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Trust & CompanyHubble India Daily Gift Voucher Discount Rate Dataset
A daily file of every brand voucher listed on Hubble, with the brand, SKU and headline discount rate on each row. Five columns, nothing to parse.
Hubble and Gyftr carry largely the same brands at different rates. In the supplied samples, 28 of 50 brands were discounted differently on the two platforms on the same day — which is the single most useful thing this file tells you.
The file already exists, because this pipeline runs every morning whether you buy it or not. Most vendors start collecting after you order — which is why they quote a lead time. Here the most recent file is in your account within minutes of payment, with an API key issued at the same time.
What you get, in plain terms
Four things. This is a small, focused file — if you want product-level pricing, it is not this dataset.
Headline discount rate per brand
The rate as displayed, brand by brand. In the supplied sample these ran from 1.5% to 12% across 50 brands.
Directly comparable with Gyftr
Same brand list, same shape, so the two files join on brand and the rate gap becomes a column rather than a project.
Fewer blanks than the comparable feed
In the supplied samples Hubble showed a rate on 40 of 50 brands against Gyftr's 28 — worth knowing if coverage completeness matters to you.
However you want it
Direct download, REST API, Amazon S3, Google Cloud, Snowflake or SFTP. The API key comes with the dataset.
Fields included in this dataset
All 5 columns, in the exact order they appear in the file — taken straight from the sample, not from a brochure. The free sample ships with a data dictionary giving an example value for each one.
Sample rows from the real file
Real rows from the sample file, not an illustration. The free sample is 50 voucher SKUs with all 5 columns.
Coverage
Every brand listed on the Hubble marketplace, refreshed every morning.
| Brand category | Brands tracked | Typical discount band | Rate shown |
|---|---|---|---|
| Fashion & apparel | 368 | 6% – 12% | 84% |
| Food & grocery | 241 | 1% – 6% | 79% |
| Travel & mobility | 152 | 3% – 9% | 81% |
| Electronics | 131 | 1.5% – 5% | 72% |
| Beauty & wellness | 178 | 6% – 14% | 86% |
| Jewellery & lifestyle | 118 | 5% – 12% | 80% |
| Entertainment & dining | 194 | 4% – 11% | 83% |
| All other brands | 238 | 2% – 8% | 76% |
Only tracking your own brand and a competitive set? Send the brand list and we will price a narrower file. Tracking the same brands across Hubble and Gyftr together is the most common setup.
Historical data
The last 30 days come with the dataset. Beyond that we hold Hubble records from June 2025 onwards — enough to see how voucher rates moved through the festive quarter, which is when they move most.
Ask about historical dataNeed more data points?
We can extend this dataset beyond the standard 5 columns — the Gyftr rate joined onto the same row is the most requested addition, along with denomination-level rates and voucher validity terms.
Request custom fields“We were comparing the two platforms by hand in a spreadsheet every Monday. Getting both as files that join on brand turned a half-day job into a scheduled query.”
What people use this dataset for
Brands issuing vouchers
See what your own voucher is selling at, and whether the effective discount exceeds what your own channels are permitted to offer.
Competitive intelligence
Track competitor voucher rates day by day — they move faster and more quietly than shelf prices.
Corporate gifting and procurement
Compare effective rates across brands and platforms before committing a bulk purchase.
Fintech and rewards teams
Benchmark your rewards catalogue against the open voucher market.
About Indian gift voucher data
Gift vouchers are a large and lightly watched discount channel in India. A brand that will not cut shelf price will often allow its voucher to sell at six or eight percent below face value on a marketplace, and a customer stacking a card offer on top can land well below the brand's own promotional floor.
Why the discount rate is not the whole discount
The headline rate is only the first layer. comments carries payment-method offers — a card-specific rate, an e-Pay rate — which apply on top. A brand showing 8% headline with a further 7% on credit card is effectively discounting closer to fifteen percent for a customer who knows to combine them. Measuring only the headline understates the channel substantially.
Reading “Not Found”
discount is a text field and it sometimes reads “Not Found” rather than being blank. That means the rate was not displayed when the page was captured, usually because the voucher was temporarily unavailable. In the supplied sample it occurred on 22 of 50 rows. Filtering it out is correct; treating it as zero percent is not.
Why this pairs with the Hubble dataset
Gyftr and Hubble list largely the same brands at different rates. In our own comparison of the two samples, 28 of 50 brands were discounted differently on the two platforms on the same day. If you are a brand, that gap is a governance question. If you are a buyer, it is arbitrage.
Is collecting this data legal?
Collecting publicly visible product and price information is generally lawful in most jurisdictions. Actowiz collects only public pages, respects robots.txt and platform terms, holds no personal data, and aligns with GDPR and CCPA. We are ISO 9001 and ISO 27001 certified, and this dataset carries documented provenance so your legal team can review the source before you buy.
