What is lead scoring?
Lead scoring is a methodology to assign leads a value to determine how qualified a lead is and what the next best action for this lead is. Lead scoring usually uses customer segmentation criteria like demographics, geographics, and firmographics in addition to behavior information.
There are many lead scoring models to define the best lead scoring system for your company.
Lead scoring is most used in marketing automation. The technology assigned the scores automatically and routes the lead to the next applicable automated marketing flow.
The goal of lead scoring models is to manage the lead flow and efficiency. Marketing hands over only qualified leads to the Sales team. That means sales and marketing teams work more effectively and increase the conversion rates of the sales funnel.
Lead Scoring Formula
Every lead score is a combination of lead category information. A common lead scoring formula looks like this:
Lead Score = Demographic Score + Geographic Score + Firmographic Score + Behavior Score
In B2C lead scoring, firmographic data isn’t relevant.
Please refer to our customer segmentation guide to learn more about the different attributes and where to find the information.
In some lead scoring models, geographic scores are included in the demographic data.
What is a lead scoring model?
In your lead scoring model, you assign predefined points to a lead for static lead attributes and variable behavior. The combination of points determines a lead stage or triggers an action in the automated lead management flow, like sending the right nurture emails or handing it over to a Sales Development Representative.
The lead score model also manages how many points should be given for any criteria or action. For example, plus 10 points for the right industry, plus 5 points for visiting the pricing page, and so forth. This process should be done in cooperation with the sales team. A good approach is the lead score matrix.
When scoring is defined, the lead score model also determines which total or combination thresholds are needed for the next actions.
What is rule-based lead scoring?
Rule-based lead scoring defines rules within your lead score model. It rewards or penalizes leads with points for certain actions or known information. It also functions as a gatekeeper between marketing and sales. Only certain thresholds (total vs. individual lead scores) are seen as qualified.
Total Lead Score Model
In the total lead score model, the absolute total lead score defines the next action in the lead management process. For example, a lead score of 40 is the threshold for a specific action like handover to sales.
While this makes it easy to manage your lead flows, this lead score model has flaws. A single score can outweigh the entire equation. But this doesn’t mean that a lead is qualified. Here are two extreme examples:
A student engages in research for a paper with the content of a B2B enterprise. He downloads whitepapers, researches prices, even chats with the product team in the live chat. His behavioral score surpasses the threshold of 40 and she gets handed over to sales. Of course, this lead isn’t qualified at all.
On the other end, an ideal customer downloads an ebook from a LinkedIn lead generation campaign, skims through the pages, and tosses it because it has no value to her. 5 minutes late, an email from an SDR pops up in the inbox asking for a call. The lead moves the email to spam.
That email may have hurt the company more than it did well. Why did this happen? Based on the demographics and firmographics the lead checked all the boxes and the total lead score was higher than the handover threshold of 40 points.
What’s a better lead scoring model? Include a safety net to have a minimum threshold for each scoring criteria.
Individual Lead Score Model
In the individual lead score model, you treat each category individually which allows you to qualify your leads better but also determine automated flows to gather missing information.
Let’s say that the total score still needs to be at least 40 points to be qualified, but that each of the four categories (demographic, geographic, firmographic, and behavior) needs to be at least 10 points.
Here are three examples and scenarios:
Total Lead Score
Lead A is qualified and checks all four boxes. This lead is ready to be handed over to Sales/Sales Development.
Lead B is missing the demographic threshold. This could either be because the information is missing or the demographics don’t match the qualification criteria.
In the case of missing information, a campaign can be triggered to collect the information. This could be a manual task to an SDR to look up the lead information as well as a marketing campaign. A relevant gated content piece could be sent to the lead. After downloading the content the demographic information will be added and a score can be assigned.
Lead C is short on the behavior. Marketings goal should be to incentive engagement with the company. For instance, Lead C could be added to an automated email nurture stream that incentivizes her of visiting your website, blog posts, or landing pages.
This is the power of individual lead score models. They allow you to dive deeper into the total lead score and trigger the best possible next action.
Score decay in lead scoring models
Scores are not only increasing but also decreasing over time. This could be the result of enriching the lead information that determines a not qualified lead, but also negative behavior. Your lead scoring model needs a negative score, too.
Non-behavior lead score decay
In most lead scoring models static lead scoring points are assigned to lead records. Usually, those scores don’t change much. If you think about it, demographics, geographics, or firmographics only change if a lead changes the role within the company or moves to another employer.
Anyways, lead score decay can also help with determining if a lead is qualified or not. For example, all demographics look good but suddenly the geographic information is revealed. The lead is outside the core market. To prevent automated marketing campaigns, the score should be decreased. This could be true for certain job titles or functions.
Behavior lead score decay
More common is the decay of behavior lead scores. The score decay is mainly triggered by two possible actions – on non-action for this matter:
- Wrong buying signal: For example, the lead applies for a job
- Inactivity: The lead doesn’t engage with the company over a period of time or touchpoints. For example, every two weeks of non-engagement the behavior score will be decreased by 2 points. Additionally, for every email that has been sent without the desired action like a click to the website, the score also decreased by 1 point.
The behavior score usually determines if the lead is ready to continue the conversation with the company. Positive trends signal readiness but negative trends could mean that the lead is no longer interested in your product, involved in the decision making, the company decided against your solution, or it’s just not a good time right now.
Score decays can also trigger specific marketing campaigns like a win-back campaign. “Sorry you didn’t find our emails valuable – we will unsubscribe you shortly” as an example.
Marketing Automation Lead Scoring Model
Marketing Automation software can help you score leads by assigning points in real-time as well as automatically trigger the next lead flow. They also play a role in capturing lead behavior through their tracking codes.
We’ve created resources for the most common marketing automation systems:
Sascha is a Lifecycle Marketing Consultant with over 8 years of digital marketing experiences in Silicon Valley, the UK, and Germany.
After leading the demand generation for a 100+ million company, he decided to venture out on himself. He’s now helping clients to attract and convert more leads and customers.
His main focus are SEO, paid media & marketing automation – all with the focus to tie marketing campaigns to revenue.
Sascha has been featured in industry publications.