actowiz

  Introduction Almost every price intelligence programme that disappoints does so for the same reason, and it is not collection difficulty. It is that prices were compared before products were matched. This guide covers the five layers of a working programme — matching, collection, normalisation, metrics, delivery — what each actually requires, the failure modes that quietly produce wrong numbers, and how to scope a first phase that proves something. What Price Intelligence Is, and What It Isn't Price intelligence is the continuous measurement of your price position against competitors, at the level of individual products, in each market where you compete. It is not a price feed. A file listing competitor prices is an input, not an output. The intelligence is in knowing that these two products are the same product, that this comparison holds in this city, and that this gap changed last Tuesday. The distinction matters commercially because the market sells the input and the buyer ne...

  Why the Distinction Matters Before Anything Else Grocery is unusually broad as a data category. It spans full-range supermarkets, discounters, wholesale clubs, quick commerce, and online-only grocers, across markets where the same brand appears in different pack sizes, languages and category structures. A request phrased as "grocery product data from these retailers" is compatible with a one-time 50,000-product catalogue pull and with a thrice-daily price tracker on 200 SKUs. Those are different projects by an order of magnitude in every dimension. The four shapes below cover most real requirements. The useful question at the start of a grocery engagement is not "which retailers" — it is which of these four is this. Type 1 — Catalogue Build The question it answers: what exists, and at what price, right now? Shape: once-off. A complete or near-complete extraction of a retailer's catalogue across defined categories, from one fixed location, with a broad attribut...

  Introduction Quick commerce prices are location-resolved and change through the day, which means a single national price check tells you almost nothing. Effective tracking requires collecting per city (or per pincode), per platform, multiple times daily, with pack-size normalization so cross-platform comparison actually works. This guide covers what to track, how often, the four failure modes that ruin q-commerce datasets, and how to size a first pilot. What Is Quick Commerce Price Tracking? Quick commerce price tracking is the automated collection of product price, discount, availability and listing-position data from 10-to-30-minute delivery platforms — in India, principally Blinkit, Zepto, Swiggy Instamart, BigBasket and Flipkart Minutes. Unlike conventional marketplace monitoring, it must be performed per serviceable location, because the catalogue a shopper sees is determined by the dark store assigned to their address. The practical consequence: there is no such thing as "...