RocketReach

RocketReach: the who, at scale

700M+ professionals, 60M+ companies, and a deliberately lean team behind it

RocketReach, led by CEO Scott Kim, is one of the world's largest contact-data platforms, spanning more than 700 million professionals and 60 million companies. Its promise is simple and hard to beat: find the right person and the right way to reach them, whether that's a verified email, a phone number, or a social profile.

That promise has made RocketReach a daily tool for sales, recruiting, and business development teams who live and die by the quality of their contact data. But great contact data answers part of the outreach question: it tells you who to reach, not when.

RocketReach’s data team has always had a primary focus on coverage and accuracy. And it became clear customers wanted more signaling on when to reach out, with perfect timing.

The right contact at the wrong moment goes nowhere

The insight behind this project is one every experienced seller feels in their gut. As Jamie Gullbrand, Group Product Manager at RocketReach, puts it, you can have the right list of contacts, but if you reach out at the wrong moment, it goes nowhere. Knowing who to contact is table stakes; knowing when is the difference between a reply and silence.

RocketReach already understood the value of timing, and customers were asking for signals. Years earlier the team had built a simple in-house system that tracked three event types, funding, mergers and acquisitions, and executive changes, by polling a hand-maintained list of RSS feeds hourly. It worked and proved the value to customers.

Three event types is a thin slice of the moments that matter across 60 million companies. Customers saw the value, and wanted more.

Why Autobound: coverage they didn't have to maintain

Existing customers were already asking for better timing signals

RocketReach users were asking for richer timing and hiring signals, and because the platform already surfaced a handful of company events, they were primed to use more. Trigger events like funding rounds and leadership changes, plus hiring trends drawn from job postings, became the obvious first signals to bring in from Autobound.

Two benefits made the case immediately. First, breadth: against the three event types RocketReach had hand-built, Autobound surfaces the full range of company moments that signal intent, from funding rounds and leadership changes to new offices, expansions, and product launches. That's not an incremental gain, it's a different order of magnitude in the moments users can act on. Second, maintenance: Autobound owns the pipeline and the upkeep, so when a source changes or breaks, that's Autobound's problem, not a fire drill for RocketReach's data team.

Trust was the gating factor: a signal users don't believe is a signal they stop using. Before shipping, RocketReach ran a manual QA pass across both the event and job-postings data and confirmed it was accurate, which gave the team the confidence to put it in front of users and keep it there.

From hourly RSS to daily managed delivery

JSONL over GCS, ingested straight into the search backend

Autobound delivers signal data as JSONL files to enterprise destinations like Google Cloud Storage or AWS S3. RocketReach's data team ingests those files directly into the search backend behind Person and Company Search, where the product team surfaces them to users. First delivery to live production took about a month, with most of that time spent coordinating two internal teams: the data team handling ingestion and the product team building the in-app experience.

Early on, Autobound moved delivery cadence from weekly to daily, an upgrade Jamie specifically called out as helpful. Fresher data means users filter on events closer to when they happened, which is the entire point of a timing signal.

The before-and-after is stark. The in-house system covered three event types from a hand-maintained RSS list; Autobound surfaces the full range of company moments and handles all the upkeep. Today Autobound is the primary source behind RocketReach's event signals, with the original in-house feed kept only as a thin supplement.

How it shows up in Search

Pick a signal type, pick a window, see who's in motion

Rather than bolt on a separate signals dashboard, RocketReach embedded Autobound data where users already work: as filters in Person and Company Search. A user picks a signal type, say a funding round or an executive change, pairs it with a time range, and the results narrow to the people or companies that triggered that event in that window. The who and the when collapse into a single query.

That's the whole point. A rep can go from 60 million companies to the specific set that just raised, just changed leadership, or is hiring against a particular trend, and pull the right contacts at those accounts in the same flow, while the moment is still live.

The signal data does double duty: it tells users when to act, and it gives them substance to act with, concrete details from the underlying event and hiring activity that fold straight into a message to make outreach more relevant and personal.

SaaS companies, 50-500 employees JG

Companies People

Signals

✓ Funding round

✓ Executive change

Hiring trends

New office

Time range

Last 30 days ▾

248 companies match Most recent ▾

N Northwind Logistics Supply Chain · 210 employees Raised $42M Series B · 4d

L Lumen Health Healthcare SaaS · 140 employees New VP of Sales · 1w

C Cobalt Security Cybersecurity · 320 employees Hiring 12 SDRs · 2d

What's next: higher frequency, deeper integration, more signal types

From a signal filter to a prioritization engine

The clearest near-term ask is frequency. Daily was a meaningful jump from weekly, and RocketReach would like to push toward hourly or real-time so the platform reflects moments as they happen. The harder, happier problem is choice: with more than 700 signal types in Autobound's catalog, deciding what to integrate next is its own challenge. Given RocketReach's majority-SMB base, website intelligence (around 6M companies monitored across 35 subtypes) and social signals (LinkedIn, Twitter, and YouTube activity at company and contact level) stood out as especially strong fits, alongside technographics, product reviews, and SEC filings for public companies. Autobound's MCP server, which connects every signal type, gives the team a fast way to test new types for list building before committing to a full integration.

Further out, RocketReach plans to weave signals into the prospecting flow itself rather than leave them as a standalone filter: using signals to prioritize which prospects to work, shaping how contacts get recommended, and drafting outreach that incorporates the relevant signal automatically, alongside 5x5 intent data and RocketReach's own job-change signals. The direction is consistent: signals started as a simple search filter and are becoming the layer that decides who the product surfaces and what a user should say.