How To Improve your Content Marketing With Predictive Scoring

Nowadays content marketers are generating too many inbound leads for sales.

The high number of leads results in sales not knowing which leads to prioritize and a lot of wasted effort as sales reaches out to many leads that are not a good fit, and miss some great leads hidden among the high inbound volume. An even bigger challenge is that content marketers don’t know which content is attracting the most valuable audience and they also can’t create tailored content to nurture these leads.

Content marketing and sales are inherently misaligned in their efforts from both sides:

  1. Great leads engaging with content aren’t getting to sales fast enough, but sales is still getting bogged down with leads that aren’t a strong fit
  2. There are no insights into which content is attracting the most valuable audiences

That’s where predictive scores come into play.

What Is A Predictive Score?

A predictive score for B2B marketers is an estimate of how likely a lead is to convert.

Marketing and sales set thresholds to determine when leads are qualified and use these scores to inform their decisions. The higher the score is for a lead, the more likely that lead is to convert.

Marketers can use predictive scores to prioritize the best inbound leads for their sales team. Whereas lead scores help marketers find the leads that are interacting with their content, predictive scores help marketers find the leads that are most similar in fit to existing customers.

How Predictive Scoring Can Help Content Marketers?

Most marketing processes are muddled with irrelevant leads, which get passed on to sales and result in a significant amount of wasted time for the sales team.

Only 30% of MQLs turn into SQLs [SiriusDecisions]

Using predictive, marketers can reduce the required number of leads their sales team must hit to reach their goals while also ensuring the right content is produced to help support their targeted efforts.

Predictive Use Case Example: Accelerate the best leads to sales

Let’s look at a basic predictive use case example:

Imagine your content marketing team publishes an amazing whitepaper. The content is rich with actionable insights, includes tips from top industry influencers, and even positions your company as a thought leader in the space.

At the end of the campaign, you find out that your white paper is projected to receive a whopping 10,000 downloads. That’s a content win, right? Well, not necessarily.

As you collect these prospects, you start sending them to your sales team for them to follow up and close. But with 10,000 downloads, your sales team is looking at an equally sizeable number of leads that they need to contact. Odds are your sales team will either start prioritizing certain leads based on their own judgment, which results in them potentially overlooking some of the best leads with the highest likelihood to convert. Or, they simply have to contact a larger number of leads in order to hit their target.

But what if your sales team knew which leads they should target first? And more importantly, what if the marketing team was able to create content that was highly personalized for these leads? With a predictive model, you can do exactly that.

Taking this example, let’s evaluate both scenarios: using a predictive model to prioritize inbound leads vs. not using a predictive model.

Without a predictive model (red line), to reach 60% of the prospects who will actually convert, your sales team will have to contact 60% of the total prospects. That’s 6,000 leads.

But with a predictive model (blue line), your marketing team can use scoring to identify and prioritize the top leads that are most likely to convert. This means you hand off more high-quality leads and your sales team can reach 60% of the prospects who will actually convert while only having to contact 40% of the total leads (or 4,000 leads).

The benefits of using predictive in this case are:

  • Your marketing team is only sending the most qualified leads to the sales team
  • Your sales team is more efficient because they don’t have to speak with a long list of lower quality leads in order to reach the high propensity prospects

From a content marketing perspective, you can use predictive to identify segments of these leads and surface key signals and attributes about them, which in turn enables you to create more personalized content that nurtures these leads through the buying cycle.

In addition, content marketers can also use predictive scoring to see how many top tier prospects were generated from your content, so you can optimize future content marketing efforts.

Wrapping It Up

If your content is helping attract, engage, and convert top-tier leads, then sales will love you if they can get in front of those quality leads right away without having to waste time on less qualified ones. But in order to do so, you need to be able to identify and prioritize the leads that are most likely to convert, while also supporting your sales team with the right content.

By using a basic predictive concept like scoring and grading, content marketers can find out which leads are interacting with their content and which ones are likely to become their customers.

[By Vignesh Subramanyan] [From Business 2 Community]