What is Activity in Lead Scoring?

DEFINITION
Activity in lead scoring takes behavioral data into account to determine which leads are the most high-intent (or the most likely to convert). Activity can help your sales team identify high-intent leads alongside opportunities to upsell, cross-sell, or prevent churn from existing clients. 

💡Understanding the Role Activity Plays in Lead Scoring

Activity plays an essential role in reliable lead scoring models, as it allows you to look at behavioral data to see which customers are actually high-intent based on their actions. 

Fit alone isn’t enough to determine which leads are likely to become customers, or which contacts are best suited for upselling or cross-selling opportunities. Lead scoring tools that focus exclusively on fit often cause the sales team to sideline too many potential customers that could have been flagged with basic activity data. 

Examples of activity may include the following:

• Newsletter sign-up
• Emails opened or responded to
• Site pages visited 
• Demos booked
• Phone calls made to the sales team
• Free trial sign-up
• In-app activity and features used (for SaaS brands) 
• Purchase made
• Support tickets submitted 
• Maxing out the existing plan
• Number of logins 

It can be difficult to keep up with which activity metrics are true indicators of intent and how to interpret them. Lead scoring tools like Breadcrumbs that allow you to test different scoring models are essential to creating custom-to-you models that actually helps your sales team determine which contacts should be prioritized by your sales team. 

When you combine activity data with frequency and recency metrics, your sales team is sitting on a goldmine; they can see how often a lead is making a specific action that acts as buying signal and how long ago that action was taken.

🖋 Takeaway

Activity isn’t the only thing that you’ll need to account for in your lead scoring model—fit is just as important to creating a lead scoring model that actually gives your sales team actionable information because alignment with your ideal customer profile (ICP) is dead useful. 

That being said, activity is half of the equation, which is why it accounts for half of our lead-scoring models here at Breadcrumbs. We utilize a co-dynamic approach to give you a holistic look at every contact in your system, no matter where they’re at in their lead journey, giving you an alphanumerical score to help your team assess fit and activity simultaneously. 

Behavioral data plays a vital role in your activity score, as it takes individual user actions into consideration to look for buying signals that should never be ignored. 

When determining which user actions you should rank most highly, look at your overall buyer’s journey. CRM data, your sales team, the marketing team, and the customer support team  may be able to give you insight into: 

• Which path to conversion yields the most high-value customers or the most customers acquired overall
• Which actions typically come immediately before account set up or deals closed
• What actions indicate a high-value audience (like a booked demo as opposed to a free trial sign-up)
• Which actions indicate upselling or cross-selling opportunities
• Which actions indicate a high risk for churn and an opportunity for re-engagement 

We typically recommend starting with 3-5 data points for activity so that you can test these out, see what works, and then move out to add data points as you see fit. Understanding the core data points you want to build a lead scoring model around is a good start before adding in additional data since too much data upfront can make it difficult to assess which elements of the model are accurate and which aren’t. 

What is activity in lead scoring? 

Activity in lead scoring involves assessing behavioral data to look for high-intent buying signals in individual users. Different actions will be given different weighted values; someone who signs up for an email newsletter will receive a few positive points, for example, but won’t be valued as highly as a contact who signs up for a demo. 

What is behavioral data? 

Behavioral data is information about individual user behaviors and actions they’ve taken. Examples include pages they’ve visited on your website, features accessed in a SaaS tool, demos booked, emails opened, and support tickets submitted. 

Why is behavioral data important? 

Behavioral data is essential for lead and contact scoring because it tells you which users are taking actions that indicate buyer intent. When combined with recent and frequency, activity is crucial; it can help you determine which leads are ready to purchase now. It prevents brands from accidentally ruling out potentially high-value customers because they’re only looking at demographic fit. 

How do you collect behavioral data? 

Behavioral data is best collected through first-party data sources. Your email marketing software, for example, can tell you which users opened what emails, and your SaaS platform tech can tell you what users are utilizing which features. 

All of this data can be synced through your CRM, and that data can be shared with your lead scoring tool. 

What are examples of behavioral data? 

Examples of behavioral data include: 

• Newsletter sign-up
• Emails opened or responded to
• Site pages visited 
• Demos booked
• Phone calls made to the sales team
• Free trial sign-up
• In-app activity and features used (for SaaS brands) 
• Purchase made
• Support tickets submitted 
• Maxing out the existing plan
• Number of logins 

How do you score leads behaviorally? 

Scoring leads behaviorally involves creating lead-scoring models that assign numeric values to different actions that a lead can take. These points are based on the value of the action itself. They make receive three points for signing up for a free trial, for example, but five for booking a demo.

Strong lead scoring systems will take both recency and frequency into account. The more often a lead takes a certain action, the better, and the more recent, the better. Models should ideally have a time-decay feature to prioritize leads who most recently took the desired actions. 

What lead activities indicate buying intent? 

Lead activities that indicate buying intent vary significantly from business to business, but examples may include:

• Subscribing to a newsletter
• Signing up for a trial
• Booking a demo
• Contacting sales about pricing 
• Visiting key product landing pages
• Visiting pricing pages 

What contact activities indicate potential churn? 

It’s common for brands to use contacting scoring tools to identify users who could benefit from re-engagement campaigns in order to prevent churn. Examples of contact activities that may indicate potential churn include:

• Users who haven’t logged into the tool in a set period of time
• Support tickets filed to the help desk
• Responding to customer support feedback saying that they weren’t happy with the results of the customer support interaction
• Downgrading their plan