Signal-based selling without the daily scramble

Signal-based selling works or fails on how long a signal takes to reach the person who acts on it, not on how good the signal was.

Focus on the right accounts at the right moment, with enough context to start a real conversation.

Overview

Most lists tell you who to contact. What reps need is when and why now. This growbook shows how to use Intempt to turn product behavior and fit criteria into clear, living queues for outreach. You'll enrich just the fields you actually use, qualify leads with simple, transparent rules, and act on signals quickly without juggling tools.

We'll use Otto (a demo SaaS platform) to illustrate the approach.

Use a Qualification Agent to score Sales Readiness with Fit + Activity.

Build sales-ready segments (e.g., High Fit + High Activity) that update in real time.

Launch a Journey for those segments: short sequences, sensible delays, and behavior-based routing.

Personalize with Smart Snippets that pull from research fields automatically.

Alert reps on key actions (reply, meeting booked) and auto-create Tasks for follow-through.

Track replies, meetings, and pipeline impact in Journey Analytics and Dashboards.

Result: Fewer cold touches, more timely conversations.

Benefits

Prospect where intent is fresh. Work the accounts showing meaningful, recent behavior.

One definition of "ready." Fit and intent live in one place, so Marketing and Sales share the same thresholds.

Arrive with context. Recent actions and role info are attached to the record you're working.

Reduce swivel-chair time. Research, scoring, outreach, alerts, and measurement run in one system.

Measure what moves deals. See which signals correlate with meetings and wins, then tune the rules.

How It Works

Define the goal events, bring leads in with only the context a rep will read, then score fit and activity separately and route on the pair.

Step 1: Define and track Goal Events

Any goal event that is missing has to be defined before routing can work, because a signal you do not record cannot be routed.

Step 2: Bring in leads and add only useful context

Import users/accounts from your list or connected sources. Use a Research Agent to enrich the few fields that change how you write or route (role, seniority, tech stack, industry). If contact details are missing, fill just what you need for the first touch.

Step 3: Define "ready" with Fit + Activity

Create a Qualification Agent that scores Sales Readiness using:

Fit: firmographics and ICP traits (company size, industry, stack match).

Activity: recent, high-signal behavior (e.g., viewed pricing, invited teammates, hit usage thresholds).

Step 4: Build sales-ready segments

Create segments like 'High Fit + High Activity', 'High Fit + Medium Activity'.

Step 5: Turn signals into outreach with Journeys

Launch a Journey for your top segment. Keep it short: two or three steps with natural spacing.

• Branch on behavior. if they engage, move them forward; if they don't, slow down or re-score.
• Use Smart Snippets. pull research fields into the message so it reads like you wrote it.
• Notify the human. send a lightweight alert on replies or meeting bookings.

Step 6: Measure and tighten the loop

In Journey Analytics and Dashboards, look at: replies, meetings created, cycle time, and opportunities/wins by readiness level. Notice which signals show up most often before a meeting, and adjust your Agent weights or segment rules accordingly.

Good to Know

Keep the score simple. Clear levels beat opaque formulas; reps should know the "why" at a glance.

Fewer signals, stronger signal. Two or three reliable intent events usually outperform long lists.

Auto-create Tasks for reps when key actions fire: call, email, LinkedIn, or a quick prep checklist. If Deals are part of your pipeline, create or update them when a meeting is booked or a stage changes.

Route it before it cools

Most teams can list their signals. Far fewer can say how long it takes one to reach the person who acts on it, and that latency is the whole game.

Reading fit and activity together per account is what the agentic GTM platform does before the task is created, which is why the routing can be immediate. The PQL signal to SDR task recipe creates the task with the context attached, which is the step that usually gets dropped.

A signal that arrives after the moment has passed is just a report entry. Signal-based selling only beats a list when the signal reaches a rep while it is still true.