Scoring your CRM leads – the good, the bad, and the ugly

In the pre-tech era, the choices for selecting a certain product or service were based on the views (of the object) and reviews gathered from word of mouth. Today with the internet raging through the veins of buyers, extensive research is done on different products- the desire to buy a material is carried forward through an intensive process of screening the choices and with every item purchased, it is possible to trace the online trajectory that led the buyer to click, “Buy Now”. Companies need to be proactive to remain accessible and available to the buyers from the beginning of their screening process and for this reason, department-wise and stage-wise strategies need to be set up to convert potential visitors into buyers.Scoring your CRM leads – the good, the bad, and the ugly

CRM Lead scoring is a meter which measures the level of interest exhibited by a visitor in your enterprise and utilizes the information to create a more engaging experience (that would eventually shift the visitor into the buyer/client zone). The prospective client is also categorized according to some suitable criteria including annual company revenue, industry, and title to ensure they sync with the enterprise’s target customer range. Following are the three factors based on which lead scoring occurs:

  • Interest exhibited by the visitor in your company
  • Visitor’s current position in the buying cycle
  • Visitor’s suitability with your business

The score leads are generally categorized on the basis of ranks (1, 2, 3…) or classified into ‘hot’, ‘warm’, and ‘cold’.

The main objective of scoring CRM leads is to harmonize the marketing and sales activities in such a manner that we can increase the productivity and profitability by engaging with the leads on the basis of their reciprocity (buy-readiness). Depending on how much interest your lead is showing, you can employ varying tools: shift them to sales track or germinate them deeper through marketing methods. The ideal form of lead scoring utilizes two types of information: static (demographic and firm-based) and dynamic (behavior scoring).  

Static information includes the size of the company, job designation, and domain of the work, while dynamic or behavioral scoring includes key-words used, number of visits to website, and the number of clicks. Both types of information can be collected through two data sources: immediate and mediate.

Immediate Data

Immediate data is provided by the prospect itself. The immediate information that can be collected for dynamic or behavioral scoring include Monetary, Orientation, Designation, and Demand (MOD2):

  • Monetary: Can the prospect afford your services or products? What are the budgetary inclinations of the target?
  • Orientation: At what stage of sales-readiness is the prospect? Will this impact any urgent or upcoming happenings like preparation of annual budget or an around-the-corner event?
  • Designation: What is the title of the prospect? Does the company have the capacity to assign budget and handle funds?
  • Demand: Does the company require your services? What is it in their company that is seeking your product? Can you cater to their needs?

Mediate Data

Mediate data is formed by tracing the behavior of your prospects (the virtual footprint) to infer their level of interest in your services or products. Following are the criteria used for measuring this type of data:

  • Did the prospect visit your company or product web-page/blog?
  • Does the prospect complete online forms, if any?
  • In how many instances has the prospect clicked on mail links?
  • Has the prospect visited the products’ merits and reviews page?

Dormant and Active Leads

While preparing your CRM leads score after answering the above set of questions, categorize the prospects under the following two heads: Dormant and Active. Two prospects might show similar behavior but could be at varying degrees of readiness towards your solutions. This categorization into dormant and active will be based on:

  • Duration taken to navigate between search-start and visit-to-sales-page
  • Frequency of visits over time
  • Action based on the last two factors

If prospect A visits your web-page for the first time on 15th April and reaches your sales-page within a week or two after flipping through reviews and demo videos, then the prospect is active. Consider prospect B who has repetitively visited your website over two months without addition of solutions to ‘Wish-list’ or ‘To Buy’ or ‘Log In’ is dormant as a lead and is still in the visitors-zone.

The success of lead scoring in shifting prospects from marketing to sales zone has been noted by studies which show that a 10% of amplification in the quality of leads converts to over 40% increase in the efficiency of sales. Laura Ramos belonging to Forrester Research remarks the need for lead scoring by pointing out “To generate qualified demand, marketers need technology and processes that capture lead quality information; validate, score and classify leads; develop programs to nurture leads that don’t yet warrant sales attention; and define metrics that directly identify marketing’s contribution to the sales pipeline and closed deals”.

Quality of Data

Another critical factor that influences lead scoring is the quality of data provided. By eliminating the leads with low level of data quality, you can focus on those which are most fitting for your company. Use the following points to add or subtract points to your leads:

  • Source of mail address: Is it a common mail address (, or or a corporate ID?
  • Locus of IP address: Where does the IP address take you towards? Does it go to an ISP (reduce points) or a corporate space?
  • Type of name: Does the first or last name of the company contain any vowels?
  • Geographic location of the IP address

Building Your Lead Scoring Model

Weighing the Past Factors

Collect data from the sales department to gauge the readiness of different buyers and prospects using past partnerships and present avenues. Use the online footprint log to check what web-pages the potential clients have visited and also, the sales history to conclude the previous communication and baits that the prospect visited before making the final moves. Most importantly, define who an ideal client is, using static and dynamic data. The data must be filled in by your marketing and sales staff. By pooling in inter-departmental resources, you can create an ideal client profile.

The Prospect Weight: Individual

Utilize the following criteria for measuring the capacity of the approaching prospect (for individual):

  • Designation
  • Years of experience
  • Public and social network recommendations
  • Career history
  • Personal inclinations
  • Position on purchase hierarchy
  • Type of mail used

The Prospect Weight: Company

Utilize the following criteria for measuring the capacity of the approaching prospect (for company):

  • Company ranking
  • Number of departments and employees
  • Company revenue
  • Website quality and traffic
  • Year of inception and growth since then
  • Geographic capacity

Categorize the prospect as: Investor, Prospect, Competitor, Partner or Client taking into account the following factors:

  • Previous type of relationship: whether a former customer?
  • What kind of products were purchased previously?
  • What kind of technologies were used (ERP, MA, CRM)?
  • What was the source of the lead (PPC, Online advertisement, website, content blogs)?
  • Also, what is the budgetary position of the company (annual, quarterly, and monthly)?

Real-life and Virtual Behavior

Collect data on what kind of online/offline activities the prospect is engaged in: online demo, free trial, articles, eBooks, virtual courses, polls and ratings, seminar, content posts (blogs/web articles), tele-communication, Slide Share, pamphlets or catalogs. Make a list of any non-lead moves that have been made like stopping mail subscriptions, absence from online activities for long time, complaint or negative comment on a social media network, inclusion in ‘Do Not Disturb’ lists or shift in the time-line of purchase. It is best to turn the above questions into a survey that can be distributed to the sales and marketing department.

Static Scoring and Dynamic Scoring

Based on all the data collected, you can make two concluding scoring sheets: Static Scoring and Dynamic Scoring with points added for each positive move and a subtraction of points for negative ones. As you develop your model, start adding specific lists to categorize the leads, that is, the scores must be accumulated in such a manner that all the behaviors and demographics are taken into account integrally and not in fragmented pieces.

Advanced Step: The Lead-Scoring Formula

The greatest criticism of the lead-scoring model remains that it is too mechanical and the buyer-readiness cannot be simply ‘measured’ using the scores. One way of resolving this issue is by creating specific target lists which will holistically add the scores into a formula. Thus, you are not simply adding or subtracting but using a ‘Lead-Scoring Formula’. This could be the advanced step you take once the model is in place.

Any company must revamp its strategies every time, when new online services are added. Make sure that you consistently coordinate with the sales and marketing team to strengthen the model according to the success of the previous engagements with the prospects.

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Author : Sahana Rajan Date : 30 Sep 2015