data). The [data feed and API guide](https://rewalto.com/guides/shelf-data-api) explains what to inspect before connecting a source. Confirm usage rights before including records in a client presentation. ## Before you commission anything Browse the category on the apps where you would sell, at the locations that matter. Note what surprises you, then separate questions you can answer from listings from those that need customer research. Bring that specific gap to a research partner. ## Testing a gap before you build on it Once the listings suggest a gap, the next job is to test it cheaply. Start with the people closest to the shopper: your sales team, your customer support inbox and your retailer contacts. Ask whether shoppers have asked for the product you are imagining. Their answers will not be statistics, but they will tell you quickly whether the idea is plausible or has an obvious flaw. Look at your own data next. If you already sell adjacent products, check how they behave: do the larger packs sell in some cities and the smaller ones in others, do reviews mention the feature you would add, do returns or complaints point to an unmet need. Your own sales history is stronger evidence of demand than any listing. Then consider a small, reversible trial. That might be a limited pack, a single city or a short run on one app. A trial costs something, but far less than a full launch, and it produces the one thing listings cannot: real orders. Keep the shelf research for what it does well: framing the question, showing where competitors cluster, and making sure you have not missed a product that already fills the space you had in mind. It is common to find that an apparent gap is filled by a product sold under a name you did not know. Finding that in a week of research is a saving, not a setback. When you present the work internally, keep the claims to what the listings show. Say that the listings suggest an area worth testing and list the tests you propose. Avoid saying that the research shows demand. Teams that make that distinction early avoid the awkward moment, months later, when a launch that looked well supported does not sell. ## Common questions ### Does new product research tell me whether people will buy my product? No. Listings show what is offered, not what sells. A gap is a hypothesis to test with shoppers, not evidence of demand. ### What does Rewalto's new product research include? A source-backed view of recorded products, pack sizes, prices, reviews and potential category gaps from live listings, delivered as a page and a deck. ### Is the free site audit the same as new product research? No. A website check and category research examine different evidence. The former free site audit did not include category or shopping-app research and is no longer offered. ## Start with the question you need to answer Check the current data catalogue, then review the coverage and dates against your question. The research in an older guide does not establish that a service is available today. [Explore Rewalto data](https://rewalto.com/)[Explore current data](https://rewalto.com/data) ## Related from the blog [From the blog ### Market-size tables cannot pick a launch city. Pin-code readings can help Public figures for fitness, eyewear and vehicles show where a category is large. What they cannot show, and how pin-code shelf readings help choose where to launch. Explore](https://rewalto.com/blog/pick-a-launch-city-with-pin-code-readings) ## Related guides [Quick-commerce shelf ### Digital share of shelf: a definition you can defend How to define and measure the share of results your brand fills, and where the figure misleads. Explore](https://rewalto.com/guides/digital-share-of-shelf) [Data ### Shelf data by CSV or API: what to ask before you connect it How teams use shelf data, CSV or API, and the questions to put to any provider. Explore](https://rewalto.com/guides/shelf-data-api) --- Canonical page: https://rewalto.com/guides/new-product-research Last content change: 2026-10-18