Disclosure first, because it changes how you should read everything below. Atlas is ours. It is the Scout Data product we ship as List Builder, and we have an obvious interest in the outcome of this comparison. What we can offer instead of neutrality is specificity: BatchData’s pricing and product claims below are taken from its own public pages, the section on where BatchData wins is written seriously, and the test we propose at the end is one we could lose.
The useful framing is not “which vendor is better” — it is that these are two different purchases that happen to end at the same place. One sells you data. The other sells you a list. If you buy the wrong one for your team, the failure shows up as a project rather than as a bad file.
Two different purchases
BatchData is a data company. It publishes property, assessor, mortgage and transaction, permit, valuation and demographic datasets, plus skip tracing and enrichment, and it delivers them through APIs, bulk feeds and integration tooling. Its own coverage claim is 155 million properties across more than a thousand data points. The purchase you are making is capacity: a monthly allowance of records you can call against, which you then turn into something useful.
Atlas — the product we ship as List Builder — is a list product. You describe an audience: homes in this footprint, roof past a certain age, owner in place long enough, system old enough. It resolves each parcel to its current owner of record, attaches a phone matched to that person by name, scrubs against the federal do-not-call registry before delivery, and replaces numbers that go dead. Building and counting an audience is free; credits are spent on export. The purchase you are making is an outcome.
Neither is the sophisticated choice. A team with two engineers and a clear thesis about which houses convert will get more out of raw data than out of anyone’s finished list, and should buy raw data. A team whose bottleneck is that Monday’s file has to be dialable by Monday should not spend a quarter building a pipeline to save money on records.
What each hands you on day one
| Day one | BatchData | Atlas |
|---|---|---|
| What arrives | API credentials and a record allowance | An exportable, owner-matched list |
| Who assembles the audience | You, from datasets and your own logic | The product, from property signals you choose |
| Phone matching | Skip tracing and reverse skip tracing, sold as tiers | Matched by name to the owner of title, included |
| DNC handling | DNC status verification and litigator scrub in the tiers | Scrubbed before delivery, dead numbers replaced |
| Engineering required | Yes — integration, storage, selection logic | No, though the same graph is available via API |
| Commercial shape | Monthly record blocks, published tiers | Credits on export, quoted against volume |
The published BatchData rate card
As publicly advertised on 4 September 2026, BatchData sells three separate product lines, each in monthly record blocks, with monthly or annual commitment. Entry tiers: property data at $1,000 a month for up to 100,000 records; skip tracing at $2,000 a month for up to 100,000; reverse skip tracing at $3,000 a month for up to 100,000 matched records. Higher tiers scale to 3,000,000 records a month.
Pricing on this page is as publicly advertised at the time of writing — confirm current pricing with each vendor, and with our sales team for Scout Data.
Two features of that card matter more than the headline figures. The lines stack: property data and skip tracing are separate purchases, so a team that needs both at 100,000 records a month is looking at both subscriptions rather than one. And the forward and reverse skip-tracing tiers are metered differently — reverse is described as paid per matched record, forward as an allowance of traces. That distinction, and the per-record arithmetic it implies, is worked through in BatchData pricing.
Atlas is quoted against your list profile rather than published as a card, which is a real disadvantage for anyone trying to compare on a website at 11pm. We would rather say that plainly than pretend the comparison is symmetrical.
Where the two genuinely diverge
Strip out the packaging and there is one substantive difference: what decides which rows exist in the first place.
Buying data means you decide. You have every filter the datasets support — ownership, mortgage, valuation, assessor attributes, demographics — and whatever thesis you can express in code. If your thesis is good, that is an advantage nobody can buy off the shelf, because it is yours. If your thesis is “owner-occupied single family, equity over 40%,” you have built the same list as everyone else who bought the same datasets, and your reps are dialling the same houses.
Atlas takes a position instead: that the rows worth dialling are the ones where something recently changed. Storm footprints, more than a million new permits a week, roof and system age, ownership changes, time in home. That is an opinion about home services demand, not a neutral capability, and if you disagree with the opinion you should not buy the product. It is also the part that is hardest to replicate from raw datasets, because the signals arrive continuously rather than sitting in a monthly file.
When BatchData is the better buy
Four cases, written without hedging:
- You are building a product. If property data is going into something you sell — a portal, a valuation tool, a lender workflow — you need a data supplier with delivery options and an API contract, not a list vendor. Buy the feed.
- Your targeting thesis is your edge. Teams that have worked out something non-obvious about which houses convert should own that logic. A finished list product will always encode somebody else’s view.
- You need datasets outside our lane. Assessor detail, mortgage and transaction history, pre-foreclosure, demographics at depth — these are BatchData product lines and not what a home-services list product is optimised for.
- You want a published price before a conversation. Their tiers are on a public page. Ours are not. For some buyers that settles it, and it is a fair thing to weigh.
The wider field around that decision — including what switching away from a data API actually costs — is in BatchData alternatives, and the platform vendors that sit between the two models are compared in best skip tracing software.
A note on the Batch names
If you have quotes or contracts with “Batch” on them, confirm which entity you are dealing with before comparing anything: the brand family was reorganised in 2025 and the names no longer identify one company. We untangled it in BatchLeads vs BatchData rather than repeating it here.
How to settle it
Do not settle this on a comparison page, including ours. Take five hundred real addresses from a market you already work. Run them through whatever BatchData configuration you would actually deploy, and export the same territory from Atlas on the free trial. Dial both with the same script and the same reps in the same week, and count right-party connects — then divide total spend by that count for each. The formula and the traps are in our skip tracing cost calculator.
If the data feed plus your own logic wins on that number, buy the feed. We would rather you ran the test than took our word for it, because the buyers who run it stay.
Frequently asked questions
Are Atlas and BatchData competitors?
Partly, and pretending otherwise would be silly given we make one of them. They overlap on the outcome — a homeowner record with a phone number attached — and differ on almost everything about how you get there. BatchData sells data by the monthly record block, primarily through APIs and bulk delivery, for teams that will do their own selection and assembly. Atlas sells the assembled, owner-matched list. Teams with engineers frequently prefer the former.
Can I buy a small amount of BatchData?
Its published plans start at a monthly commitment rather than a small pay-as-you-go balance — the entry tiers are sized in blocks of a hundred thousand records a month. That is a normal shape for infrastructure pricing and it means the first question is not “what does a record cost” but “can I commit to a monthly block”. The tiers and the per-record arithmetic behind them are in BatchData pricing.
Which one is better for a solar or roofing floor?
It depends on whether you have engineers and a point of view about targeting. If you do, buying raw data and building your own selection logic gives you something nobody else has. If your constraint is that Monday’s file has to be dialable and nobody on staff writes code, a finished list is the purchase. We build one of those, so weigh that — but the test is the same either way: right-party connects per dollar on your own records.