Retail pricing and merchandising analytics

Deciding what to charge and what to stock, store by store and size by size

It is October. A clothing chain with 200 stores must decide how many kurtas to order for Diwali, for each store and in each size. After Diwali, it must decide when to cut the price on the ones left over, and by how much. Meanwhile, the same kurtas are on sale on the big marketplaces, where rivals change their prices many times a day.

What to stock and what to charge are a retailer's two hardest decisions. The software that makes them does five jobs:

Forecasting

predicting how many of each item will sell.

Merchandise planning

deciding which products to carry each season.

Allocation

splitting the stock across the stores.

Pricing

setting prices, including markdowns, the price cuts that clear unsold stock.

Promotions

planned offers, such as "buy two, get one free".

The Diwali kurtas through the five jobs: forecasting how many will sell, planning which kurtas to carry, allocating them to each store and size before Diwali, then pricing, including the markdowns, and promotions during and after it.

This software relies on machine-learning models more than most retail software does. Its buyers are retailers, and the brands that sell through them. Several of its companies were founded in Bengaluru.

Every company named here has posted software engineering jobs in India. Famous companies that don't actively hire software engineers in India are left out.

A bigger version of the same planning covers how much to make and move across a whole supply chain. It is covered in Market Segment 30.1, Supply chain planning software (in Industry Vertical 30, Supply chain and logistics). Blue Yonder and o9 Solutions, two companies that sell it, are covered there.

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What this section holds

What this section holds

Planning and pricing for the retailer. Take the clothing chain and its Diwali kurtas from the start of this Market Segment.

Impact Analytics

sells retailers forecasting, merchandise planning, allocation, pricing and promotions, all from one platform. Much of it is built in Bengaluru. It has engineers there, and the most job postings in this Market Segment.

Revionics

now part of Aptos, and Hypersonix Inc sell price and promotion optimisation to retailers: software that picks the price and the offer most likely to earn the most. (More on Aptos in Market Segment 27.3, Retail checkout and store systems.)

PriceEasy AI

sets the prices of fuel and convenience-store goods.

Selling on the marketplaces, for the brand. A brand that sells on Amazon and other marketplaces faces the same questions, on someone else's shelf.

CommerceIQ

manages a brand's sales on Amazon and other marketplaces. It covers the digital shelf: how the brand's products appear on the marketplace, from the photos and ratings to where they show up in search. It also covers retail advertising, the ads a brand buys inside the marketplace, and the analytics. CommerceIQ has engineers in Bengaluru. Its advertising work also appears in another Market Segment. (More on it in Market Segment 34.1, Ad buying platforms (DSPs) and ad networks, in Industry Vertical 34, Adtech.)

Watching the competition

Anakin, Wiser Solutions and Paxcom

now part of Paymentus, watch competitors' prices and product listings across the web. Wiser Solutions has engineers in Kolkata.

Dcluttr

tracks brands' prices, discounts and advertising on India's quick-delivery apps, the apps that deliver groceries in ten minutes. The industry calls this quick commerce. Dcluttr has engineers in Delhi. (More on those apps in Market Segment 28.1, Food and grocery delivery apps, in Industry Vertical 28, Foodtech and quick commerce.)

The data behind the decisions. Two companies covered mainly in other Market Segments bring the data these decisions rest on:

Circana

sells retail sales data: what sold, where and at what price. It has engineers in Bengaluru and Pune. (More on it in Market Segment 8.3, Market research and market intelligence providers, in Industry Vertical 8, Analytics and data providers.)

dunnhumby

sells customer science to grocery chains: the analysis of what each shopper buys, read from loyalty-card data. It also sells retail advertising. It has engineers in Delhi. (More on it in Market Segment 13.7, Loyalty and rewards platforms, in Industry Vertical 13, Martech.)

Who helps decide what to stock and what to charge: Impact Analytics, Revionics, Hypersonix Inc and PriceEasy AI plan and price for the retailer, CommerceIQ sells on the marketplaces for the brand, Anakin, Wiser Solutions, Paxcom and Dcluttr watch the competition, and Circana and dunnhumby bring the data.

The price set by a model for each store and hour.

Retail prices used to be set by category managers, the people in charge of one kind of product, working in spreadsheets. Now models set them for each store, each hour and against every competitor. The quick-delivery apps, where prices change all the time, have made that speed necessary. Regulators now ask whether prices set by models will become prices set for each customer. The industry calls that personalised pricing.

That is how the Diwali kurtas get planned and priced. A forecast decides how many go to each store, a model decides when to cut the price, and other software watches what rivals charge.

Who they hire

Who these companies hire, and for what, is on What retail tech companies hire for.

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