Setting Up Lead Scoring
What Is Lead Scoring?
Lead scoring is the process of ranking leads to identify which leads are ready to move to sales and which leads require further nurturing. So you would assign a score to each lead based on various attributes, including the interest they show in your business, and their current place in the buying cycle. This score can later be used to qualify leads for sales outreach and for refining your marketing messages.
The main goal of lead scoring is to sort highly qualified potential customers from the rest. Once sorted, marketers can take special steps to increase the rate at which those qualified leads become customers. Businesses of all types can use lead scoring to determine whether prospects need to be fast-tracked to sales or developed with lead nurturing.
Most of the lead scoring approaches use some sort of algorithm to determine lead qualification. Lead scoring algorithms can be created using marketing automation tools. Marketers may even opt for a third-party lead scoring tool that can integrate with an existing marketing automation platform. Hence, using a lead-scoring algorithm helps marketers automate what would otherwise be a time-consuming task and also helps to improve customer experience.
Need For Lead Scoring
Improves Funnel Efficiency
The top of a typical marketing funnel consists of several leads but as we proceed down the funnel leads may be removed because potential customers become uninterested or you determine their lack of fit. An efficient funnel can attract and close the right customers quickly. This is where lead scoring comes into the picture, it improves the efficiency of the funnel.
Improves Time Management
Initially, marketers are worried about getting enough new leads in the funnel and once they have a lot of leads, it is necessary to figure out who's interested in the product and who's just starting to look around. But lead scoring helps solve this problem as it identifies the leads that will be the easiest to reach and who have the highest potential of becoming clients. Hence lead scoring can ensure that your sales team uses their time efficiently by focusing only on leads that are likely to become customers, which may lead to higher conversion or close rate.
The Backbone Of Lead Nurturing
The marketing and sales need to get together to develop a lead scoring strategy, to pinpoint where a particular lead is within your brand’s buying model. Lead scoring is the backbone of a strong lead nurturing system because it identifies when and how to address each buyer with the most timely and relevant communications. Additional nurturing may be required by lower-scoring leads to enhance their interest and engagement. You can segment your leads with a range of scores, then drop them into nurturing campaigns built specifically to develop them into sales-ready leads using marketing automation.
Standardized Evaluation Of Leads
Assigning a score to each lead helps you to understand the characteristics of your customers and the pattern of behavior that leads to a purchase. So lead scoring provides marketing and sales a common language for discussing the quality and quantity of leads, they’ll naturally align themselves. Marketing will have a numerical value of how important each lead factor is, so they can alter their inbound marketing to target specific factors to generate more leads that match specific criteria.
How to Score Your Leads
Depending on your industry and target audience the details of the lead scoring system may vary. However, the following are the dimensions of lead scoring that should be evaluated as you develop your strategy.
Lead fit describes how well a particular lead matches the brand’s ideal buyer. The following are three categories that will tell you if a lead is worth pursuing :
Demographics —The buyer’s job title, company size, location, years of experience, income level, etc play a major role in any lead scoring model.
Firmographics —The company’s name, location, annual revenue, size, etc. We can say, firmographics are to businesses and organizations what demographics are to people.
Budget, Authority, Need, Time (BANT) — It's a framework that can be used to determine how qualified a lead is to work with your company and determine which leads should be prioritized.
Now consider this example :
You have two visitors to your marketing site - visitor A, a CEO of a 100+ employee fintech company, lands on your site through a Google search for your company name. They visit the “Product”, “Pricing”, and “Customers” pages, read three articles on your blog, and enter their information into a lead form for an upcoming webinar.
Another visitor B, a sales rep from a 5-person marketing startup, lands on your site through a Google search for your company name. They visit the “Product”, “Pricing”, and “Customers” pages, read three articles on your blog, and enter their information into a lead form for an upcoming webinar.
You can notice that the activity is the same, but the person is not. Lead scoring has to over-weight the CEO in this scenario so that this prospect is quickly brought to the attention of the sales team.
