Many companies implement PR campaigns to drive awareness of their products and services with the goal of reaching buyers. Earned media can be a wonderful way to attract and motivate buyers to visit your web site, research your product, or sign up for a trial. Earned media can help you drive more top-of-funnel activity for your company or client.

As lead scoring within CRM and marketing automation solutions becomes more sophisticated, the PR professional should take a few minutes to become familiar with it. As every good sales person knows, not all leads are equal. PR people need to understand the general concepts of lead scoring as it might inform decisions about campaigns and help them be more effective.

For instance, if I know that my client wants to reach owners of privately held independent insurance firms selling property and casualty insurance with revenues of $20 million in the Midwest, I am going to design and implement a very different PR campaign than if the goal is reaching providers of health insurance with revenues in the billions. Lead scoring can help you hone in on the prospective buyers your campaign should reach.

The first step in understanding lead scoring is to become familiar with the terminology. You will want to understand the difference between lead scoring and grading, how rules-based lead scoring differs from predictive lead scoring, as well as the meaning of a few other key terms. Let us begin.

Lead Scoring. According to Melissa Day, senior consultant with SmartAcre, a demand generation agency, lead scoring is the process of assigning a numerical value to a potential buyer based on his or her behavior. For instance, if a potential buyer watches three videos on your website, your marketing automation software might assign a particular score to her. That score is likely to be higher than that of the prospective buyer who watches only one video. Behavior-based scores might be assigned to things like number of live-streamed events watched, surveys completed, tradeshow visits, or web searches.

Lead Grading. This is the process of grading the buyer based on a demographic profile. Common company-specific demographic data used in lead grading are annual revenue, number of employees, and geographic location. Some people also use individual-specific demographic scoring rules based on a person’s title, role, purchasing authority or other attributes.

Rules-Based Lead Scoring. This is the process in which you or software assigns a ranking or score based on a prospect’s behavior, demographic profile, or some combination of behavior and demographic data.  You or your software might assign a numerical score, or use rankings like “hot,” “warm” or “cold.”

Predictive-Lead Scoring. Some experts believe predictive-lead scoring will replace rules-based lead scoring. Predictive-lead scoring is the advance process of using machine learning to combine and analyze much larger data sets to identify buyers. According to Valerie Levin, this is “even more accurate than basic [rules-based] lead scoring, because of its correlation between patterns discovered in both a company’s first-party data and general third-party trends.”  Other experts believe that they initially will use predictive-lead scoring to identify buyers, however, once those buyers have embarked on their journey and are in the funnel, the sales team will leverage rules-based scoring to nurture them along.

A number of companies have developed specialized predictive-lead scoring software. For instance, Versium Predict which is used by Microsoft Dynamics 363 allows users to leverage predictive lead scoring with Dynamics so sales and marketing teams can build predictive models, score leads and enhance their lead data. Dynamics CRM administrators can download Versium Predict from the Microsoft preferred provider solution site.

“By automating the predictive analytics process and leveraging our LifeData®, Versium Predict removes the dependencies on data science professionals and turns Dynamics into one of the most intelligent CRM solutions in the industry,” said Chris Matty, founder and CEO of Versium. “Initial feedback has been very positive and we are looking forward to announcing additional integrations soon.”

Negative Scores. Some lead scoring systems assign negative scores for actions like unsubscribing to an email, not visiting the website for an extended period, or complaining about spam. Negative scores can be helpful to sales and marketers and can eliminate them wasting time on low-probability-of-conversion leads.

For more on lead scoring, I recommend looking at this blog from SmartAcre. They have a nifty chart that breaks down how to combine grades and scores to determine if the buyer needs more engagement, is ready for a sale, is not a good fit, or should try another product.

For more information on Versium Predict, please check out our blog with links to additional articles.

Finally, I if you are designing your own rules-based lead grading and scoring system, I highly recommend download Marketo’s “Big List of Lead Scoring Rules.” In it, they have listed more than 50 explicit scores and more than 200 implicit scores to help you come up with the right rules for your leads. You can download this guide here.