A client needing daily, accurate gift-card and cashback offer data to power in-app rewards

Use Case

Gift-card, voucher and cashback offer tracking

Region

India

Sources

Payment-app voucher stores, e-commerce gift-card stores, voucher and rewards apps, cashback sites, brand e-voucher pages

Number of sources

8 public platforms

Key metric 1

Discount and cashback % per brand and denomination

Key metric 2

Cashback caps and validity windows

Key metric 3

Daily offer changes (new, changed, expired)

Contact Sales

Key Takeaways

Actowiz built cashback data tracking for a fintech rewards app in India across 8 public gift-card, voucher and cashback platforms. Every day it captures each brand's denomination, discount, cashback percentage, cap and validity from public offer pages, normalises them into one schema and pushes only the changes through an API, so the app shows current offers instead of expired ones.

What did the client need?

The client is a fintech rewards app in India. Members redeem points for gift cards and vouchers from hundreds of brands.

The product team needed each brand's offer on every major platform: discount, extra cashback, cap and validity. Manual checks could not keep up, and stale offers caused failed redemptions and support tickets.

They asked for daily cashback data tracking across 8 public platforms, delivered by API in a format their offer engine could read without manual clean-up.

What made this hard?

Eight platforms, eight layouts. Payment-app voucher stores, e-commerce gift-card stores, voucher marketplaces and cashback sites each organise brands, denominations and terms differently.
Offers change daily. Discounts, cashback rates and caps move with campaigns, often without any notice on the page.
Terms hide in small print. Caps, minimum denominations and validity windows sit in terms text or pop-ups rather than in clean fields.
Same brand, different names. One brand can appear under several spellings, sub-brands or category labels across platforms.
Public pages only. The scope excluded anything behind a login, member-only pricing and any personal or account data.

How did Actowiz solve it?

Actowiz built the cashback data tracking pipeline from platform collectors, a shared schema and a daily API change feed.

Approach

Platform-aware collection. Each platform got its own discovery logic (brand search, category browsing or deep-scroll listings), limited to publicly visible offer pages.
Terms parsing. Cashback percentages, flat amounts, caps and validity dates were extracted from offer text and stored as separate, typed fields.
Brand and denomination matching. A brand dictionary mapped spelling variants to one brand ID so the same gift card could be compared across all eight sources.
Validation rules. Records with missing denominations, impossible discounts or expired dates were flagged, not sent.
Change detection. Each run was compared with the previous one to mark offers as new, changed or expired.
API delivery. A push API sent daily changes and a pull API served on-demand lookups, both as structured JSON.

Data Attributes / Fields

Field	Description
brand	Normalised brand name with a stable brand ID
platform	Source platform type and name where the offer was seen
denomination	Face value of the gift card or voucher in INR
discount_pct	Instant discount on the voucher price, as a percentage
cashback_pct	Cashback rate offered on top of, or instead of, the discount
cap	Maximum cashback or discount amount per transaction, where stated
validity	Offer start and end dates as shown on the page
offer_status	New, changed, active or expired versus the previous run
captured_at	Timestamp of collection (IST)
terms_url	Link to the public terms or offer page used as evidence

What were the results?

One comparable view. Cashback data tracking let the app compare a brand's gift-card offer across all eight platforms in one table.
Fresher offers in-app. New campaigns and expired offers were reflected after the next daily run rather than after a manual check.
Fewer redemption issues. Validity and cap fields helped the team pull expired or capped offers before members saw them.
Less manual work. The team moved from manual spot checks to reviewing flagged exceptions.

Project at a Glance

Metric	Value
Use Case	Cashback data tracking for gift cards and vouchers
Region	India
Sources	8 public gift-card, voucher and cashback platforms
Metrics	Denomination, discount %, cashback %, cap, validity, offer status
Reconciliation / Method	Brand dictionary, denomination matching, validation rules, run-on-run change detection
Cadence	Daily, with on-demand pull
Output	JSON via push and pull API; several hundred gift-card and voucher products, tens of thousands of offer records a day

Client Feedback

“Actowiz delivered a daily feed that keeps our rewards app current — we stopped showing expired offers and started comparing every brand across all eight platforms in one place.”

— Product Lead, Fintech Rewards App

Frequently Asked Questions

Q: What is cashback data tracking?

A: It is the regular collection of cashback rates, caps and validity dates from public offer pages, so a business can see which brand offers are live, how generous they are and when they end.

Q: Which platforms can be covered?

A: Public gift-card stores, voucher marketplaces, cashback sites, payment-app voucher sections and brand e-voucher pages. Pages that need a login or show member-only pricing are excluded.

Q: How often can offers be refreshed?

A: Daily suits most rewards apps; higher frequency is possible during campaigns, subject to each site's terms.

Q: How is the data delivered?

A: As structured JSON through a push or pull API, or as CSV files, with only changed offers flagged in each run.

Need gift-card cashback offer data?

Actowiz can scope a cashback data tracking feed for your brands and platforms, starting with a free sample. Visit actowizsolutions.com to discuss your data requirement.

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