With the proliferation of Predictive Scoring, why should you still use regular Lead Scoring in your marketing automation platform?
The truth is that most firms are still in the early stages of marketing tech use and thus lack the behavioral data history to aid predictive scoring systems. Thus, regular Lead Scoring is still a useful way to prioritize leads for Sales. In fact, many firms continue to use regular Lead Scores alongside their predictive systems.
Lead Scoring and Sales-Marketing Alignment
Lead scoring is a crucial step in achieving sales-marketing alignment because it represents how well leads fit into buyer personas and the level of interest. Getting this right over time is an important part of marketing operations.
Lead Scoring Models
There are many models and methods to design a lead scoring system. What most firms do early on in their use of marketing tech:
- The Back Room – you and the Sales VP make it up.
- The Reasonable Guess based on personas and chats with SDRs.
- Sales ranking survey – you ask Sales which behaviors and demographics they think work. (Sounds scientific at least).
What marketers would like to say they do:
- Opportunity-behavioral clustering – you pull Opp data, Win-Loss, and tie it back to behaviors or other Lifecycle data if possible. You may already have enough data to try this, but it’s not easy to properly correlate.
What you should do:
- Predictive Scoring from a third party vendor who specializes in the hard math and data collection necessary to do this.
Predictive Scoring may be ideal, but before you can get there you will need to build one of the other models first. This is especially true if your firm is new to marketing automation because you will not have a deep behavioral dataset for Predictive yet. Sales also needs to become used to the idea of working the Lead Lifecycle Stages and scoring priorities.
Maturing Lead Scoring Over Time
Lead scoring degrades because the audience shifts or workflow errors become more pronounced, creating a higher rate of rejection from Sales. So it is important to periodically calibrate the scoring system, which is what I can help you with, regardless of the original scoring model used.
- Build new models and weightings
- Audit the workflows to prevent double scoring or misfires
- Win/Loss Analysis
- Install predictive scoring
These steps will keep your Lead Lifecycle running smoothly along with the flow of MQLs to Sales.
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