Building a Signal-Driven Outbound Engine: From Converting Buying Triggers into Conversations

Client: Adventum

Website: goadventum.com

Overview

Adventum’s outbound strategy was slowed down by fragmented tools, manual research, and missed timing on buying signals. To solve this, we designed and implemented a signal‑driven outbound engine that connects every part of the stack, from capturing data, enrichment, CRM, outreach, and follow‑up into one seamless flow. Now, LinkedIn engagements, scrapes, or manual inputs instantly enrich their CRM, buying triggers are detected in near‑real time, and meetings are logged with automatic next steps. The result is a repeatable system that turns raw signals into booked conversations within minutes.

The Challenge

Adventum’s outreach process was messy and slow. Their team had to build and update records by hand from LinkedIn and campaigns. They often spotted buying signals too late, and their CRM lists went out of date quickly. Key details were stuck in personal notes, making it hard to know the right timing or stage. They leaned too much on spreadsheets, follow‑ups were hit‑or‑miss, and many good chances slipped away.

Our Objective

Our goal was to give Adventum a faster, more reliable way to act on buying signals. We wanted to remove the manual work, make their CRM the central part of the operation, and build an automation engine that moved smoothly from new lead to booked meeting with little human effort.

What We Did for Them

To solve these problems, we built a unified, signal‑driven outbound engine that automated every step of the workflow:

1.Acquisition & Identity

We implemented webhooks that pulled data from LinkedIn campaigns, profile scrapers, and manual form entries. This meant every new contact or company was captured automatically. And integrated with Make.com which helped to either create a new Person/Company record or update an existing one in Attio CRM, making CRM the single place where all records lived and stayed current.

2.Enrichment

Once records were in Attio CRM, scheduled searches looked for missing details. Clay filled in fields like revenue, funding stage, team size, industry, and key decision‑makers. Each record was then marked with an updated enrichment status, so the team always knew what was complete and what was still missing.

3.Signal Detection

Abacus.ai and Clay continuously scanned for triggers such as new hires, funding rounds, or major news. When something happened, the trigger was added into Attio CRM with a date stamp. Instead of replacing old notes, each new signal was added on top, creating a full history of why and when outreach should happen.

4.Engagement

Lemlist handled outreach campaigns across email and LinkedIn. When a prospect booked time through Calendly, the Person’s stage in Attio updated automatically to Meeting Booked. Even LinkedIn invites were logged back for reporting, so every interaction was tracked and nothing got lost..

5.Post‑Meeting Follow Up

After a meeting, notes stored in Attio CRM were passed to ChatGPT, which turned them into clear summaries and even drafted follow‑up emails. These were pushed back into the record the same day, so their reps could send professional follow‑ups immediately.

6.Governance & Hygiene: 

To keep data clean, every new record was checked by LinkedIn URL, email, or domain to avoid duplicates. Status fields like enrichment_status, trigger_status, and trigger_last_checked kept automation reliable. A 30‑day review cycle ensured signal checks stayed fresh and nothing went stale.

This system changed Adventum’s outbound from manual and reactive to automated and signal‑first, cutting time‑to‑touch, enriching records within hours, syncing stages automatically, and making sure follow‑ups were always made on time.

 

Conclusion and Results

Here’s what the system delivered once it was in place:

1. 45% faster time‑to‑first‑touch from lead capture.
2. 78% of new records were enriched within 24 hours.
3. 32% meeting conversion after signal‑based nudges.
4. 10 hours/month saved on research & note writing.
5. 5. Pipeline velocity up 27% from meeting to proposal.

Qualitative wins

1. Their reps now spend more time talking to prospects, because the system takes care of pulling together data and context.
2. Outreach happens at the right moment, because triggers like funding rounds or new hires are caught as they happen.
3. Follow‑ups are no longer delayed; meeting notes are turned into same‑day emails so nothing is left hanging.

Tech Stack Used

Make.com (orchestration • webhooks/routers/mapping/retries)

Attio (CRM objects, lists, list entries)

Clay (data enrichment, signals, partner/firm enrichment)

Apify (web scraping & automation)

Abacus.ai (custom, code‑based trigger detection for VC + portfolio)

Lemlist (multichannel outreach)

Calendly (bookings + stage automation)

What They Had To Say:

“Prospects Hive turned our scattered tools into one rhythm. Signals land, records enrich, meetings book, and follow‑ups write themselves. Our team finally sells instead of stitching data.” — Austen, Adventum

Want a signal‑driven outbound engine like Adventum? 

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