While this is certainly not a bad problem to have, it's a problem for many companies nonetheless.
93% of companies that implement inbound marketing increase their lead generation, but if they fail to enable their sales team with a process for prioritizing this influx of new leads, this progress means very little.
In an effort to keep their head above water, many companies adopt lead scoring as a way to help their team prioritize leads and increase efficiency, however lead scoring can often be a flawed process.
Enter predictive lead scoring.
Acting as the cooler, smarter older sister to lead scoring, predictive lead scoring is rooted in analytics to help provide businesses with a more organized approach, while also serving as a way to differentiate them from the competition.
Wondering how it works? Let's explore.
What is Predictive Lead Scoring?
Before we dive into what predictive lead scoring entails, let's cover the basics.
Lead scoring (minus the predictive element) refers to the process in which businesses attribute a numerical score to leads based on various factors and behaviors. Essentially, it functions as a way to qualify leads and surface priorities.
The trouble with this approach is that it can be challenging for marketers to interpret the data in a way that is both consistent and accurate. Even if sales and marketing both sit down to define a strategy for scoring leads, it's easy for assumptions to get in the way of generating a score that you can all agree upon.
To combat this, predictive lead scoring leverages both historical data as well as predictive analytics to calculate a more informed score.
This approach eliminates the risk of human error by replacing the need for people to manually weigh the importance of qualifying factors with a more streamlined process.
How Does It Work?
Typically a predictive lead scoring software will follow a strategic step-by-step process to uncover the most qualified leads for you business to tackle. While the logistics vary from software to software, this is a general overview of how it works:
Start with your existing leads. If you have a lead in your system, it's likely that you had to capture at least some basic information to get them there. This will serve as the foundation.
Let the software mine the web. The predictive lead scoring software will pull something as simple as a lead's email address and use this small bit of information to scrape the web for a ton of additional signals such as social presence, web presence, and patents.
Create the an ideal profile from science. From here, the software will work to calculate a score based on the likelihood that the lead will convert or contribute to a large revenue impact. To calculate this score, the software will pull data from your CRM and marketing automation software to identify where you've historically seen success. It will then employ a machine-learning engine to analyze different combinations of buyer signals to surface a custom model and ideal customer profile.
Leverage the integration. Predictive lead scoring software integrates with a variety of different CRMs and marketing automation software, which makes it easy to push the score out across multiple platforms to keep everyone on the same page.
It's Actually A Lot Like Netflix...
Have you ever felt like your Netflix account just gets you?
I certainly have.
Not only does it autoplay the next episode of a show without me having to lift a finger, but it also recommends just the right movie every. single. time.
(Spoiler alert: this isn't magic either.)
The way it works is Netflix leverages analytics to identify correlations between the movies and shows that users watch. This process takes into account things such as genre, rating, and length to deliver the best suited option -- just for you.
Think of predictive lead scoring in this same light.
When a lead enters your database, your software will use predictive analytics to compare the contact's properties (company name, industry, size, etc.) against those of existing contacts (both won and lost) to determine the best fit.
Makes sense, right?
What Does This Mean For Your Agency?
Predictive lead scoring aims to provide both answers and direction to help sales and marketing regain control of their efforts.
Unlike traditional lead scoring, this approach will help your agency to:
1) Absolve doubt.
While the lead scoring systems you may be used to rely heavily on assumptions, predictive lead scoring is rooted in cold, hard analytics. This type of certainty helps marketers and sales reps rest assure that their basing their actions off of something meaningful.
The fact of the matter is, employees come and go. For your company to scale, it's important that you're focused on training new hires on a lead scoring system that is based on defined analytics rather than an approach that is susceptible to continuous change.
3) Uncover patterns.
Predictive lead scoring helps to highlight recurring behaviors or properties that tie back to "closed-won" opportunities. With a better understanding of what these leads looks like at all stages, it's much easier for your agency to replicate its lead generation process to attract more like them.
4) Better align sales and marketing.
Taking the guesswork out of lead scoring will eliminate the need for finger pointing between sales and marketing. With a better understanding of things like which leads should be sent to sales or which leads should take priority, both departments are set up to see more sustainable results, which ultimately means you can prove higher ROI to your clients.
Has your company ever experimented with predictive lead scoring? How did it compare to traditional lead scoring? Let us know in the comments below!
Infer, a platform that automatically researches every lead and identifies MQLs with predictive lead scoring, is now a HubSpot integration partner. Check it out here.
Originally published May 12, 2015 9:00:00 AM, updated July 28 2017