Content consumption does not always equal purchase intent
Modern marketers can all agree that content marketing is the key to engaging and acquiring new leads. A great thought leadership webinar can attract new prospects to your solution and educates them on the benefits it can deliver. The typical wisdom of marketing automations systems is to award points to leads for consuming the great content marketers publish.
I’ve implemented many lead scoring models in my time. I’ve built out smart campaigns to award points for white papers downloads, points for attending a webinar, more points for visiting a website. More points get awarded for the right job title and maybe even company size. The leads with the most points are dubbed “qualified” and make it into my sales teams’ queue.
Over time the sales team learns to pick and choose which leads they want to call based on what they have learned from previous calls and which leads to pass over. They know the lead is just downloading content for the sake of education and is not ready to talk to sales. I’ve seen sales teams gradually become less and less inclined to look at the lead score and just “go with their gut”. And at the end of every quarter the head of sales inevitable asks me:
“Is our scoring model right?”
“Why is our qualified point threshold at 50 points?”
“How do we know a white paper is worth 10 points, or 20 points, or -17 points?”
The answer is that without some heavy statistical analysis, and regression testing, a lead scoring model is really just based on assumptions we marketers make. They may be highly educated assumptions, but assumptions none the less. A good lead scoring model needs to take into account more than just activity on the site and consumption of content. Downloading white papers and attending webinars certainly works to cultivate leads and educate them about why they need to purchase your product, but be careful to not confuse correlation with causation. They may score all the behavioral points they want but will never be the right fit to actually purchase your product.
An even better lead scoring model should be predictive. Meaning, a predictive model is an analysis of all closed won deals to find commonalities amongst those leads. Once the model knows which is the ideal lead, you can prioritize those leads and optimize your sales team’s time.
If you want to make your sales team happy, send sales leads that match contacts that have already closed. Not just leads that downloaded a bunch of content.