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Growth
7
min read
December 13, 2024

Your Signal-Based Selling Guide for 2024

Keelyn Hart
Content Writer at Letterdrop

TL;DR:

  • Signal-based selling focuses on recognizing and interpreting buyer intent signals throughout the sales process.
  • Key elements include data collection, prioritizing signals, response strategy, and continuous learning.
  • Implementing signal-based selling involves identifying and scoring relevant signals, using signal-tracking tools, and personalizing outreach playbooks.
  • Challenges to signal-based selling include signal overload, generic messaging, siloed tools, and lack of credibility.

If you’ve ever wished your sales process could be less of a "boil-the-ocean" approach, then signal-based selling is your solution.

It can help you find and prioritize signals so that you're focusing on the right accounts — those who are visiting your pricing pages or who have liked a company LinkedIn post, for example — and can help you target that 5% of folks in-market.


What is Signal-Based Selling?

At its core, signal-based selling focuses on recognizing and interpreting buyer intent signals throughout the sales process. These signals might include subtle actions, like time spent on a key webpage, or more explicit behaviors, like a demo request.

By identifying these cues early, sales teams can prioritize the accounts who are actually likely to become buyers instead of going with a spray-and-pray approach.

Key Elements of Signal-Based Selling:

  1. Data Collection: Gather behavioral, firmographic, and intent data from multiple touchpoints, such as websites, emails, and social media.
  2. Prioritizing Signals: Determine which actions signify buying intent, such as visiting your pricing page or explicitly liking your company page posts.
  3. Response Strategy: Design personalized responses for each signal to move deals forward.
  4. Continuous Learning: Analyze outcomes to refine your approach.


An example of a signal-based selling workflow in RB2B
An example of a signal-based selling workflow in RB2B



Why Signal-Based Selling Matters

The old spray-and-pray approach to sales gets harder and harder with each passing year.

You can't expect to hit targets if you're trying to boil the ocean, so to speak.

Buyers are inundated with robotic pitches, so it's more important than ever that when you reach out

  • you're talking to the right person
  • you're adding value
  • you're standing out from the crowd

As for the benefits of signal-based selling specifically:

  • Higher Reply Rates: Personalized messaging based on intent signals increases the likelihood of a response.
  • Faster Deal Cycles: Engage prospects when they’re ready to buy, reducing time spent on cold leads.
  • Improved Resource Allocation: Focus efforts on the 5% of prospects actively in the market, maximizing efficiency.


Signals to Track Across the Buying Journey

I always say that not all signals are created equal. Some are so overcrowded that it takes a little more research and finesse to get a response — others are unique to you.

Since everyone and their mom is going after public signals, your private signals are what you need to focus the most energy on.

Differentiating the most valuable sales triggers
Differentiating the most valuable sales triggers


I have a specific guide for sales triggers to look out for and when — but here's the TL;DR.

It's important to divide signals into two distinct categories:

  1. Public Signals: Easily accessible but often competitive because everyone can see them.
  2. Private Signals: Exclusive to your team and invisible to competitors, giving you a unique edge.

And of course, different signals appear at different stages of the buyer journey. Timing is everything.


Early-Stage Signals: Awareness and Exploration

At this stage, prospects are exploring options and researching solutions to their problems. These signals indicate initial interest:

  • Website Activity: Visits to blog posts, features pages, or pricing pages show curiosity. Prioritize prospects who spend significant time or return frequently.
  • Social Engagement: LinkedIn likes, comments, or shares (on your posts or related topics) signal interest in your thought leadership. Use these as conversation starters to build rapport.
  • Employment Activity: New hires, promotions, or company growth often trigger fresh priorities or new budgets. Leadership changes are especially noteworthy for targeting decision-makers.

Mid-Stage Signals: Evaluation and Validation

Prospects at this stage are diving deeper into your solution, evaluating fit, and seeking proof of value.

  • Content Downloads: Downloading resources like case studies, ROI calculators, or whitepapers suggests active evaluation. Tailor follow-ups to address the content’s themes.
  • Email Engagement: Repeated opens or clicks on nurture emails reflect growing interest. High engagement, such as clicking multiple links, signals readiness for deeper conversations.
  • Competitor Engagement: If prospects interact with competitor content or relevant influencers, position your solution as an alternative or complementary offering.


