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How to Create a Lead Scoring Model

A lead scoring model is an integral supporting pillar of an inbound marketing campaign. It filters out high-priority prospects from lead nurturing campaigns, delivers them to the sales team, and ensures conversion.

According to a 2021 survey by Hubspot, 40% of sales professionals say that sales prospecting is the most exhausting part of a marketing process. It is because most sales teams pitch to prospects that are still in the awareness or consideration stage. All this results in low conversion rates.

A lead scoring model solves this problem by creating sales cycles that are more accurate. It follows a simple mechanism that keeps an eye on the prospect’s activities and alerts the sales team only when a lead reaches a high-buying intent.

But how does lead scoring work?

This article aims to answer all your questions related to lead scoring and provide you with the best way to create a lead scoring model that boosts your sales productivity and helps you achieve your conversion targets.

What is a Lead Scoring Model?

Lead scoring is a grading method used for awarding ‘points' to different marketing leads based on their sales-readiness.

The points get assigned to leads based on various actions they perform that move them closer to the buying stage. For example, if a prospect downloads an e-book, they get 3 points. If they visit the pricing page two times, they gain 10 points, making the overall score 13.

A lead scoring model customises the grading method according to a company’s requirements. For example, a B2B company will be more interested in the lead’s firmographics and make a lead scoring system that weighs a visitor’s job title, company name, size, etc., more than other factors. In comparison, a B2C company would focus more on the prospect’s age, name, DOB, etc., while building their scoring system.

Why is a Lead Scoring Model Essential?

Lead scoring models are essential in marketing because they help identify strong quality of leads and establish a more focused approach for converting them into buyers. It assists in saving your team's time and allows them to work on other crucial tasks, increasing your company's overall efficiency.

Other prominent benefits that lead scoring provides are:

1. Lowers Customer Acquisition Cost (CAC)

By analysing your lead scoring models, you can recognise and eliminate the channels that do not provide relevant returns. It lowers your customer acquisition cost (CAC) and boosts your ROI.

2. Removes Guesswork From a Sales Cycle

Conventionally, marketers have relied on gut feeling for qualifying sales-ready leads. Methods like lead scoring reduce guesswork from the marketing equation. It shares score-wise data that helps in differentiating between weak and strong leads.

3. Streamlines Marketing and Sales

For setting up a lead scoring model, marketing and sales teams have to come together. Activities like formulating a scoring system, deciding the sales-ready lead qualifying score, etc., help make your sales and marketing team come under the same flow and avoid any leak in the sales funnel.

Lead scoring can help you drive your market growth. An ActiveCampaign case study about the success of a taxi-service company, Sneleentaxi, proves this. They efficiently utilised site tracking and lead scoring to isolate 200 prospective leads and raise 0.5M Euros in two months.

Incorporating the type of content can further enhance the lead scoring process by considering factors such as engagement levels, content preferences, and interaction patterns.

Factors That Make Up a Successful Lead Scoring Model

A lead scoring model judges leads based on a scoring system set up by you. Most scoring systems have the same parameters that award points to a prospect. While the parameters can remain the same, every company can prioritise which activity offers high and low points.

Below are the factors that you must consider for setting up a successful lead scoring campaign:

Score Threshold
Implicit Scoring
Explicit Scoring
Lead Segmentation
Negative Scoring
Timely Updates
Automation

1. Score Threshold

A threshold in lead scoring represents a score after which you consider a prospect sales qualified. Based on your scoring system, it can be 50, 150, 200, or any other number.

Choose a lead scoring threshold based on your sales historical data. Try to follow up on the activities that result in high customer yield.

For example, a B2B company identifies a prospect with a higher chance of conversion after booking a discovery call. The company sets their lead scoring model so that any lead who books a discovery call automatically becomes sales-qualified.

2. Implicit Scoring

Implicit scoring deals with the potential customers' online behaviour. It measures how enthusiastically a lead is interacting with your brand.
Some of the implicit scoring parameters can be:

Emails opened and clicked
Website visits
Resources downloaded
Webinars attendance
Signed up for a free demo/ trial
Social media engagement
Newsletter subscription

Depending on your company’s requirements, you can award points based on various implicit activities discussed above.

A prospect’s preference can change from time to time. Implicit scoring helps you keep track of it and not miss out on any ready-to-buy behaviour.

