Autobound

Autobound sells signal access as one-time credit packs ($19 for 2,000 credits up to $4,999 at the top tier), so an agency's data cost scales with the queries it actually runs rather than a seat license that bills whether or not a client campaign ships. Zero-result requests are free and credits never expire, which means an agency can prototype a client's intent workflow on the $19 Starter pack before committing a retainer to it. The strategic risk sits on the other side: Autobound is API-first, so the agency owns billing, credit allocation per client, and the integration work that turns 700+ signal types into something a client will pay monthly for.

Autobound sells one-time credit packs ($19 for 2,000 credits up to $4,999 at the top tier), and zero-result requests cost nothing. That single rule should drive how an agency scopes client work. A narrow ICP with tight signal filters burns credits slowly; a broad query with loose filters burns them on every match. Model each retainer as credits consumed per delivered contact, not seats or hours. Example: a client needing 200 intent-scored contacts a month against three signal types may consume a few thousand credits, which fits inside the $49 Growth pack (5,444 credits) with room for re-runs. Because credits never expire, an agency can buy ahead of demand and carry unused balance across clients, but must still allocate consumption per account so one noisy client does not drain the pool. Price the retainer against worst-case burn, not average.

Signal Decay Half-Life is the working assumption that an intent signal loses most of its commercial value within days, not weeks, so the useful question is not whether a prospect is in-market but how long ago the signal fired. Agencies that treat intent as a static list end up pitching accounts that already bought, while agencies that timestamp every signal and route it inside a 72-hour window convert at materially higher rates. The framework forces three disciplines: record the signal date, define a contact deadline per signal type, and retire anything past its half-life. Community monitoring tools such as Agenmatic surface posts in real time, which only pays off if a reply goes out the same day. Web visitor identification from Leadfeeder behaves differently, since a company reading a pricing page on Tuesday is a colder contact by the following Monday. Pair the half-life rule with CRM deal stages so a signal that never advances past discovery gets flagged rather than recycled into next quarter's retainer reporting.

Signal-to-Stage Mapping treats every intent signal as a hypothesis about where a buyer sits in the pipeline, not as a lead. The framework asks agencies to tag each signal source against the deal stages it actually predicts, then retire sources whose signals never convert past first call. A community post scored for urgency by Agenmatic may indicate early research, while a Bombora surge on a category topic usually marks mid-funnel comparison, and a Leadfeeder page visit on a pricing URL often signals late-stage evaluation. Mapping each source to a stage lets an agency route outreach differently: education for early signals, competitive displacement for mid, proposal support for late. It also exposes overlap, since three sources firing on the same account rarely means three times the intent. The discipline matters because retainer clients pay for pipeline movement, and a signal that never advances a deal is a cost center dressed as intelligence.

Adopt Autobound when the deliverable is signal infrastructure a client will run on, and decline it when the client only wants a finished prospect list you would have to hand-build.

Before scaling spend or outreach on any intent signal, back-test it against the client's last 90 days of closed-won and closed-lost deals and keep only the signal types that appear in won deals at least twice as often as lost ones.

IF your agency already sells prospecting, enrichment, or AI SDR work and needs buying signals (funding, hiring, leadership changes) inside client workflows, THEN start with the $19 Starter pack (2,000 credits, all 35+ signal sources, REST API + MCP server, credits never expire) to validate one client use case before committing. IF volume is proven across multiple clients, THEN step to $149 Scale (19,867 credits) or the $4,999 one-time tier rather than stacking small packs, because Autobound is credit-based and your agency owns per-client credit allocation and billing. IF you need a managed UI, done-for-you onboarding, or per-seat dashboards, THEN skip: Autobound is API-first and the trade-off is that your team absorbs integration and credit governance.

Stand up a white-label OEM deployment of Autobound's signal API so agency clients get 700+ signal types from 35+ sources on 270M+ contacts and 50M+ companies under the agency's own brand, with credit allocation and billing handled at the retainer level.