Lead scoring is a common component to marketing automation. Often, when a lead achieves a specific scoring threshold, that record is automatically migrated to a CRM for sales contact. However, not all lead scores are the same when they are passed to the sales team. In order for sales to be effective at converting a marketing-qualified lead to a win, it’s beneficial to for each sales agent to understand how a fresh MQL has been scored.
The total lead score is often comprised of a letter grade (A, B, C, etc.) that represents the lead’s explicit attributes (company size, industry, job title, etc.) and a numeric score (70, 80, 90, etc.), which represents the lead’s implicit characteristics as evidenced by its online footprint (web page views, email open, social click, etc.). The lead is graded against other suspects according to how well it fits a lead profile or customer persona then given points for engagement activities with your brand.
Why a Score Breakout is Important
The lead grade is fairly standard. The closer it fits to your typical customer, the higher the grade. CRM users can typically view the information used to generate a lead grade in the CRM interface. It’s the implicit score that a sales agent is typically blind to. If your sales agents see a lead score in the CRM, it is usually the total score. But how did the MA system calculate that total score? If your salespeople can identify what factors contributed to a lead’s total score, they will be better prepared to approach that lead and understand his or her motivators, research strategy, and MA awareness level.
Our Lead Management Automation™ platform breaks your lead score “out of the box”. Users can see what tracks a lead has taken to earn its implicit score. Various point values are assigned for each activity. For example, a single ‘email open’ activity may receive 5 points; a web form submission may receive 30 points. Each activity-related parameter is assigned a value which contributes to the implicit score.
This implicit score can reveal a lot about how the lead behaves, where he or she is in the buying cycle, how influential the lead may be in the purchase decision process, and other factors that can be critical to both the salesperson’s approach and the likelihood of conversion.
Every digital footstep doesn’t deserve the same scoring weight. Website pricing page views typically reflect a higher level of interest than a home page view. A lead that has engaged in a chat is often more sales-ready than one who has submitted a web form. Therefore, it’s critical to improving sales productivity for sales agents to view the lead scoring baseline in order to get a more complete impression of a sales lead.
Within your scoring matrix, the implicit activities should be weighted to account for the importance of each activity to the buying process.
If you’ve gone to the effort of deploying a marketing automation system, you should be able to view a breakout of the lead score. If your system provides this granularity, make sure your sales team is leveraging the information provided within initial and follow up contacts. Your sales conversion rate will rise and your sales team will become more efficient.
If your lead management/marketing automation system does not have a lead score breakout, take a look at our Lead Management Automation platform!