QlikTech, a provider of powerful, affordable business intelligence software that helps you make better decisions faster, operates globally with a focus on 13 key regions. To implement an effective lead scoring program globally, QlikTech began by launching a simple, global, enterprise scoring model, then allowing each regional subsidiary to customize local scoring criteria based on their specific requirements, programs, and languages.
QlikTech’s scoring system includes rules at the global level, regional level, and product level (for tracking downloads), all of which contribute to ranking a lead based on its activity.
For QlikTech, lead scoring is an iterative process of improving collaboration between sales and marketing teams, as well as between corporate and regional managers. Ongoing reviews help ensure that rankings are continually adjusted and refined, ensuring that sales reps receive the right number of qualified leads of the right quality.
Feedback loop
Lead scoring methods—especially new ones—are an imperfect science. You meet with salespeople, develop common definitions, and assign scores to leads based on your understanding of the buying process.
A feedback loop turns guesswork into accurate predictions of lead readiness. Don’t underestimate the power of simple discussions with sales reps who have received your first qualified leads. Feedback from salespeople allows you to match your understanding of the buying process with the lead’s score and interesting insights from your CRM. At Marketo, for example, discussing the scoring system with the phone lead qualification team resulted in lower scores for careers page visitors.
A structured screening process is another way to evaluate your current lead scoring campaign, examine the database you've collected, and segment individual leads from it.
Lead Ranking Checking Process
Plan to review your scoring process at least quarterly.
Take stock of your assessment database.
How many leads have scores in the ranges 0-10, 10-20, 90-100, etc. Which of these ranges do most of your leads fall into? Do extreme score variations indicate errors in the scoring methodology?
Is lead rating degradation taken into account?
Do you have any new ranking influencers and are they being measured correctly? Remember that significant changes – such as a website redesign, a change in the surrounding marketing ecosystem – mean that you need to re-evaluate your scoring system parameters.
Create a list of new opportunities created since your last check. What online behaviors are most associated with moving a lead to an opportunity? Which online assets are converting the best?
Assess the accuracy of BANT data to overcome the inherent philippines phone number data limitations of self-reported information by using leads qualified as “ready to buy” and actual sales to compare actual and self-reported BANT data.
Create a list of disqualified leads that are ready to buy and look at their preferred assets to identify meaningful differences with your opportunity list.
Understand the relative importance of implicit versus explicit metrics. Marketers often overestimate the importance of latent behavior (like downloading a new white paper).
Use your customer list, focusing on your most recent wins in your target market: compare the demographics of these successfully converted leads to your qualification threshold. If they are below the threshold, you will need to adjust both the positive and negative rankings within your scoring campaign.
Assess who exactly in the buying organization was the key figure in closing the deal. A common mistake marketers make is overestimating the influence of top management on the collective decision to purchase.
Make changes and adjustments to your scoring campaigns.
Advanced marketing automation platforms—through retargeting campaigns—give you the ability to retroactively re-score leads and massively reposition prospects throughout the buying cycle.