Late-Stage Signals: Decision and Commitment

These signals show that prospects are narrowing down their options and moving toward a decision:

  • Demo Requests: A direct request for a demo or trial indicates serious consideration. Personalize your demo to their specific pain points and decision criteria.
  • Pricing Discussions: Questions about costs, implementation, or timelines signal that the prospect is close to a decision. Address these promptly and transparently.
  • Private Engagements: Actions like profile views, following your company page, or attending webinars suggest intent that isn’t visible to competitors but is ripe for action.


How to Implement Signal-Based Selling

Here's how to set up your signal-based selling model.

Identify and Score Relevant Signals

Creating a data-driven account scoring model using tools like Clay, Letterdrop, and RB2B can help automate the process of both defining and prioritizing your best-fit accounts.

You can read more in our dedicated guide for it, but the TL;DR is:

1. Pull the Right Data

Collect accounts using multiple signals like website visitors, LinkedIn engagement, cold lists, and job switches. Tools like RB2B and Letterdrop are key here.


Leads pulled from RB2B
Leads pulled from RB2B


2. Qualify the Accounts That Matter

Score and filter your accounts using tools like Clay — are they hiring in your vertical? Do they use X tools? Etc.


Filtering by best-fit customers in Clay
Filtering by best-fit customers in Clay


3. Enrich Contacts for Outreach

Narrow your top accounts and identify key decision-makers:

  • Find email addresses and LinkedIn profiles (Clay, Apollo).
  • Sync data into your outreach tools to kickstart some multi-channel outreach.

4. Outreach With Context

Personalize every message using insights:

  • Did they engage with your LinkedIn post? Mention it.
  • Are they hiring AEs? Connect your product’s value to their growth.
  • Are they visiting your site? Highlight relevant features they explored.


Use Signal-Tracking and Metric-Tracking Tools

As seen above, automation is a key aspect of signal-tracking today.

With Letterdrop, you're able to track historical engagement on company-wide LinkedIn pages as well as the impact of LinkedIn activity on actual pipe. From there, you can immediately contact them.

You can filter by first or third-party engagement and segment by competitor, ICP, etc. There's a keyword monitoring feature to help with social listening, too.


Track historical engagement and impact of LinkedIn on pipe
Track historical engagement and impact of LinkedIn on pipe

Clearbit, 6Sense, and RB2B are excellent for de-anonymizing your web visitors to the same end.

It's important to keep on top of your signals as well as whether your outreach appears to be working so that you can refine and iterate.


Personalize Outreach Playbooks

Create tailored playbooks for each signal. For example:

  • Pricing page visit? Send a follow-up email highlighting relevant features.
  • LinkedIn comment? Reply to their comment with a thoughtful question or insight to spark conversation.

Incorporate insights from your ICP to make every touchpoint relevant and timely.


How to Overcome Challenges to Signal-Based Selling

Signal-based selling isn’t without its challenges.

1. Signal Overload

Not every signal is actionable or valuable. Avoid chasing every interaction by creating an account scoring model, as outlined in the above section, to prioritize your warmest and best-fit accounts.

2. Generic Messaging

Personalization is everything. Avoid templated outreach by using the prospect’s signals as context for your messages.

For example, if they engaged with a recent post on a certain topic, you might send a message like this.



3. Siloed Tools

A fragmented tech stack can create silos and inefficiencies. Make sure your tools, like CRM and engagement tracking software, integrate seamlessly.


4. Lack of Credibility

Prospects are more likely to engage with reps who have a strong online presence. Invest in social selling and building your credibility by:

  • Posting consistently on LinkedIn for instance about industry trends, customer success stories, or personal insights from personal accounts
  • Engaging with others’ posts to stay visible and establish thought leadership


Sharing thought leadership like Laura Erdem builds your credibility
Sharing thought leadership like Laura Erdem builds your credibility


Final Thoughts

Signal-based selling (especially when it comes to private and less competitive signals) is the future of B2B sales. By focusing on real-time intent signals, you can build stronger relationships, improve efficiency, and close deals faster.

If you’re ready to level up your sales game, start tracking signals with Letterdrop— the all-in-one tool for identifying, prioritizing, and acting on buying intent.

Ready to find warm accounts to outbound to?

Let us help you track historical engagement on site and LinkedIn and tap into warm leads.

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