Skip to content
Evgeny
Rodionov
← All projects

Anecdotes / 2026

Sales intelligence · GTM

LinkedIn Signals

Give Sales a relevant person and the context to act.

I built a system that turns LinkedIn engagement into qualified prospect worklists, with CRM context and follow-up measurement.

A closer look at the workExplore the case
LinkedIn SignalsSystem overview
01

Collect activity

Read relevant posts and engagement, then gather person and company evidence.

02

Qualify the fit

Check role, company, region, and CRM relationships.

03

Help sales act

Deliver a short, contextual worklist through the board and Slack.

04

Observe outcomes

Follow later CRM activity to connect the initial signal with commercial progress.

Process illustration · Read the build decisions below

01 / The problem

A reaction is only the start of a sales decision

A list of people reacting to a post includes existing customers, unsuitable companies and people with no relevant buying role. Sales also needs to know whether someone is already being worked by another colleague. I set out to turn those scattered signals into a small, usable set of opportunities.

02 / The build

How I built it

01

The system collects engagement from relevant LinkedIn posts and checks the person’s current role and company fit. It joins that evidence with HubSpot relationships and ownership information. Ambiguous matches remain unresolved rather than becoming confident-looking leads.

02

Qualified people reach a working dashboard and a short Slack digest. The record explains why the person is relevant and gives Sales the context needed to decide on an approach. Outreach remains a human decision.

03

A separate tracking layer follows actual CRM changes after a person enters the worklist. This connects the initial signal to later commercial activity while preserving the distinction between identifying a prospect, influencing a conversation and originating a deal.

My role

I built the collection, qualification, CRM checks, delivery and measurement workflow. I worked with the sales users on targeting and usability, then adjusted the system around the way they actually worked.

03 / In practice

What makes a signal actionable

01

Trigger

Evidence on the card

Comment on a relevant industry post

Why it matters

A reason to start a conversation

02

Fit

Evidence on the card

Role and employer qualification

Why it matters

The person could be a buyer

03

Relationship

Evidence on the card

CRM match and account owner

Why it matters

Respect the existing relationship

04

Next step

Evidence on the card

Review, claim, and follow up

Why it matters

A human owns the conversation

Illustrative contact card. Names, companies, and production CRM details are intentionally omitted.

04 / The result

Six-figureARR pipeline

The work contributed to a six-figure ARR pipeline. Sales acted on the prepared prospects and owned outreach, follow-up and closing. The system gave them relevant worklists and the context to turn an initial signal into a useful conversation.

Keep exploring

Offero

I built a job-search product that discovers roles, explains mutual fit and prepares a coordinated application package.

Next case
Ask my
AI avatar