A client needing to see the real offer stack behind competitor prices on India's two largest marketplaces, every day.

Use Case

Competitor price, coupon and bank-offer tracking

Region

India

Sources

Amazon.in, Flipkart

Number of sources

Coupons & Bank Offers

SKU by SKU, Every Day

Prime and Plus Badges

Listing by Listing

Contact Sales

Key Takeaways

Actowiz is delivering Amazon and Flipkart coupon and bank offer tracking for an Indian home-products brand. The daily feed covers about 372 competitor and own SKUs, starting on Amazon.in and extending to Flipkart. Each record joins MRP, selling price, coupon, bank-offer terms, Prime or Plus badges, seller and stock status, with an API delivery option under review.

What did the client need?

On Amazon and Flipkart, coupons and card offers often decide what a shopper actually pays, and they change daily. List prices alone were not enough for the brand's pricing team.

They wanted a daily file for roughly 372 SKUs showing competitor prices, coupons and bank offers, starting with Amazon, then Flipkart, plus Prime-related listing data. The client approved the scope on 24 September 2026 and the project is now at kickoff. [Add kickoff date]

What made this hard?

Changing layouts – coupons, bank offers and badges sit in different blocks on each marketplace.
Bank offers are conditional – each offer depends on the bank, card type and a minimum transaction value, so the text must be split into clean fields.
Personal eligibility is not public – what one shopper gets depends on their card and account, so only offers shown publicly on the listing can be captured.
Daily cadence – 372 SKUs on two marketplaces every day leaves little room for failed runs or late files.
Matching across platforms – the same product carries an ASIN on Amazon and an FSN on Flipkart, so a mapping table is needed.

How did Actowiz solve it?

Actowiz designed a phased daily pipeline that captures the public offer stack in a single schema.

Approach

Amazon first, Flipkart next – Flipkart is added on the same schema, so reports stay comparable.
SKU mapping table – ASINs and FSNs are linked to the brand's own product list, covering both its items and competitor items.
Offer parsing – coupon text is turned into a value and type, and bank-offer text is split into bank name, card type and minimum transaction value.
Badge and seller capture – Prime or Plus badges and the business seller name are recorded as shown on the listing. [Confirm Prime-related fields with delivery team]
Daily QA – runs are checked for missing SKUs and empty prices before delivery.
Flexible delivery – a daily file is the base option, with an API under discussion. [Confirm delivery format / API]

Data Attributes / Fields

Field	Description
asin / fsn	Amazon or Flipkart product identifier
product_title / brand	Listing title and brand name
mrp / selling_price	Listed MRP and current selling price (INR)
coupon_text / coupon_value	Coupon wording and parsed value
bank_offer_text / bank_name	Bank-offer wording and issuing bank
card_type / min_txn_value	Eligible card type and minimum transaction value
prime_badge / plus_badge	Prime (Amazon) or Plus (Flipkart) badge shown
seller_name	Business seller on the listing
availability	In-stock or out-of-stock status
scrape_date	Date the record was captured

What were the results?

The project is at kickoff, so results below are expected outcomes to be confirmed after implementation and initial data validation.

Effective price view – the pricing team can compare competitor list prices with applicable coupons and bank card offers to understand the effective purchase price.
Daily promotion alerts – new, updated or withdrawn coupons and bank offers can be identified through daily monitoring, supporting timely promotional analysis.
Two marketplaces, one format – Amazon and Flipkart product and pricing data can be standardised into a common schema once phase 2 goes live.
Ready for automation – the structured schema supports automated file-based or API delivery, subject to the final integration requirements.

Project at a Glance

Metric	Value
Use Case	Competitor price, coupon and bank-offer tracking
Region	India
Sources	Amazon.in (phase 1), Flipkart (phase 2)
Metrics	MRP, selling price, coupons, bank offers, Prime or Plus badge, seller, availability
Reconciliation / Method	ASIN and FSN mapping to the brand SKU list, offer-text parsing, daily QA
Cadence	Daily, about 372 SKUs
Output	Daily file, API option under review [Confirm delivery format / API]

Client Feedback

“Actowiz Solutions is helping us build a clearer picture of competitor pricing across Amazon India and Flipkart, including product prices, coupons, and bank offers. This structured daily tracking will help our team compare effective selling prices, monitor promotional changes, and make more informed pricing decisions as we expand coverage across marketplaces.”

— E-commerce Manager, Indian Home Products Brand

Frequently Asked Questions

Q: Why track coupons and bank offers, not just prices?

A: Coupons and card offers change the final price, so tracking them shows the real competitive gap. Our festive sale price war study shows why this matters.

Q: Is any personal data collected?

A: No. Only public listing data is captured, in line with India's DPDP framework (EY overview). Site terms are respected and legal review is recommended.

Q: Which seller details are included?

A: The business seller shown on the listing. Marketplaces must display seller details under the E-Commerce Rules 2020. For seller checks, see our unauthorised seller playbook.

Q: Can Flipkart be tracked on its own?

A: Yes. See our Flipkart data scraping services.

Q: Is there a ready-made Amazon India dataset?

A: Yes. The Amazon India weekly pin-code dataset covers price and availability by location.

Need Daily Marketplace Offer Tracking?

Share your SKU list, marketplaces and preferred format, and we will scope a daily feed. Visit actowizsolutions.com to discuss your data requirement.

Hear It Directly from Our Clients

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