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Lead Scoring

Lead scoring is an approach to ranking leads based on their value to a firm, which supports marketing and sales activities. It helps qualify leads and indicate whether efforts should be devoted to market to a lead, as well as the movement of the lead throughout their journey and, potentially, if and when they reach the purchase stage.

Many approaches exist to score leads, such as the following:

  • BANT: budget, authority, need, timeline
  • MEDDIC: metrics, economic buyer, decision criteria, decision process, identify pain, champion
  • CHAMP: challenges, authority, money, priority
  • GPCTBA/C&I: goals, plans, challenges, timeline, budget, authority/negative consequences and positive implications
  • ANUM: authority, need, urgency, money
  • FAINT: funds, authority, interest, need, timing

Lead scoring approaches use data collected by the firm (e.g., using forms) as well as behavioral data collected during the interactions of leads with the firm (e.g., whether or not the lead opens an email, requests a call, or views a product). We will group these types of data under “observable or explicit characteristics” and “behaviors or implicit characteristics.” Either type of data helps the firm know whether a consumer is interested in them and whether it should devote efforts marketing to them.

Observable or explicit characteristics represent data that a firm can readily collect by asking consumers or observing them (e.g., on their LinkedIn profile). This data is typically collected by simply asking consumers for it (for example, by using a form or during a phone call) or by looking them up online. Examples of such characteristics include the following:

  • job title
  • firm size
  • personal or firm revenue
  • company size

Marketo offers more than 50 observable/explicit characteristics in their lead scoring guide (p. 18).

Behavioral or implicit characteristics represent data acquired through the tracking of online activities to measure the interest of a lead in a firm’s product or service. This data is typically collected when a lead visits the firm’s website, interacts with its emails, and responds to offers. Examples of such data points include the following:

Marketo offers more than 200 behavioral/implicit characteristics in their lead scoring guide (pp. 19–20).

Lead scoring entails first identifying the data that a firm believes is relevant to scoring leads. This process will greatly vary depending on the firm. Questions such as “Who is responsible for making purchases?”, “Does my consumer need to have a certain revenue to buy my product?” or “What kind of actions can I make consumers take that show that they have an interest in my product?” can help identify how to score leads. Once the right characteristics have been identified, firms will typically assign a weight to them. For example, having the right job title might be worth less than viewing a product demo or requesting a sales call. By assigning points to each characteristic, a firm can establish whether a lead is qualified and how a lead is moving through their journey. Leads with a certain score can be identified as marketing-qualified, while leads that later reach a higher score can be identified as sales-qualified.

An example of a lead scoring framework that has historically been heavily used by firms throughout the world is the BANT (budget-authority-need-timeline) framework. We use this framework here to exemplify how to perform lead scoring when focusing on observable or explicit characteristics. For example, to create a lead score, a firm could create forms or collect data during calls with potential customers and ask questions such as the following:

  • Budget: What is the budget of the potential customer? How does it align with my product or service?
    • Questions to ask the lead:
      • Do you have a budget set aside for this purchase? What is it?
      • Is this an important enough priority to allocate funds toward?
      • What other initiatives are you spending money on?
      • Does seasonality affect your funding?
  • Authority: Who makes the decision to purchase?
    • Questions to ask the lead:
      • Whose budget does this purchase come out of?
      • Who else will be involved in the purchasing decision?
      • How have you made purchasing decisions for products similar to ours in the past?
      • What objections to this purchase do you anticipate encountering? How do you think we can best handle them?
  • Need: What is the need of the lead? Can my product or service answer this need?
    • Questions to ask the lead:
      • What challenges are you struggling with?
      • What’s the source of that pain, and why do you feel it’s worth spending time on?
      • Why hasn’t it been addressed before?
      • What do you think could solve this problem? Why?
  • Timeline: What is the purchase timeline of the lead? How does this align with my sales process?
    • How quickly do you need to solve your problem?
    • What else is a priority for you?
    • Are you evaluating any other similar products or services?
    • Do you have the capacity to implement this product right now?

Last, it is important to emphasize the role of progressive profiling, the idea that you should collect information from potential customers throughout their interactions with your firm. As we saw earlier, you can’t ask a lot from visitors when they fill out a form without hindering the conversion of visitors to leads. How, then, do you collect this information? By slowly collecting bits and pieces over time. This can be done, for example, through the use of progressive profiling technology and dynamic forms, where a firm sets up ahead of time many forms that iteratively collect information based on what a consumer will have provided on a previous form. Put differently, if consumers give their name and email in the first form, the second form will move to asking for pieces of information that have yet to be obtained. Another approach is to combine explicit and implicit scoring and score a lead over time as they interact with a firm’s website.