Most marketing automation tools give you the ability to nurture and score the leads in your database.
The overarching idea is to nurture a lead towards sales-readiness, usually in the form of crossing a lead score threshold.
You don't want to waste your sales team's time chasing down every single lead to call, after all.
However, it's likely that one of two things will happen:
1. Marketing will inadvertently send over leads who are completely uninterested to talk to Sales (false positive).
2. Marketing will inevitably fail to send over some qualified leads who have a high latent propensity to buy (false negative).
This may be controversial, but here's what we think:
The whole idea that marketers can design a lead scoring model that correctly scores leads according by their interest to talk to Sales is deeply flawed.
This belief creates a cascade of problems for revenue teams, leading to a net-loss of qualified opportunities for Sales. If you are not careful with lead scoring, you end up running into endogeneity* problems which can be insidious and hard to debug.
*The word endogeneity is just a fancy word for having variables in your model affected by unforeseen variables. And... I've used up my one big word quota per article.
If we filter only by leads which are a good fit, then you realize that there are only two kinds of leads that really matter:
1. Leads that are willing to talk to Sales
2. Leads that are unwilling (or not ready) to talk to Sales
If we can somehow take away the human & manual effort of reaching out to every lead: let’s suspend disbelief and assume this is possible - you realise that leads will sort themselves into two groups: hand-raisers, and non hand-raisers. This is what we call Binary Scoring.
Saleswhale wants to help sift out the leads who are ready for a sales conversation, and hand them over immediately to Sales.
The Saleswhale AI assistant will also continue to "check in" with dormant leads automatically every 90 to 120 days.
This is what we see across our entire customer base of hundreds of marketing teams that transitioned over to a Binary Scoring model by backfilling their marketing automation with an AI assistant:
A lift of 30% to 250% of lead-to-opportunity conversion rates, and huge savings in Sales’ time.