We do not publish price tables for this market. Rates move, they are negotiated, and a figure quoted in an article gets copied for years after it stops being true — which is how most of the "GST leads price" content online became useless. What does not change is the structure of the pricing, and structure is what determines whether a quote is good.
This guide covers the four models in use, the contract terms that move real cost more than the headline number does, and the arithmetic to run before signing anything.
The four pricing models
Per-record
You buy a defined number of rows. Simple, and the easiest to compare superficially — which is why it is the most commonly quoted and the most commonly misleading.
- Watch: whether the count is GSTINs or unique businesses. Multi-state registrations inflate GSTIN counts substantially.
- Watch: whether records with empty contact fields count toward your allowance. They usually do.
- Suits: one-off campaigns with a fixed, known target list.
Subscription with a credit allowance
A monthly or annual fee including N record exports, with overage priced separately.
- Watch: whether unused credits roll over. Usually not.
- Watch: the overage rate, which is frequently several times the effective included rate.
- Watch: whether viewing a record consumes a credit or only exporting does.
- Suits: continuing prospecting with roughly predictable monthly volume.
Territory or filter licence
Unlimited access within a defined scope — a state, a set of districts, an activity category.
- Watch: how scope changes are priced mid-term. Adding a state is a renegotiation in most contracts.
- Watch: whether "unlimited" carries a fair-use ceiling in the terms.
- Suits: regional teams with a stable territory.
API metered
Priced per call or per query, sometimes with tiered volume commitments.
- Watch: whether failed lookups and empty results bill.
- Watch: rate limits against your actual burst pattern, not your average.
- Watch: cache permissions — if you may not store results, your metered cost is far higher than modelled. See the API guide.
- Suits: verification-at-point-of-use and CRM enrichment workflows.
The six terms that decide real cost
The headline number is rarely where the money is.
| Term | Question to ask | Why it moves cost |
|---|---|---|
| Deduplication key | GSTIN or PAN? | GSTIN counts can exceed PAN counts materially |
| Empty-field billing | Do rows with no phone/email consume allowance? | At 30% fill, you may pay for 3× what you can use |
| Export limits | Rows per export, exports per period, format | Caps can make a large allowance unusable in practice |
| Usage rights | Internal only? Resale? Client work? Retention period? | Agencies get caught here constantly |
| Refresh | Are updates included or a new purchase? | Data decays; if refresh is extra, annualise it |
| Term & exit | Minimum term, auto-renewal, notice period, refunds | A twelve-month lock on unmeasured data is the expensive mistake |
Buy the shortest term first
You cannot evaluate a data product from a sample alone — you need to run it through a real sales motion for a few weeks. Take the shortest term available even at a worse unit rate, measure, then negotiate the annual deal from a position of evidence. Vendors discount annual commitments precisely because the commitment is worth more to them than the discount costs.
Cost per usable record
This is the only number worth comparing across quotes.
usable records = total records
× contact fill rate
× (1 − bad contact rate)
× filter relevance
× (1 − duplicate rate)
cost per usable record = total cost ÷ usable records
Worked through on a hypothetical ₹30,000 for 20,000 records — ₹1.50 per row on the invoice:
| Step | Multiplier | Remaining |
|---|---|---|
| Delivered records | — | 20,000 |
| Contact fill rate 35% | ×0.35 | 7,000 |
| Bad or unreachable contacts 20% | ×0.80 | 5,600 |
| Relevant to your actual filter 60% | ×0.60 | 3,360 |
| Duplicates across the file 10% | ×0.90 | 3,024 |
| Cost per usable record | ₹9.92 |
A 6.6× difference between the invoice rate and the real rate. The multipliers are illustrative — you must measure your own from a sample — but the shape is typical, and the ranking between two quotes flips regularly once this is applied. The measurement procedure is in the B2B data quality checklist.
Then take it one step further: divide by your expected contact-to-meeting rate to get cost per meeting, and compare that against your other channels. Data that looks expensive per row is often the cheapest meeting you can buy, and cheap data is often the most expensive.
What legitimately makes one product cost more
Higher prices are sometimes justified. These are the differences worth paying for:
- Lower lag. Genuinely faster collection is operationally expensive to run. If your segment is timing-sensitive, it converts.
- Higher, verified fill rate. Contact verification costs real money and shows up directly in usable-record arithmetic.
- Documented provenance per field. This has compliance value that does not appear on the invoice and appears sharply during a due-diligence review or a complaint.
- API and CRM integration. Removes recurring manual labour that nobody costs but everybody pays.
- Correction and removal workflow. A provider who processes a deletion request properly is protecting you as well as themselves — see the DPDP checklist.
And what does not justify a premium: record counts, "AI-powered" as a description of a database, accuracy percentages with no stated method, and any claim of government verification on contact fields.
Getting comparable quotes
- Write your filter as one sentence and send the identical sentence to every provider.
- Request a sample against that exact filter, not a generic one.
- Ask each for the same six-term table above, in writing.
- Measure fill rate and lag yourself from the samples.
- Compute cost per usable record for each.
- Ask for the shortest available term.
- Re-measure at renewal — data products degrade quietly, and renewal is your only leverage point.
Providers to include will depend on your buyer population — the category breakdown is in where to buy B2B leads in India, covering Zauba Corp, Tofler, Probe42, Apollo.io, Lusha, FinScreener and others. FinScreener is built by the team publishing this site — see our disclosure.
Common questions
What should GST lead data cost per record? There is no defensible universal figure, and anyone quoting one is describing their own product. Compute cost per usable record for your filter and compare quotes against each other.
Is a free sample enough to evaluate? For fill rate, lag and format, yes. For conversion, no — that needs a real campaign, which is the argument for a short first term.
Why do quotes for the same thing vary so much? Different deduplication keys, different fill rates, different definitions of "new", different usage rights. Normalise all four before concluding one is expensive.
Should I pay more for verified phone numbers? If verification is genuinely performed and dated, usually yes — it removes cost from the most expensive part of your funnel, which is rep time. Ask what "verified" means and when it was done.
Are annual contracts worth the discount? After you have measured, often. Before you have measured, no discount compensates for being locked to data you have not tested against your funnel.