Do you charge per seat?

No. You buy credits and the whole team draws on the same balance. Adding a rep does not add a licence fee, which is usually the single biggest cost difference against conventional sales-intelligence tools.

Can this replace our existing contact database?

For many teams, yes — particularly those pulling a few thousand contacts a month, where per-result pricing beats an annual seat contract. Teams pulling hundreds of thousands should compare against a bulk agreement. The per-result price makes that calculation straightforward.

How do we avoid burning credits on bad-fit leads?

Filter hard before you collect, then score before you enrich. Narrow filters return fewer results and therefore cost less, and running AI scoring at two credits per row before spending five per message keeps the expensive step off the wrong people.

What about deliverability?

Filter Leads Finder to verified email status. It returns a smaller list with materially better deliverability, which matters more than raw volume if you are protecting a sending domain.

HomeSales Teams

Fill your pipeline from any platform.

SDRs and AEs use VoxScrape to build targeted prospect lists, enrich contacts, and identify in-market buyers — all without leaving one dashboard.

Get started →See pricing

Why sales teams use VoxScrape

Sales teams do not have a data problem so much as a time problem. The information needed to build a good prospect list is public and available; assembling it is what eats the week. A rep who spends Monday building a list has four days to sell, not five.

VoxScrape collapses the assembly step. Describe the buyer, get the list, enrich it, score it against your ideal customer profile, and start the sequence — in one place, with one credit balance, without a seat licence per rep.

The result is not more leads. It is the same reps spending materially more of their week in conversations rather than in tabs.

Who this is for

SDRs and BDRs who own list building as well as outreach, and feel the tradeoff between prospecting volume and personalisation quality every single day.

Account executives working defined territories who need to know which accounts are in-market now rather than which merely fit the profile.

Sales leaders carrying a pipeline number who are tired of paying per seat for a database that goes stale between renewals.

Sound familiar?

Manually building lists eats hours per rep, per week.

Why it happens: List building is invisible in pipeline reporting, so it never gets optimised. A rep spending six hours a week in LinkedIn tabs and spreadsheets loses roughly a full selling day, and nobody sees it in the numbers.

What changes: A filtered Leads Finder run returns a few hundred matching contacts in one pass at one credit each. The six hours becomes a few minutes, and what the rep does with the recovered time is visible in pipeline.

Enrichment tools charge per contact regardless of data quality.

Why it happens: Seat licences and per-contact pricing bill for access, not outcomes. You pay the same whether a record is current and complete or stale and half-empty, which means the vendor carries none of the quality risk.

What changes: Credits are consumed per result actually returned. A run that finds nothing costs nothing, a failed run is refunded automatically, and results are capped at the hold you authorised — so you never pay for data you did not receive.

Buying signals on Reddit and Twitter go unnoticed.

Why it happens: The window between someone publicly describing a problem and choosing a solution is often days. Nobody on the team is watching those channels continuously, so by the time anyone notices, the evaluation has moved on without you.

What changes: Reddit and Twitter monitoring runs on a schedule at one to three credits per result, and AI Intent Detection scores each post. The team reviews a short ranked list of in-market conversations rather than a firehose.

What a week actually looks like

Monday morning starts with a filter rather than a search. Leads Finder returns 200 contacts matching the territory definition — job title, seniority, headcount band, country — in a single run at one credit each.

AI Lead Scoring ranks all 200 against the ICP profile saved in the account. Anything below a six is deprioritised immediately, which typically removes half the list before a rep looks at it.

The surviving contacts go through Message Writer, which drafts an opening line for each using their role, company, and context. The rep edits rather than composes — a different and much faster task.

In parallel, a standing Reddit Pro and Twitter run monitors the category for buying language. Posts scoring seven or higher on intent get same-day replies referencing the specific problem the person described, which is the highest-converting outreach the team sends all week.

What it costs in practice

A realistic weekly loop for one rep: 200 contacts from Leads Finder at one credit each, AI scoring across all 200 at two credits each, and Message Writer on the top forty at five credits each. That is roughly 800 credits per rep per week.

At Starter's 10,000 monthly credits, that supports a rep running the full loop weekly with headroom for intent monitoring. Pro's 50,000 comfortably covers a small team doing the same.

The comparison worth making is not against a cheaper data vendor but against the hours currently spent assembling lists by hand. One recovered selling day per rep per week is a larger number than any line on this pricing page.

Frequently asked questions

Do you charge per seat?: No. You buy credits and the whole team draws on the same balance. Adding a rep does not add a licence fee, which is usually the single biggest cost difference against conventional sales-intelligence tools.
Can this replace our existing contact database?: For many teams, yes — particularly those pulling a few thousand contacts a month, where per-result pricing beats an annual seat contract. Teams pulling hundreds of thousands should compare against a bulk agreement. The per-result price makes that calculation straightforward.
How do we avoid burning credits on bad-fit leads?: Filter hard before you collect, then score before you enrich. Narrow filters return fewer results and therefore cost less, and running AI scoring at two credits per row before spending five per message keeps the expensive step off the wrong people.
What about deliverability?: Filter Leads Finder to verified email status. It returns a smaller list with materially better deliverability, which matters more than raw volume if you are protecting a sending domain.

Workflows built for Sales Teams

Lead Gen

Lead Generation

Most teams spend hours manually searching LinkedIn and Google for prospects that half the time don't match their ICP. By the time the list is ready, the window has closed.

See the workflow →Social Intel

Social Listening

The most qualified prospects aren't filling out forms — they're posting on Reddit and Twitter about exactly the problems your product solves. You're not seeing those posts.

See the workflow →