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The best lead scoring models have these 7 factors

By Josh Bean, Director, marketing

Published February 20, 2020
Last modified February 20, 2020

A business can’t thrive without lead generation, however, the more leads you generate, the more selective you have to be in your pursuits. Sales rep don’t want to waste time chasing a large list of dead-end leads. That time could be spent nurturing more promising leads.

Yet, when it comes to valuing leads, how do you separate the wheat from the chaff? Experience and gut instinct goes a long way, but they aren’t enough. To consistently find strong potential customers, sales reps need a lead scoring model.

What the best lead scoring models have in common

A lead scoring model is a system for evaluating leads. You give points to a lead based on a number of different factors, such as the industry the lead works in or their level of interest in your product. Qualities that are associated with past high-value leads have more points.

With this model, you’re able to quickly identify leads that are the ripest for a potential sale and which leads should be considered a low priority. We’ve already examined how to score leads. Here we’ll look at the seven factors that all robust lead scoring models have in common.

1. Alignment between marketing and sales

If marketing and sales aren’t on the same page about your lead scoring model, some great leads might fall through the cracks. Or, some not-so-great leads that were mistakenly considered qualified will make their way through, sending sales reps on wild good chases.

To ensure that there are no leaks in your sales funnel, have sales and marketing work together to develop the scoring criteria and lead scoring threshold (see the section below) for your model. If any team member makes changes to the model, clearly communicate those updates to both departments. With this communication, your marketing department will be able to identify strong prospects and refer them to sales.

2. A lead scoring threshold

A lead scoring threshold refers to the point value where a prospect is considered sales-ready. When a lead’s score reaches or exceeds this amount, they become a marketing qualified lead, or MQL, and are passed from marketing to sales.

It’s important to get your threshold right. If the bar for entry is too low and leads are being qualified prematurely, sales reps will have a frustrating time going after prospects that aren’t ready to be pursued. But raise the bar too high and you risk sitting on valuable leads for too long and giving them time to be snatched up by a competitor.

You should determine your threshold in part by looking to what historical data has told you about which characteristics (or combination of characteristics) mark a lead as qualified. For example, if requesting a product demo is the number one indicator that a lead will eventually convert into a sale, your lead scoring threshold should be set so that any lead who requests a demo will be assigned enough points to immediately become an MQL.

Once you’ve set a threshold, you can set up your CRM to automatically notify you when a lead receives that many points.

3. Explicit scoring

With explicit scoring, you assign points to a lead based on specific objective qualities, such as firmographic or demographic details. Examples of explicit characteristics include:

  • ตำแหน่งงาน
  • Role
  • Level of seniority
  • Experience in the industry
  • อุตสาหกรรม
  • ขนาดบริษัท
  • Company revenue
  • Geographic location

These clear-cut factors offer a simple way to evaluate leads. For example, if your ideal customer is a C-suite executive from a large tech company, you can check leads’ company sizes and industries to see if they are a good fit.

Sometimes a lead will volunteer the information that you need for explicit scoring—for example, filling out a questionnaire to download gated content from your website. Or the info may be uncovered by research, which could involve checking out a prospect’s LinkedIn page or company website.

4. Implicit scoring

On the other hand, implicit scoring refers to the points you award to a lead based on their behavior, such as:

  • Website visits
  • Social media interactions
  • Email opens/clicks
  • Newsletter subscriptions
  • Contact requests
  • Contact form submissions
  • Content downloads
  • สัมมนาผ่านเว็บ
  • Free trials/product demos

Say, for example, someone downloads an eBook from your company. You should award points for the very act of downloading the eBook, since you can infer from that interaction that the prospect has a certain level of interest in your company.

You can use CRM to track every interaction a customer has with your company.

Implicit scoring often contributes more to a lead’s overall score than explicit scoring. A prospect can only be scored once for their job title, but will be scored every time that they download a piece of content or open an email.

5. Negative scoring

Not every interaction a prospect has with your company is a step in the buyer’s journey, and your lead scoring model needs to recognize that. Negative scoring is a way of removing points from a lead score based on actions or characteristics that indicate a waning or complete lack of interest, which could include:

  • Unsubscribing from your email list
  • Visiting your careers page (implying they are interested in becoming an employee, not a customer)
  • A job title (like “student” or “retired”) or industry that has nothing to do with your product or service, suggesting they are interested in your content for purely academic reasons
  • A rival company (suggesting that the person is just researching the competition)

Negative behaviors are especially important for avoiding deceptively high lead scores. A lead seems to have a healthy score based on their qualities, like their industry, but their actions show they’re increasingly losing interest in your brand. With negative scoring, sales reps can recognize these weak leads and focus on nurturing stronger potential customers instead.

Marketing and sales must work together to create a list of all the red flags that indicate a prospect isn’t likely to convert. Both departments should have valuable insights, and collaborating can help them remain aligned. Assign a negative point value to each of the traits and actions, based on how common they are across past leads who have left your pipeline, and dock a lead points when they display the characteristics or behaviors in question.

6. Score degradation

When it comes to prospect interactions, no news is bad news. Ideally, you want to see leads moving through your sales funnel, not getting stuck at a certain stage and never progressing.

Score degradation helps you track stagnant leads. You lower a lead’s score if they haven’t interacted with your brand over a significant period of time. For example, you might lower a lead’s score if they stop opening your company’s email or download one piece of content but never interact with the site again. Like negative scoring, score degradation helps you pick out bad eggs and focus on more valuable leads.

To use score degradation, decide which actions should warrant point deductions when the lead stops doing them. As a starting point, consider reversing the point system you use for implicit scoring. If a lead gets 10 points for subscribing to your newsletter, they lose 10 points for unsubscribing. Or, consult your marketing team to understand which actions promising leads do consistently.

7. Regular refinement

The motto of a good lead scoring model is not “set it and forget it”—it’s “design it and refine it.”

To keep your lead scoring model as accurate as possible, continually update your scoring methods based on the most recent customer data. For example, if lots of leads are getting qualified but very few are being converted by the sales department, it’s very likely that the lead scoring threshold is too low. Or, if you notice sales from one type of persona or prospect behavior are increasing or decreasing, the way you weigh those variables may need to change.

How do you know when you need to update your lead scoring model? Check to see if your MQL-to-conversion rate is declining. If it is, there’s a good chance your target customer profile has shifted and your scoring model needs to be adjusted.

Making the most of your lead scoring model

Lead scoring allows sales reps to work smarter, not harder when it comes to pursuing prospects. Focusing solely on qualified leads saves you the time and frustration that comes from trying to reach and convert prospects that just aren’t ready, and maybe never will be. But remember, a lead scoring model requires some maintenance. If it seems like your leads are being over- or under-valued, check your customer data to see if your model needs to be adjusted.

Don’t have time to create a manual lead scoring model? Consider using a CRM that automatically creates and updates lead scoring models.