Lead Scoring Best Practices

More and more B2B marketers are turning to lead scoring as a way of optimizing lead management. Many of us will remember when we used to process raw Excel lists, handing over hundreds of names with job titles and companies to our sales department, only to find that leads weren’t being followed up on. It wasn’t possible to know which leads were the most interested in your company, and wasn’t easy to see which matched your target buyer.

Recent advances in marketing automation and sales CRM software have made it easier to streamline the whole process. Marketing and sales professionals can apply lead scoring algorithms to leads, effectively sorting and prioritizing them for nurturing programs and sales follow-up.

In a recent episode of the weekly #B2Bchat on Twitter, we dug into questions surrounding lead scoring. Here is a summary of the questions and comments, compiled:

Q. What is lead scoring?

  • There are a lot of online resources on the topic lead scoring. We’ve posted a couple of articles on lead scoring including The 5 Basics of Lead Scoring on B2Bbloggers.com.
  • Here are a couple of definitions of lead scoring in 140 characters or less: Lead scoring is assigning a probability/weight to a lead based on its online behavior while interacting with your digital assets (via @joezuc) and Lead scoring is giving a rating system to prospects so more time spent with qualified leads (via @NuSparkMktg)

Q. What do you need in order to get started with lead scoring?

  • A marketing automation system. Vendors that were mentioned by name in the session included Marketo, Vtrenz, Eloqua, Genius, Marketbright and Silverpop. @jepc referred us to a comprehensive list of marketing automation systems that he has compiled.
  • You need a list of the possible paths/interactions a customer can have with your digital assets. This can be quite complex, depending on the type of product/service.
  • A target audience definition is needed, and an understanding of your buyer personas.
  • You need to understand your customer buying behavior. Talk to sales in order to learn buying behaviors, and look at previous activities associated with closed deals.
  • An agreement on the definition of a lead is essential. Sales and marketing need to come up with the definition together. Any discussion of lead scoring helps sales and marketing connect better with goals.
  • Executive buy-in from sales & marketing leadership is needed.

Q. What advice would you give to marketers that want to take lead scoring to the next level?

  • Normalize job titles to get better scoring, or restrict job titles to a pick list.
  • If possible, include consideration of offline activities as well.
  • The following high-value interactions should be weighted accordingly: E.g. “How We Help” page = higher score
  • The combo of product page w. case study or contact us page = bonus points
  • More visits from more people in one company within a shorter time frame = bonus points
  • Use negative scoring for certain job titles, e.g. consultant, student and assistant.
  • Review lead scores of closed sales to assess the validity of your scoring assumptions

This post appeared originally at b2bbloggers.com.

Meaningless Statistics Went Up 2% Last Week

“Meaningless statistics went up 2% last week.”

Thanks to John Favalo, Managing Partner at the B2B Group of Eric Mower and Associates, for referencing this smirk-evoking quote at a recent conference. I unfortunately missed where it came from and haven’t been able to find the original source.

Isn’t it interesting how numbers can add perceived importance to something even though they may be irrelevant? In my recent post on strategy vs. tactics, I talked about the importance of having a big picture view, whether you’re a traveler or marketer. This is just as important in web analytics.

Now don’t get me wrong. Online marketing has truly benefited from measurement tools. These range from Google Analytics, a free yet robust web analytics service, to competitive intelligence tools such as Hitwise, and marketing automation software from the likes Marketo and Eloqua. The question is, what to do with all the data?

The key is measuring what you need to measure, getting the data you need to make the important decisions. Granted, it isn’t always easy to know what important means. But if your strategy is clear, it becomes a whole lot easier.