How to establish and refine Lead Score framework
Lead Score framework is the cornerstone of a business-to-business marketing and sales process. Lead score indicates the potential of a lead to convert to sale, and therefore, it dictates how a lead is handled on its way to sale.
Lead score is a component of any major marketing automation platform. Typically lead scoring system contains the following two components:
Demographic (including firmographic): This includes variables such as Title, Company size, Industry, Geography, et cetera.
Behavioral: How the lead has interacted with your marketing channels such as website, thereby indicating its interest in your product. Examples include: Visiting web pages, Opening / clicking emails, downloading eBooks and white papers, origin of the lead (lead source), and attending webinars.
Both demographic and behavioral variables can be negative as well. Example of negative demographic variable include submission of a generic email instead of company email. Examples of negative behavioral variables include opting out of emails, a period of inactivity, and unanswered phone calls.
Once a lead is acquired, its demographic score does not change much (assuming all the demographic fields are populated). However, Behavioral scores can change as the prospect gets more interested in your business and visits more web pages and downloads more resources.
If you are implementing lead score framework for the first time, you may be wondering how to start with lead scores. The key is to start small with few variables, and expand as you get a feel of what is important for your business. Your marketing automation vendor is a good resource to call upon to get initial lead scores for companies like yours. Then work with your Sales and refine these initial lead scores before inputting into the marketing automation system.
Also, a good practice is to cap both demographic and behavioral lead score totals so that one does not dominate the other. For example, a maximum of 100 for demographic and 100 for behavioral.
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For behavioral scores, the deeper into the marketing funnel a given activity is relatable, higher its lead score. For example, top of the funnel activities like visiting home page, opening emails, and watching a short video will get low scores (say 1 or 2). In contrast, bottom of the funnel activities like visiting pricing page, downloading a white paper comparing your products to competition, or attending a product demo will receive much higher lead scores (say 10 or 15).
A key milestone in the marketing funnel is the score at which the lead reaches the “Marketing Qualified Lead” (MQL) status. This is the stage at which the lead is ready to be handed over to Sales (typically Sales Development Rep). If this threshold score is chosen correctly, the lead will be ready to have a conversation and will not have to be flagged “not ready”. If there are too many “not ready” statuses following initial calls, the MQL score need to be adjusted up. Working together with sales team on a continual basis is important for this adjustment.
Once you have the preliminary lead score framework going, you can refine the scoring system using real insights. After the end of a quarter is a good time to do it so you have full quarter’s worth of data to look at. Following guidelines will help:
- Create a table with lists of campaigns and related leads and opportunities (as below). This will give an idea of which campaigns were the most effective in converting a lead to opportunity. Higher conversion means higher lead scores for the associated behaviors
- From your leads database, create a frequency chart with lead score ranges in x axis (like 0-9, 10-19 etc.) and number of leads in the y axis. If you have a perfect lead score framework, this chart will look like a normal distribution. If not, see what changes you can make to lead scores to make the distribution closer to normal distribution.
- Look at all new Opportunities created the previous quarter (if too many, use a random sample) and see the demographic and behavioral traits of each lead. Have a working meeting with Sales to see the common traits of high performing (and low performing) leads and adjust lead scores of variables up or down.
Also, it is important to create a written record of the lead score changes over time, so there can be a self-correction mechanism in the future.