No matter how hard you try, your email list will always, always, always encounter two things:
A lead scoring model is a system that assigns customers with scores to indicate the potential sales opportunity they present. A lead score is usually a number between 1-100. A higher point value suggests that the lead is very likely to convert into a paying customer.
You can determine a lead’s score by evaluating specific signals like how much personal information leads provide, how often they’ve submitted online forms or their social media engagement with the company like shares and retweets.
Lead scoring helps a company develop an effective marketing plan to improve sales and align with the market.
Keep reading to discover the elements of lead scoring models and examples.
What makes a lead scoring model?
A good lead scoring model must accurately classify leads based on set lead actions and behavior continuously. The model uses demographic data, behavioral, user action, and other relevant data to assign relevant scores to potential clients.
Capturing all relevant signals in your lead scoring model helps determine when a lead is ripe for conversion. An effective lead scoring model ensures that the marketing team hands over qualified leads to the sales team. It shortens the sales cycle and helps to utilize business resources productively.
The following elements are crucial to the success of any lead scoring model.
1. Behavior scoring element
Classifying leads using their behavior helps companies create better marketing and sales plans for their potential clients.
Behavioral or implicit scoring gives a value to an indirect user action that implies their level of interest in a company’s product, like following a company’s social media page.
Implicit scoring differs from explicit lead scoring, which values facts like job title.
Identifying and valuing both implicit and explicit client information contribute to a lead scoring model’s success.
2. Effective marketing and sales collaboration
Lead scoring is a collaborative venture between sales and marketing teams. The teams work together to develop a robust lead scoring criteria.
Aligning the sales and marketing teams will improve the scoring quality, enhance lead qualification standards, and streamline lead sorting processes.
When the sales and marketing teams cooperate effectively, prospective leads’ sorting, assigning, and onboarding becomes faster and more efficient.
3. Demographic scoring element
The potential buyer persona determines the type of demographic scoring model a company develops.
Demographic scoring gives a score to leads from socioeconomic groupings who have the highest conversion potential. Demographic markers include industry, age, nationality, and job titles.
Demographic scoring improves the lead qualification process by allowing businesses to focus on customers with high conversion potential.
4. Negative score element
Customer information based only on desirable targets and actions may give skewed results over time. A good lead score model should have a corrective feature to identify false high scores.
Negative scoring excludes leads that don’t show a high potential of converting or leads that don’t qualify to be mapped in the lead scoring model. For example, when a customer unsubscribes from your email list, their score lowers.
A negative score is a corrective action that aims to correct bias in the lead data collection process. It helps a company enhance its lead database.
Negative scoring ensures that companies only target client’s with the highest conversion probability or those who genuinely need a company’s product or services.
5. Accurate scoring weights
Not all user actions carry the same weight. Some actions may be more promising than others, depending on a company lead scoring model.
Assigning different weights to various user actions helps a business calculate a lead score correctly. Lead data with the right scoring weight enables a company to accurately segment its leads and take the appropriate action to convert them.
Accurate lead weighting allows a company only to deploy assets to the most relevant leads. The business uses its resources to convert the most sales-ready lead efficiently.
A user who likes a company’s Facebook post is not as sales-ready as one who fills out a subscription form. Classifying the two types of leads will improve conversion success.
6. Score degradation element
Over time leads may grow cold, and user engagement may drop. The reduced interest may be due to different reasons which the lead scoring model needs to reflect.
Lead degradation refers to lowering the score because of reduced engagement with the company’s product. When a client stops opening promotional emails or engaging on social media, their score should fall.
A score degradation element should signal upward or downward trends to the sales teams for corrective action.
Lead scoring model examples
A company can use different lead scoring data points based on their target leads, buyer persona, and product.
Here are a few lead scoring models.
1. Email engagement
Emails are easy to track and provide reliable business data used to tailor products for potential clients.
Email lead scoring is an excellent tool for improving a business’s click-through rates and conversions. Emails communicate directly to the lead and create numerous avenues for positive user action.
Email lead scoring depends on set parameters that accurately describe how leads interact with emails.
Look at examples of email engagement parameters.
Clicking on a product link
A customer clicking a product link shows a high transactional intent. Such a client is ripe for conversion and warrants a higher lead score than a client who ignores the product link. The model can award 5 points for clicking on links.
When the lead’s total score reaches a set threshold (a score that shows the client is ready to buy), the sales team can take over to convert them.
Email open rate
How often a lead opens company emails is a good indicator of their interest in a product or service.
The model awards some points when a lead opens a newsletter. A lead with a high email open rate signals sales teams to ramp up their conversion efforts for that particular lead.
Multiple visits to an email
Award a point every time a lead visits your email. Numerous visits to an email show clear intent from the lead.
A client who opens the same email several times and their subsequent actions will likely raise their score.
2. Website visits
Companies effectively engage potential clients through their websites. Website activity by site visitors is a good measure of how interested they are in company products.
A company can concentrate on the following metrics to score a customer’s online activity.
High-value page visits
Different pages on a company’s site carry different scoring weights.
High-value pages like pricing pages have a higher lead conversion value than an “about us” page. A lead visiting high-value pages is more sales-ready and likely to convert. You, therefore, award specific points to opening these pages.
Knowing which pages clients visit on a website demonstrates their level of interest in a product or service.
Time spent on company pages
The time spent by a lead visiting a company’s pages is a good measure of their interest.
A lead with a high bounce rate is usually a cold lead with little interest in a company’s products. You can even assign a negative score to a high bounce rate.
Leads who spend considerably longer periods on a company’s site are hotter and may convert more easily. For these, you award some points.
Scoring leads based on on-site visit duration helps companies segment their leads more accurately.
The number of pages visited
Leads who visit multiple pages are generally more qualified than a single page visitor.
If each page visit is assigned a value, then a multiple page visitor will automatically have more scoring weight and more likely convert than a single page visitor.
3. Demographic analysis
Each company has a unique buyer persona that they target depending on their products and services. A high demographic score means that leads fit a company’s ideal buyer persona.
Demographic score aims to showcase the leads who match a company’s unique buyer person. Demographic scoring considers information like age, income, employment, and more.
Here are a few of the unique attributes demographic scoring considers.
Award points to a client who influences decision-making.
A senior-level employee will have a higher score compared to a junior employee. For example, a company president is more likely to influence a company’s conversion than a junior analyst.
The type of goods and services a business provides determines which department they target. A software company will award some points to a client in the IT department.
Enhance lead scoring with data enrichment
A lead scoring model is a powerful tool that helps companies to optimize the sales funnel.
A lead scoring model uses behavior scoring, marketing, sales collaboration, demographic data, and negative scores to assign scores to potential customers.
Different lead models, including email engagement, website visits, or demographic analysis, provide actionable data to the sales team. But a lead scoring model functions if the data is up-to-date and accurate.
Trust Datagma for all your data enrichment needs.
Datagma uses cutting-edge technology and innovative products to enrich your business data.
Datagma will help you identify what data needs enriching to develop an efficient lead scoring model.
If you’re looking for a partner who will strive to deliver expert data services that are tailored specifically for your company, contact us right now.