Understanding Prospect Signals to Boost Your Revenue Operations

If you’re on your organization’s Revenue Operations (RevOps) team, sales team, or marketing team, you’re in the trenches making things happen. In this guide, we’ll dive into types of prospect signals essential data points that reveal your customer’s journey and help shape your strategy. While leadership might find value in strategizing around these signals, this is really aimed at ground-level operators who will use this insight to drive real action.

Here’s why it’s worth understanding the types of prospect signals: maybe you’re feeling lost in the customer journey, or you need clearer insights into what’s working (or not working). Knowing the signals that your prospects give off will help you understand your customers, make better decisions, and ultimately win more deals.

Why Prospect Signals Matter

• Understand the Customer Journey: Knowing prospect signals is like mapping out your customer’s journey. By identifying key actions and events, you can see the path your customers take, even if it’s not always linear.
• Identify Effective Tactics: Sometimes, it’s tough to pinpoint what’s working in marketing, sales, or RevOps. Prospect signals give you a way to see patterns, evaluate tactics, and share these insights with the team.
• Competitive Edge: Whether or not you’re a “data person,” knowing prospect signals can help you leverage data effectively, and give you a serious competitive edge.

The Three Categories of Prospect Signals

To make sense of prospect signals, we categorize them into three main types: First-party, Second-party, and Third-party. Each has unique strengths and uses in shaping an accurate view of your prospects and their journey.

1. First-party Signals: These are the data points you collect directly from interactions with your customers and prospects. They include:
   • Explicit Data: Information that prospects provide directly, like filling out a form or answering a survey. Sometimes called “zero-party data,” this is data that’s voluntarily shared and highly valuable for tailoring the customer experience.
   • Implicit Data: This data might be inferred from behaviors, like website visits or app engagement. Regardless, it’s data you directly observe, control, and own, making it accurate and reliable.
2. Second-party Signals: Second-party signals come from trusted partners with a direct customer relationship. This could be a data-sharing arrangement with another company in a complementary industry. For example, if your partner shares data about overlapping prospects, it gives you more perspective on your customers' needs and interests.
3. Third-party Signals: These are collected by external providers and can be purchased or accessed by your organization. They can be very helpful for identifying broad trends, but it’s important to verify the quality and ethics of third-party data providers. Keep in mind that while this data might be valuable, it may lack the specificity of first- and second-party signals.

The Four Types of Signal Analysis

In addition to categorizing signals by origin, you can also classify them by how they are measured and used. This includes Observed, Calculated, Extrapolated, and Situational signals.

1. Observed Signals: Directly collected data that is measurable and objective. For example, a prospect visiting your pricing page is an observed signal that indicates possible interest.
2. Calculated Signals: Calculated signals require processing observed data to identify patterns. For example, if a prospect hasn’t replied after seven days, that might be a “ghosting” signal. Calculations are helpful to identify key actions or red flags based on past interactions.
3. Extrapolated Signals: These signals are derived from observations and calculated data but involve predictive judgment rather than hard numbers. For example, if a competitor is making moves in a shared market, you might extrapolate that your prospect is evaluating both of your solutions.
4. Situational Signals: These are signals derived from a combination of factors that provide insights based on the current market, industry trends, or company-specific situations. For instance, if you know a company recently hired a new VP of Sales, that situational signal could mean they’re in a growth phase or re-evaluating vendors.

How to Apply Prospect Signals Effectively

Using a Prospect Signal Matrix can help your team organize and interpret different signals. Here’s how to set it up:

• Step 1: Create a table with columns for First, Second, and Third-party Signals and rows for Observed, Calculated, Extrapolated, and Situational Signals.
• Step 2: Identify and list all signals you can capture for each category.
• Step 3: Use this matrix to understand which signals are most relevant, reliable, and actionable.

For example:

• A first-party observed signal might be a website visit, while a third-party situational signal could involve competitor activity data from a third-party tool.

Feeding Prospect Signals into Your CRM

Your signals should be captured and fed back into your CRM. This data can sit in your contact records, company records, deal records, and more, depending on your CRM’s structure. If you’re using a BI tool, you can go further in analyzing these signals, slicing the data to see trends and success rates.

Wrapping It All Up

Understanding and utilizing prospect signals—first, second, and third-party as well as observed, calculated, extrapolated, and situational—can elevate your RevOps, sales, or marketing efforts. By categorizing and analyzing these signals, you gain clarity on your prospects’ journey and can communicate your insights effectively with leadership.

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