Quick and Easy Guide to Behavior Scoring

Pete Furseth Marketing

Which of your leads are sales ready? Do you have a “hot list”? To answer these questions you need lead scoring. Lead behavior scoring helps you quickly identify those leads that are sales ready and those that need more nurturing.
Behavior Scoring and Measuring Leads
We recently blogged about our “Quick and Easy Guide to Managing Your Leads.” One of the key factors in lead management is lead scoring. We proposed three general categories of lead scoring: demographic, behavior, and account based. Each of these is useful in understanding where a prospect is in her buying journey. This blog post focuses on a methodology you can use for behavior scoring.

Behavior Scoring

A high behavior score tells you how likely a single lead is to buy your product.

It is based on the lead’s activities recorded by your marketing automation platform. Leads who visit your website, attend webinars, and download content are showing high interest. This tells you how interested the lead is in your products.
A good way to score your leads’ behavior is on a scale from zero to 100. Zero implies the lead has not interacted with your content. 100 indicates that the lead has interacted with your content in a way that indicates she is ready to buy. Marketing automation platforms are powerful tools that help you track a lead’s behavior. They can tell if a lead has visited a website, opened your email, or read your blog post. Each of these behaviors drive a change in behavior score.
To get started with behavior scoring you need to start by identifying which actions are indicators of a lead’s propensity to buy your product. To do this you should divide activities into four categories: Critical, Important, Influencing, and Bad Fit. If you read our blog post on Demographic Scoring, you will notice we use the same framework. Each behavior, or combination of behaviors, will fall into one of these four categories and will be scored appropriately.
Critical (10-15 Points) – When a lead engages with your content in a meaningful way, a way that is consistent with buying, it is considered critical behavior. Examples of this might be a visit to your pricing page, clicking a link in a sales email, attending a webinar, or visiting 10 of your webpages in a single day. When any of these activities occur, you should increment the lead’s behavior score by 10 to 15 points.
Important (5-9 Points) – Important behavior indicates that a lead is on its buying journey, but is not yet sales ready. Examples of important behaviors are downloading a whitepaper, searching for your company name, visiting important landing pages, or visiting five webpages in a single day. These activities should increment a lead’s behavior score by 5 to 9 points.
Influencing (1-4 Points) – Influencing behavior occurs early in a lead’s lifecycle. Examples are visiting any of your webpages, opening an email, or registering for a webinar. When these activities happen, the lead’s behavior score should increment by 1 to 4 points.
Bad Fit (-10 Points) – It is important to decrease behavior scores when a lead exhibits behavior that is inconsistent with a buyer. Examples of this behavior are unsubscribing from email, a visit to the careers or investor page, or being added to the “do not call” list. These are all indications that a lead is not a buyer. When this occurs the lead’s behavior score should be decremented by 10 points.
You are now ready to start scoring your leads based on how they interact with your digital content. At ORM we specialize in marketing analytics to include lead scoring and revenue attribution. If you have questions, or have some ideas to discuss, please let us know at info@orm-tech.com.
For more information on lead scoring, our white paper on creating an Effective Lead Scoring Model details how to use behavior, demographic, social, and account scores to obtain a full picture of your leads.


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With over a decade of experience with advanced technologies, Pete leads both the Sales and Marketing teams at ORM Technologies. Previously, as the VP of Engineering, he led the technical development of ORM's advanced analytics and optimization solutions.

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