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Telemarketing

Understanding the Difference Between Traditional and Predictive Lead Scoring

Featured ImageJul 23, 2024

The telemarketing industry has seen significant improvements, largely due to third-party US calling data providers. Businesses now use refined data from these providers rather than relying on yellow pages. Lead scoring remains essential, and there are two main types: traditional and predictive lead scoring. Traditional lead scoring involves sales teams setting criteria and scoring leads based on explicit and implicit data. Predictive lead scoring uses scientific methods, analyzing historical and behavioral data through CRM and marketing automation to predict conversion probabilities. Traditional lead scoring is assumption-based and can result in fluctuating scores, while predictive lead scoring offers a more realistic, bounded, and nonlinear approach. Predictive lead scoring is preferred for its ability to analyze behavioral patterns and improve B2B sales and marketing efficiency.

There has been a tremendous improvement in the telemarketing industry in the past few years and most of the credit goes to third-party US calling data providers. Businesses no longer need to depend on the yellow pages and contact each name mentioned on the list. Though the data provided by specialist providers is refined to a great extent, the need for lead scoring still exists, which often brings in the dilemma to choose between traditional and predictive lead scoring. In this post, we discuss both the lead scoring types in detail and provide a brief comparison to help businesses make an informed decision.

Traditional Lead Scoring

Traditional lead scoring involves the participation of the sales team for identifying the criteria to determine lead quality, evaluating the prospects, and scoring them based on the established criteria. The score helps to identify leads that are more likely to convert. The sales team collects explicit and implicit information to score every lead. The explicit data contains details of the company, budget, area of work, and other relevant information. The implicit data consists of the digital behavior of the prospects by considering their emails and blog subscription, etc.

Predictive Lead Scoring

Predictive lead scoring involves a scientific method to determine the quality of lead and estimate the probability of conversion. CRM and marketing automation help to retrieve historical and behavioral data of the client. Other details used in predictive scoring include marketing action, company revenue, size, and demographic information.

Workings of the Scoring Systems

Traditional Lead Scoring

Three steps involved in setting up a traditional lead scoring system are:

  1. Determine the criteria to identify quality leads using the implicit and explicit information.
  2. Create a scale and point system to rate the lead based on the information received.
  3. Finalize a threshold score to filter out the leads that are ready to convert.

Predictive Lead Scoring

Here’s the process followed in setting up a predictive lead scoring system:

  1. Creation of lead profiles by referring to marketing and CRM databases.
  2. Review of the client’s website (if it is B2B) and other sources to find more valuable information about finances, sales, and marketing.
  3. Use predictive analysis to assess the profile of all the leads and determine the highest valued lead.
  4. Score every lead against the quality lead and find out the ones that will pass through the sales funnel and convert to customers.

Difference Between Traditional and Predictive Scoring

Comparing score based on assumption

Traditional lead scoring is an assumption-based process, wherein the sales and marketing team sits together to assign point values based on the actions taken by the lead. There could be 20 points given for a callback request or another 30 if the lead asks to send more data via email. It might look like a perfect scoring model but requesting a callback doesn’t result in a purchase.

Predictive lead scoring is more realistic as it is done by closely looking at the lead and understanding the profile. Scoring all the leads against each other makes it easier to filter out the leads that are closer to crossing the sales funnel. The explanation is simple - a lead with a predictive score of 8 has more probability of converting than a lead with a score of 3.

Comparing increasing scores with consistent ones

There are chances of leads building up hundreds of points over time when a business follows traditional lead scoring. The leads might have a high score and still won’t be near purchase. If the marketing team hasn’t built decay scoring campaigns and limiters, there will be a constant fluctuation in the scores.

Predictive lead scoring has a bounded scoring pattern, which means if the rating scale is 1-10, leads wouldn’t have a fluctuating score of 15 or 18, at any stage of the cycle.

Comparing linear correlation with non-linear correlation

Traditional lead scoring practice enables marketers to identify only the positive linear correlation between the behavior of the lead and willingness to buy. If 7 out of 10 leads who closed the deals, for instance, were VPs in their organizations, the traditional system would give more importance to all the leads that are VPs.

A predictive lead scoring system sees the nonlinear correlation for rating the potential clients. It analyzes the buying behavior of the lead, success ratio, and many more factors to rate them on the scale.

A Few Last Words

Businesses mostly opt for a predictive lead scoring system as it analyzes the behavioral pattern of the lead and presents a clearer picture of how far it would go in the sales funnel. It is considered to have an upper hand over the traditional methods, specifically for improving the efficiency of B2B sales and marketing. Should you wish to learn or have any questions, feel free to connect with us for a no-obligation free consultation.

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