Is DataForGTM an Apollo alternative for selling to developers?

It's an alternative for the developer-signal part. Apollo filters a contact database by company and title; DataForGTM starts from GitHub activity and resolves a developer's GitHub username to their LinkedIn. For broad contact data and sequencing, Apollo remains the better tool, and the two are often used together.

Can Apollo find developers by their GitHub activity?

No. Apollo keys on firmographics and job titles, so it can't tell who is starring, forking, or filing issues on a given repo. DataForGTM surfaces those GitHub buying signals and then resolves the person behind a username to LinkedIn.

An Apollo alternative for selling to developers

Apollo is a huge B2B contact database you filter by company, title, and industry. It can't see what a developer is actually building or evaluating. DataForGTM starts from GitHub activity and resolves the person behind a username to LinkedIn — so your outreach starts from intent, not a job title.

The core difference

Apollo and DataForGTM solve different halves of a dev-GTM problem. Apollo answers "who works at companies that look like my ICP?" by keying on firmographics and a person's title. That's broad and useful, but it's blind to GitHub behavior — a developer evaluating your library, starring a competitor, or filing issues on a dependency looks identical to one who has never heard of you.

DataForGTM starts from the behavior. You find developers and companies showing GitHub buying signals for a repo, org, or category, then resolve a specific GitHub username to a LinkedIn profile with POST /api/v1/deanon (2 credits, ~$0.30, charged only on a hit; misses are free). No other API sells that person-level GitHub → LinkedIn step.

How it compares

Capability	DataForGTM	Apollo
Find developers by GitHub activity / intent	Yes	No — keys on company & title, not code behavior
GitHub username → LinkedIn (person-level)	Yes, via API	No
Broad B2B contact coverage (emails, phones, titles)	No — not a general contact DB	Yes — this is Apollo's strength
Email sequencing, dialer, CRM sync built in	No	Yes
Agent-callable MCP / OpenAPI, bearer key	Yes	Some API, not agent-native
Self-serve, no demo, no seat, no dashboard	Yes	No — seat-based plans
Pricing model	Prepaid, pay per resolve	Per-seat subscription + credits

Resolve a GitHub username to LinkedIn

Authenticate with a bearer API key and call the endpoint from any client or agent:

curl -X POST https://dataforgtm.ai/api/v1/deanon \
  -H "Authorization: Bearer $DATAFORGTM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"githubUser":"torvalds"}'

You're charged 2 credits only when it resolves. A miss returns no profile and costs nothing.

When Apollo is the better fit

If you need broad B2B contact coverage across every department — not just developers — Apollo's database is far wider and includes verified emails, direct dials, and titles DataForGTM doesn't carry. If you want sequencing, a dialer, CRM enrichment, and a full sales-engagement workflow in one seat-based tool, Apollo is built for that and DataForGTM is not. Many teams run both: Apollo for the broad motion, DataForGTM for the developer-signal layer Apollo can't see.

Start

Self-serve trial — no demo, no dashboard. Start at dataforgtm.ai and grab an API key, or read the OpenAPI spec to wire it into your agent.

Is DataForGTM an Apollo alternative for selling to developers?: It's an alternative for the developer-signal part. Apollo filters a contact database by company and title; DataForGTM starts from GitHub activity and resolves a developer's GitHub username to their LinkedIn. For broad contact data and sequencing, Apollo remains the better tool — the two are often used together.
Can Apollo find developers by their GitHub activity?: No. Apollo keys on firmographics and job titles, so it can't tell who is starring, forking, or filing issues on a given repo. DataForGTM surfaces those GitHub buying signals and then resolves the person behind a username to LinkedIn.