This demographic score is the most important part of your lead score as you can assign large weights to your ideal customer profile criteria. If your ideal customer profile is a large fintech company, then it's important that no matter what their behavior, your sales team is alerted to the interest of a qualified lead.
The next stage of lead scoring is to determine the lead’s interest in your company by tracking their online behavior. You can track the time spent by leads on your site and leads’ engagement with the social networks. A study found that 95% of people between the ages of 18 and 34 are more engaged with brands on social media. So you can assign numerical values accordingly to each behavior and use these scores for lead evaluation.
- Number of Web Page Views
- Duration of Webinar Attendance
- Number of Emails Opened
Lead Behavior/Engagement Score
When prospects start engaging with any services of your company, from reading a blog post to filling out a survey, each of these actions gives you insight into what they want. This lead behavior will help you identify if a lead is serious about buying or just grabbing information about your company. Now prioritize leads appropriately based on the collected information.
- Product Demo Request
- Video View
- White Paper Download
- Email Click-through
To understand scoring based on lead behavior consider this example:
You have two visitors to your marketing site, visitor A lands on your site through a Google search for your company name, they visit the “Product”, “Pricing”, and “Customers” pages, read three articles on your blog, and enter their information into a lead form for an upcoming webinar.
On the other hand, visitor B comes to your site through a keyword search, visits your “Pricing” page, reads a single blog article, then leaves.
From these descriptions, it is clear that Visitor A has a higher interest in your product than Visitor B. If in the above example each page visit was worth +1, a direct referral +2, and form submission +3, visitor A would score +11 while visitor B would only score +2. This component of lead scoring is based on the lead’s behavior.
Now if you set your threshold for contact at +10, your sales team could then be flagged about the interest of visitor A. They could then reach out immediately with the information from the lead form.
Ask yourself the following questions:
- Which ones have been with you the longest?
- Who has spent the most money with you?
- Who was a breeze to sell to and have productive conversations with?
Negative criteria serve as the checks-and-balances of your lead scoring matrix, adjusting your lead score in response to factors that might make a lead less desirable.
The following are examples of negative criteria you should consider:
- Lack of response to marketing messages
- Unsubscribing from an email list
- Requesting to be added to your do-not-contact list
- No decision-making authority
- Defined periods of inactivity
- Visits to certain pages (e.g., your Careers page)
How to Calculate Lead Score?
Calculating a basic lead score is not that tough with the help of lead scoring models. The following are techniques for calculating the lead score :
Manual Lead Scoring
This technique for calculating the lead score is quite a time-consuming approach, you first calculate the lead-to-customer conversion rate of all your leads. The lead-to-customer conversion rate is equal to the number of successful sales divided by the number of total visitors.
Now choose different attributes for customers who can become higher quality leads. You can pick these attributes with the help of your sales team and your analytical data. Next, calculate close rates for each of the selected customer attributes and then compare the close rates of each attribute with your overall close rate. Now find the attributes with close rates that are significantly higher than your overall close rate and choose which attributes to which you will assign point values based on the magnitude of their close rates. Hence in this way, you can manually calculate the lead score for all your leads.
Logistic Regression Lead Scoring
The above method is labor-intensive so in this technique, the system builds off the work you have done with manual lead scoring. The logistic regression technique is more mathematically advanced and complex, it builds a formula in Excel that inputs customer attributes — like industry, and company size weighs the importance of each, and calculates the probability of a lead converting into a customer. This is more accurate than the other methods as its formula monitors past behavior and attempts to apply learnings to every new customer that enters the sales funnel.
Predictive Lead Scoring
This lead scoring technique uses machine learning to automatically assign scores to leads based on all your past opportunities and identifies what attributes lead to a close. Predictive lead scoring builds a formula to sort all your leads based on their potential to convert. This sorting helps the sales team to prioritize the leads easily, then focus on the higher priority leads. Also, the use of machine learning makes your predictive score get smarter over time because your predictive lead scoring system will constantly update without you having to do so manually.
- Setting Up Lead Scoring
- What Is Lead Scoring?
- Need For Lead Scoring
- How to Score Your Leads
- How to Calculate Lead Score?