Move the price by five percent and almost every line on the P&L moves. The volume curve bends, the channel mix shifts, the retailer behaviour changes, the finance projections rearrange. No other decision a retail business makes has that kind of leverage on revenue and margin together.
And yet, in most Indian retail brands under five hundred crore in revenue, the price is set the same way the year before. Match the competitor, add a margin, hope the volume holds. The conversation about price almost never starts with the demand curve, because the team has never built one.
What follows is what a working pricing approach looks like for an Indian retail brand. The diagnostic, the test, the channel decision, the six-week audit method.
Why pricing is hard for Indian retail
Three structural reasons that make pricing harder for Indian retail than the textbooks suggest.
Multiple channel realities. The same SKU runs at different prices in modern trade, traditional trade, ecommerce, and your D2C site. The retailers know it, the customers know it, your own team plays the channels off against each other. The pricing decision is not one decision, it is four decisions that interact.
Promotion-soaked history. The volume history you would use to estimate elasticity is full of overlapping schemes. You cannot tell the price effect from the promotion effect without doing real work to separate them.
Distributor incentives misaligned. The distributor wants the highest MRP, the longest credit, and the biggest scheme. None of those line up with the retailer's interest or the customer's. The price you publish is not always the price the customer pays.
The three pricing models actually used in India
Almost every Indian retail brand uses one of three approaches. Each has a place. Few are used deliberately.
Cost-plus. Take the landed cost, add a target margin, get the price. Simple, defensible, ignores the demand. The trap is that the resulting price is right for the seller and wrong for the buyer. Volumes underdeliver and the team blames the market.
Market-following. Look at the competitor's price, sit a rupee below, hope to win the basket. The trap is that the competitor priced the same way last year, so you are following somebody who was following somebody, and nobody is actually optimising. The race to the bottom is unintentional.
Value-based. Build a view on what the buyer is willing to pay, given the alternatives and the use case. Set the price to capture more of that. The right answer, almost always. Almost nobody does it because it requires data and judgement that the textbook does not supply.
What the demand curve actually looks like
The demand curve is the relationship between the price and the volume. It is not a textbook downward-sloping line. It bends. There is a sweet spot, a zone where the combination of price and volume produces the highest profit, and stepping outside the zone in either direction loses money.
The point of pricing is to find the sweet spot for each SKU in each channel. Not the lowest price. Not the highest. The one that gives you the most profit, after the customer behaviour responds.
You find the sweet spot by testing. You run a small price change on one SKU in one geography or one retailer chain, you watch the volume response over four to six weeks, and you read the curve. The first test is the hardest. After that, the method scales across the catalogue.
Pricing differently per channel
The single biggest unlock for most Indian retail brands is allowing the price to differ across channels by design. Today, in many brands, the price differs by accident. The team has not decided to do it, the channels have done it on their own.
The intentional version is harder but worth doing. D2C carries the brand price, premium positioning, full margin. Ecommerce carries a tactical promotional cadence because the platform demands it. Modern trade negotiates schemes that bring the effective price down to a defensible mid-tier. Traditional trade often holds the highest realised price because there is less price benchmarking, less direct competition on the shelf, and a stickier customer base.
What you decide is who you want to be on each channel. The pricing follows the positioning, not the other way around.
A six-week pricing audit, end to end
Week one, map the prices. Every SKU, every channel, the published price, the realised price after schemes, the margin at each. The map alone tells you things you did not know. Almost every audit we run uncovers SKUs being sold below cost in at least one channel.
Week two, pick a test SKU. One SKU, one channel, with stable history and minimal promotional overlap. The test runs a real price change (up or down) for four weeks and measures the volume response. This is the bit that requires discipline because the sales team will want to undo the test if early numbers look bad.
Weeks three and four, build the demand curve. From the test, plus historical data normalised for promotion effects, you build a price-volume relationship for the SKU. Generalise carefully to similar SKUs in the same category.
Week five, recommend. The recommendation is per SKU per channel, with the expected volume and margin impact stated honestly. Some recommendations will be to lower price (to gain disproportionate volume). Some will be to raise (because you have been leaving margin on the table).
Week six, ship the first round. Implement the most defensible recommendations first. The ones that are clearly margin-positive, with low channel-conflict risk. Hold the harder ones for a follow-up after the first round shows impact.
What tends to go wrong
The model is usually fine. The team usage is where the audit either lands or gets parked.
The sales team does not trust the result. Reasonable. The first time anyone sees a recommendation to raise a price on a slow-moving SKU, the gut says no. The fix is showing the test data, the comparable cases, and the downside guardrails. Trust is earned in the second and third recommendation, not the first.
The retailer pushes back. Real risk. The mitigation is to package the price change with a meaningful upgrade (a refreshed pack, a new size, a new occasion) so the retailer has a story to tell their buyer.
The team reverts after a quarter. Inevitable if there is no review cadence. The pricing decisions need to come back to a monthly review, where the actual volumes get plotted against the modelled volumes and the model gets updated.
What to do this week
Pick three SKUs that you think are priced wrong. Pull the volume history for the last six months. Pull the price every retailer is selling them at. Pull the margin at each price. The exercise alone usually surfaces a problem worth fixing in week two.
If you want help running the audit with a senior team that has done it in Indian retail many times, talk to us.