Perfect Your Lead Scoring Model to Close Sales

A business needs lead generation to survive. Yet, the more leads you generate the more you have to be particular about your actions. Sales teams don’t want to be chasing a growing list of leads that result in a standstill when they could be nurturing more promising ones. However, how do you move from generating leads to valuing them? How do you properly manage your leads over time? For businesses to have a strong, consistent way of finding potential customers, they will need to develop a lead scoring model.

 

Lead Scoring Marketing Fundamentals

Your lead scoring model will be the system you use to evaluate your leads. Each lead is given a certain amount of points based on various factors such as their demographic, industry, and level of interest in your product or brand. As you gather data from past, high-quality leads, you will also be able to determine the qualities that amount to more points.

Using this model, you will be able to quickly discern which leads are worth pursuing and which are less of a priority, giving you the momentum and the insight you need to make a sale. This process helps sales and marketing teams prioritise leads, respond to them properly, and increase the rate of high-value lead conversions.

Lead Scoring Models

There are 6 different ways to score leads based on the category of information collected:

Demographic Information:

This information can typically be collected from your landing page and can range from age and gender to job position, region, country, etc. Demographic information can tell you whether to remove a lead from your sales funnel by subtracting points from people who fall under categories that don’t match your target demographic. For instance, if you only ship to a certain geographic location, you can give any lead that falls out of that demographic a negative score.

Company Information:

Information like company size, industry, type, etc. can help inform you as to who you want to sell to as a B2B company. This will also help you evaluate your leads to then rate and eliminate them.

Engagement Information:

Also understood as customer behaviour online, can show you whether a site visitor is interested in your product or not. Information can be collected through forms, the number of page visits, and which pages were visited on your site, to determine and assign point values. Higher points are given to leads that visit high-value pages, for a longer duration of time, whereas lesser engagement on your site can result in a deduction of points for that lead.

Email Engagement:

You can also decide how to rate leads based on the data collected from your email marketing campaigns. Email address engagement data is a great place to start lead scoring. Other indications of people’s interest can include email open rates and click-through rates.

Social Engagement:

Social media is one of the biggest platforms for customer engagement; therefore, the information gathered regarding how customers choose to engage with your brand can help guide your lead scoring. Social engagement information includes likes, shares, comments, or followers. Depending on a person’s level of engagement, you can assign the reciprocal amount of points.

Spam Detection:

Your landing page will help you identify whether a contact form has been filled out which has been categorised as spam. This will enable you to immediately assign them a lower score. Using this parameter, you can eliminate leads than never turn into prospects.

Elements That Contribute to a Good Lead Scoring Model

Here are a few elements that all durable lead scoring models have in common:

 

1. A strong lead scoring threshold: Understanding the point value wherein a prospect is officially sales-ready will help determine when a lead is ready to be moved from a marketing qualified lead (MQL) to a sales qualified lead (SQL). You should determine your point threshold based on historical customer behaviour and data, and which characteristics led to a qualified lead. Once you determine your point threshold, you can structure your CRM to notify you when a lead receives that number of points.
2. Alignment between sales and marketing: To ensure that your sales funnel has no cracks, sales and marketing have to share a unified understanding of the lead scoring system. Both teams need to take part in forming the lead scoring foundation; from developing the scoring criteria to finding the right lead scoring threshold.
3. A mix of explicit and implicit scoring: Explicit scoring involves scoring leads based on specific objective qualities such as job title, role, level of seniority, experience in the industry, industry, company size, company revenue, geographical location; whereas implicit scoring refers to points assigned to a lead based on their behaviour, for instance, website visits, social media interactions, email opens/clicks, newsletter subscriptions, contact requests, form submissions, content downloads, etc. Both scoring methods should be considered in your leads’ overall score. However, implicit scoring often contributes more to a lead’s overall score than explicit scoring.
4. Consistent refinement: You should update your lead scoring methods regularly to ensure that your lead scoring model is as accurate as possible. For example, if your lead scoring threshold is too high, you might be sitting on valuable leads allowing the competition to get to them first; however, if the bar for entry is set too low, sales will struggle by going after leads that aren’t ready to be pursued.

Make the Most Out of Customer Data

Your lead scoring model will work wonders in saving you time and energy when pursuing prospects. It will enable you to work smarter and close more sales by focusing solely on qualified leads. Your lead scoring model, however, will require maintenance. You should continually check in with customer data and trends to determine whether your leads are being over- or under-valued. If your model needs to be adjusted, remember to involve both sales and marketing to offer their lead evaluations and insights.