Top 10 B2B Lead Scoring Mistakes (Part 1 of 2)

Lead scoring has quickly become an integral part of a demand generation marketer’s arsenal. A well-planned, well-designed, and optimized lead scoring schema can be a key contributor to sales productivity, sales engagement, and the rate at which inbound leads convert to Sales Qualified Leads, opportunities, and deals.

lead score thresholdConversely, a poorly designed lead scoring system – one that labels good leads bad and vice-versa, can quickly result in sales disenchantment, to the point where good leads are routinely ignored and demand generation ROI suffers accordingly. In my experience, companies new to marketing automation often launch scoring schemas too quickly as part of an overall rush to value, and by the time the schema gets corrected, sales needs to be re-sold and re-trained on what they now regard as inaccurate and irrelevant data.

In our firm’s work with marketing automation clients, lead scoring optimization is a critical part of ensuring that companies reap the greatest benefit from the investment in marketing technology. Drawn from that experience, here are 10 examples of the most common scoring mistakes we see B2B companies make:

1. No separate scores for behavioral and demographic values.

Demographic scores are best thought of as how interested you are in a prospect. Behavioral scores are how interested that prospect is in you. If you only use one lead score value, there will be no easy way to distinguish between, for example, the CEO with little to no interest in your solution vs. the low-level end user with a high interest. Scoring on both demographic and behavioral attributes allows you to provide more meaningful and relevant data to sales.

2. Faulty inactivity campaigns

Companies routinely use “inactivity” campaigns to subtract points if, for example, a prospect takes no action for 3 months. However, if a prospect so much as clicks on one email or visits one Web page during that period, his/her score will never go down. A better approach is to institute a score degradation scheme – see #3 below.

3. Score inflation.

When you award points to a prospect for some specific behavior (e.g. visiting a Web page, attending a Webinar), that score shouldn’t last forever. The value of someone attending a Webinar last week, for example, will be much less significant say, a year from now. However, many lead scoring schemas don’t reflect that degradation of score value over time, and the result is “score inflation,” where individual prospects may ring up lead scores of one thousand points or more, by which time the score has become meaningless. One elegant solution is to use a system of expiration dates and deduct points over time, something I discussed in more detail in this earlier post.

4. Multiple campaigns assigning lead scores.

Depending on the marketing automation platform you use, there are usually two ways to assign lead scores. The first is to build a lead scoring “step” into each campaign, so that (for example) when someone registers for a specific Webinar, a step is included in the workflow that adds a predetermined number of points to that individual’s lead score. The problem with this approach arises when you want to refine and optimize your lead scoring schema over time, in that any change will require that you change scoring commands in every campaign in which that particular scoring action is included. A much better alternative is to utilize one, centralized lead scoring workflow that applies to all campaigns and assigns lead score whenever the appropriate behaviors occur, regardless of the circumstances. This approach makes lead scoring much more flexible and optimizing the overall schema much less time-intensive.

5. Scoring email opens.

As I discussed in an earlier post, email opens are a grossly unreliable measure of email effectiveness. An email “open” can mean many things, but more than likely does NOT mean that the individual recipient consciously opened and read your message. As such, scoring email opens not only runs the risk of assigning lead value for no valid reason, but can also contribute to score inflation (see #3, above.) Better options are to score on email click-throughs and form submissions.

Click here for Part 2 of this post.

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