Scraping Tata CLiQ is mostly maintenance work. We build the crawler, run it and keep it running. When the front end changes, repairing it is our job, not yours. You choose the scope - a category, a brand, a competitor set, a fixed list of product codes - and the frequency, from a single snapshot to daily runs.
Delivery is CSV, JSON, XLSX, a database drop, or an API endpoint you poll. Every row carries a run timestamp, so a price history is a series and not a heap. We collect public product and pricing data only, and no customer data.
A standard Tata CLiQ scraper run returns one row per sellable item, keyed on the product code carried in the URL. Product pages follow the shape /product-name-slug/p-mp plus a fifteen-digit code, and Tata CLiQ Luxury uses the same MP code format on its own host, so rows from both storefronts join cleanly.
Pack sizes and multipacks are separate items with separate codes. We have seen a single product title carry several distinct MP codes, so deduplication on a Tata CLiQ data set works on brand, title and pack size together, not on the code alone. We tell you which rule was applied instead of quietly merging rows behind your back.
Tata CLiQ was built as a phygital marketplace. Sellers onboard their physical stores onto the platform, an order can be routed to the store nearest the customer and shipped from there, and a return can be walked into a store. Customers can also buy online and collect in store, a mode Tata CLiQ calls QUiQ PiQ. Croma, Westside and Titan are among the Tata retail names that have taken part in this model.
For a crawl this has one blunt consequence. Availability and the delivery promise are not a single warehouse fact. They resolve against a PIN code, and the standard, express and collect-in-store options each surface differently depending on the PIN code, the item and the seller's own policy. A single-location run tells you whether an item exists. It does not tell you whether it is buyable in Bengaluru. Where city-level coverage matters, we run the same product set against a list of PIN codes you supply and return one row per product and PIN code.
Bank offers and EMI blocks behave the same way. They are conditional, they rotate, and they are why two shoppers can see different effective prices for one item. We record them as observed at the run timestamp rather than presenting them as fixed attributes.
Tata CLiQ is an Indian online marketplace operated by Tata Unistore, part of the Tata Group. It opened in 2016 and moved fully under Tata Digital in December 2022. The main storefront runs on tatacliq.com and covers clothing, footwear, jewellery, watches, accessories, beauty, home and electronics.
The part that matters for data work is the seller policy. Tata CLiQ runs a curated marketplace: listings come from brand owners, from their authorised distributors, or from approved sellers who have filed a brand authorisation certificate. Brand owners register with a trademark certificate instead. At launch the company described procuring either from brands or through their approved retailers only, cutting out unauthorised wholesalers.
That one policy changes what the catalogue means. On an open marketplace the brand field is a string a seller typed, so brand attribution has to be treated as a claim and cleaned before use. Here the brand attached to a listing has passed an approval step. For anyone watching their own label, or a competitor's, that is the difference between a dataset you argue about and a dataset you act on.
Tata CLiQ also sells through separate properties. Tata CLiQ Luxury sits on its own host, luxury.tatacliq.com, carrying luxury and bridge-to-luxury labels. CLiQ Palette is the beauty vertical. Each has its own front end and needs its own crawl configuration.
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Brand and price policy monitoring. Three prices are in play on one Indian product page: MRP, the legal ceiling printed on the pack; the selling price charged today; and the effective price once bank offers and EMI schemes are applied. A feed carrying only the selling price has lost the denominator, so the discount cannot be checked and any comparison against your own pricing policy is guesswork. We keep MRP and selling price as separate columns.
Authorised channel checks. Because listings run through brand approval, a Tata CLiQ price sitting under your floor points at a partner you hold a contract with. MAP-style enforcement in India is contractual, not statutory, so the platform will not police it for you. The value of the data is that it names a counterparty you can call.
Assortment tracking. Which of your codes are listed, which went dark, which competitor lines appeared this month, and where you land in a category listing.
Sale-window analysis. Capturing before, during and after a sale shows what the cut actually was against MRP, not against a price that moved quietly the week before.
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If you sell online, run a marketplace, or advise e-commerce clients, you already know why eBay matters: it’s one of the few places where big retailers compete side by side with thousands of small merchants and private sellers.
E-commerce teams do not just need “some” competitor data anymore. They need a continuous stream of real prices, discounts, stock levels, reviews, and seller behavior from the platforms that actually shape their markets.
Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce.
ScrapeIt is a managed web scraping agency. Not a library, not a self-serve tool. You describe the fields and the schedule, we hand over clean data and keep it arriving.
Start by telling us which part of Tata CLiQ you need: one brand, one category, both storefronts, or a fixed product list. We come back with a sample extract from live pages so you can check the columns before anything is committed.
No. Tata CLiQ publishes no open catalogue or pricing API that a buyer can sign up for. A seller-side integration path does exist, but access is switched on by a Tata CLiQ account manager against a Seller ID, and it exposes that seller's own listings, inventory and orders rather than the wider public catalogue. Third-party order management platforms connect through that same seller channel. If you need catalogue or competitor pricing across brands, extraction from the public pages is the route available.
Yes. Tata CLiQ Luxury runs on luxury.tatacliq.com, a separate host with its own robots.txt and its own sitemap. It uses the same MP product code format as the main storefront, so results from both can be joined on the code. It is a separate crawl configuration, and we set it up inside the same project.
MRP is India's maximum retail price. Under the Legal Metrology (Packaged Commodities) Rules it has to be declared on the pack, inclusive of all taxes, and selling above it is an offence. It is a legal ceiling, not a suggested price, and every discount percentage on the site is computed against it. Without an MRP column you cannot verify a discount claim or measure real price movement, because the headline percentage shifts when either number moves.
Not the product data. Checked on 31 August 2026, a default command-line request to the homepage, to sitemap.xml and to a category path each returned HTTP 403. Even the archived HTML of a product page is a small React shell: it carries site-level structured data describing the website and the organisation, with no product-level markup, no canonical link and no preloaded data object. Title, MRP, price, seller and ratings all arrive after client-side rendering, which is why we run a rendering pipeline instead of a simple fetch.
Prices and discount badges move continuously and step sharply inside named sale windows such as The Big CLiQ Sale and the festive Moments that CLiQ period. Range rotates as well. In the sitemap index captured on 20 January 2026, apparel partitions dominated the catalogue, and fashion assortment turns over by season. Most clients settle on daily runs for a price watch list and weekly or monthly runs for full category sweeps. We size the schedule to the decision you are making with it.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
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