Lead scoring

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Lead scoring describes a procedure in the marketing approach of the lead management process in which potential customers of a company are classified using a scale. The value determined in this way indicates the sales priority with which a customer should be processed.

description

Lead scoring models contain both explicit and implicit data. Explicit data is provided by or about the prospect, e.g. B. Company size, industry segment, job title or geographic location. Implicit scores are derived from monitoring potential behavior. Examples of this are website visits, white paper downloads or opening and clicking emails. In addition, social scores analyze a person's presence and activities in social networks.

Lead scoring enables a company to customize a prospect's experience based on their buying phase and interest. The aim of such an approach is to use the existing sales resources of a company as efficiently as possible. It is therefore an essential part of a corporate strategy focused on inbound marketing .

Methodical approaches

Depending on the size of the company and the specific area of ​​application, different methodical approaches to lead scoring are used.

  • Lamb or Spam: The lamb or spam model is most often used by small businesses that do not have a clear, ideal customer profile (often modeled as a buyer persona). It consists of filtering out low quality leads and popping up leads with high potential. Poor quality leads are identified by online businesses using personal email address domains (Gmail, Hotmail, Yahoo) or temporary email generators, which are used to send email spam or log in anonymously. High-quality leads are identified based on their corporate email domains and firmographic data such as job title and company size.
  • Rule -Based : These lead scoring models assign point values ​​to a lead's firmography and behavioral attributes. Point thresholds are set to assign rule-based follow-up actions to the lead. The implementation is usually carried out via marketing automation platforms and add-ons that serve as a supplement to the customer relation management system, e.g. B. Lead scoring solutions for Salesforce CRM.
  • Predictive Lead Scoring: Predictive lead scoring models use machine learning to generate a predictive model that is based on historical customer data and supplemented by third-party data sources. The approach is to analyze the behavior of leads in the past or past interactions between a company and leads and find positive correlations of this data with a positive business outcome (e.g. a purchase).

Predictive lead scoring methods are generally preferred because they can routinely collect new customer data and refine their forecasts.

Goals of lead scoring

Lead scoring comes into play if such an amount of incoming data can be expected in the course of lead generation that processing in chronological order is not possible or not economical. The main goals of the scoring method:

  • Increased sales efficiency and effectiveness: Lead scoring draws sales attention to leads the company deems most valuable and ensures that leads that are not qualified or have low perceived value are not available for further processing (e.g. for more detailed contact) to the sales department.
  • Increased Marketing Effectiveness: A lead scoring model quantifies which types of leads or lead characteristics are most important. This helps marketing to align its inbound and outbound programs more effectively and to provide higher quality leads for sales .
  • Tighten Marketing and Sales Alignment: Lead Scoring strengthens the relationship between marketing and sales by establishing a common language that marketing and sales managers can use to discuss the quality and quantity of leads generated.
  • Increase in Sales: Lead scoring also ensures that sales come first for leads who are qualified based on their scores. A lead with higher scores is more likely to be closed than a lead with lower scores. This also indirectly contributes to sales growth.

Individual evidence

  1. ↑ Federal Association for Information Technology, Telecommunications and New Media Bitkom EV: Product-neutral and environmentally friendly procurement for public administration . In: Innovative Administration . tape 34 , no. 4 , March 2, 2012, ISSN  1618-9876 , p. 42–42 , doi : 10.1007 / s35114-012-0069-3 ( bitkom.org [PDF; accessed June 3, 2020]).
  2. ↑ What is lead scoring? - Definition from WhatIs.com. Retrieved June 3, 2020 .
  3. ↑ Lead Scoring - Ryte Wiki - Digitales Marketing Wiki. Retrieved June 3, 2020 .
  4. ↑ Lead Scoring Best Practices. Retrieved June 3, 2020 .
  5. ↑ a b 5 Ways Lead Scoring Can Increase ROI & Produce Better Customers. Marketing Automation Insider, accessed June 3, 2020 .
  6. ^ The Three Stages of Lead Scoring: Lambs, Ducks & Kudus. In: The MadKudu Blog. January 29, 2019, accessed June 3, 2020 (American English).
  7. ↑ This is what good lead scoring looks like - methods and tips from practice. April 30, 2020, accessed on June 3, 2020 (German).
  8. ^ Predictive Lead Scoring: Why, How & Where. Retrieved June 3, 2020 .
  9. ^ The Three Stages of Lead Scoring: Lambs, Ducks & Kudus. In: The MadKudu Blog. January 29, 2019, accessed June 3, 2020 (American English).