3. Explicit Scoring

Explicit scoring helps you assign scores based on a lead's personal and professional qualities. It covers many factors like demographics, firmographic data, transactional, etc.

Some of the explicit scoring parameters are:

Job title
Company name
Location
Industry
Company Size
Revenue
Age
DOB

Marketers use lead magnets and social media sites like LinkedIn for gathering such information about a prospect.

Explicit scores mostly remain static as the attributes of a consumer don’t change fast. It sometimes results in alloting higher scores to explicit parameters. For example, a SaaS company will give +100 points to a lead if their job title is CEO.

4. Engagement Scoring

Engagement scoring helps you keep up with the leads that have a higher buying intent by introducing time as a factor. It allows awarding and deduction of points based on a prospect’s current activities.

For example, a lead got awarded 10 points for downloading an e-book. Two cases can arise from here:

If the lead revisits the site in 3-5 days, they get awarded 5 points. It results in a total score of 15 points.
If the lead remains inactive for more than one month, they get a deduction of 5 points. It results in a total score of 5 points.

Engagement scoring balances your active and inactive leads, further refining the lead scoring process.

5. Predictive Scoring

Predictive lead scoring models use advanced analytics techniques, such as machine learning algorithms, to analyze historical data and identify patterns that predict lead quality or likelihood of conversion. These models can incorporate a combination of demographic, firmographic, and behavioral data to generate accurate lead scores.

6. Negative Scoring

Engagement scoring helps you keep up with the valuable leads that have a higher buying intent by introducing time as a factor. It allows awarding and deduction of points based on a prospect's current activities.

It weighs in parameters like:

Unsubscribed from the emails
Visiting the career page (might be looking for a job)
Job title (student, teacher, or retired)
From a rival company

Negative scoring prevents your leads from having high lead scores and allows you to focus only on prospects with a healthy score.

7. Timely Updates

It is vital to update your lead scoring model timely. It is so because consumer behaviour changes rapidly, and your marketing workflow should always be ready to tackle it. By refining your lead scoring system, now and then, with the latest prospect and customer data, you can keep the efficiency of your sales system constant.

For example, if you notice that you have a long list of qualified leads, only a few are converting into buyers. Then it is time to revisit your lead scoring board.

How To Design a Lead Scoring Model

Till now, I have discussed everything required for developing an efficient lead scoring model. Let’s put that knowledge to use and create a lead scoring model for an email nurturing campaign.

Step 1: Checking Historical Data

Historical data holds a critical relevance in designing a lead scoring model. By understanding your established clients’ buyers’ journey, you can see the actions that triggered them into becoming sales-qualified leads and then a buyer.

Step 2: Setting Scores

In step 2, you must assign points to different prospect actions and attributes.
Below I have done the same for my emailing campaign.

Implicit Scoring List

Explicit Scoring List

The expiry (days) column represents the validity of the points awarded by performing an action. For example, if the lead opened the Calendly link but had no further engagements with it for the next 14 days, the awarded scores are taken back.

Step 3: Setting Threshold

You are now ready to set up a threshold for your lead scoring model with all your information. Based on the historical data and your score awarding system, you can divide leads into three categories:

Cold Leads: Prospects with a lead score lower than 60 get categorized as cold leads and monitored for further activities.‍

Warm Leads: Prospects having a lead score greater than 60 but lower than 120 get categorised as warm leads. Such leads are added to long-term nurturing programs.‍

Hot Leads: Prospects having a score higher than 120 go to the sales team.

Step 4: Deploying and Updating

After setting everything discussed, you can deploy your lead scoring model. Choose a marketing automation tool like ActiveCampaign, Hubspot, Marketo, or Pardot for executing your scoring system. These tools align your CRM processes with lead scoring, making it easier to monitor everything. Update your system according to market needs.

Conclusion

A lead nurturing model is not hard to develop if you understand your target audience. You can do it by analysing your marketing and sales historical data. It will help you design a lead scoring system aligned with your lead nurturing requirements. A lead scoring program ensures that a sales team effectively utilise their time by sharing ready-to-buy leads.

With the help of explicit, implicit, and engagement scoring, you can make precise lead scoring models. Remember to set different lead scoring systems for your existing clients and prospects.

If you want to know when is the right time to develop a lead scoring model for your lead nurturing program, then check out my blog: