Quality Matters – Analyzing the Effect of Quality on the Lead Handoff Process

We are glad to have Steve Woods, CTO of Eloqua as a guest contributor to The Annuitas Group blog.  Steve is a thought leader in the world of marketing automation and lead management and is also a prolific writer on topics related to demand generation and the current transitions within the marketing profession.  His book, Digital Body Language explores these topics, and he is a regular writer on his blog of the same name. Steve is also deeply involved with the Eloqua user community, with whom he regularly interacts through the discussions on hisEloqua Artisan blog.

Thanks Steve for this great contribution!

By now, there’s a general acceptance among most B2B marketing practitioners that a lead should be scored to determine its level of qualification.  At a predetermined score, a lead can be called a Marketing Qualified Lead and handed off to sales, and below that level, the lead should be continued to be nurtured.  This is a great foundation to build from as it creates a fundamental alignment between sales and marketing around the flow of these qualified leads.  However, this only forms part of the picture.  Not all leads, even marketing qualified leads, are created equal, and without paying close attention to the quality of the MQLs the effectiveness of your sales force can suffer.

To dig into this a bit further, it’s first worth exploring what we mean by a marketing qualified lead.  There are two dimensions that make up an MQL, fit and engagement. Fit is the demographic and firmographic criteria that define the type of person in the type of organization that generally buys your solutions.  Made up of such factors as title, industry, geography, and revenue, it does not change rapidly over time. Engagement, however, is the set of actions that indicate a current, real, interest in your products or solutions.  Made up of such factors as website visits, Google searches, Twitter activity, event attendance, or blog activity, it is highly transient and time sensitive.

Together, fit and engagement make up the two key dimensions of a lead scoring matrix that defines an MQL.  Ranked between A-D for fit and 1-4 for engagement, we can see a grid where the top right corner is the MQLs we will send to our sales team.  While all of these are MQLs, there is a clear difference between an A1 lead and a C2 lead.  It is this quality difference within an MQL that is worth digging into further.

The first thing to analyze is lead handoff quality.  By mapping each territory, and even each rep, to the A1, B2, and C1 leads they are given, quality differences in lead flow may become obvious.  While each rep may be receiving 30 MQLs per quarter, if one is receiving all A1 MQLs, while another is only receiving C1 MQLs, a material difference in deal flow would be reasonable to expect.

There are two possible avenues to explore if a difference in quality is observed.  If a difference in fit is observed, where one territory is seeing more A’s and another is seeing more C’s, it may be that there are natural differences in the makeup of geographic territories, based on size of company, executive presence, or company size, that make one territory more of a natural fit for your solutions than another.  If a difference in engagement is noticed, where one territory is seeing mainly leads with an engagement rank of 1, while another territory is seeing only 2s and 3s, it may be that the level of field marketing involvement in each territory is significantly different.

Looking at the quality differences within the set of leads flowing to a sales team allows optimizations of territory size, quotas, and field marketing engagement.  Without looking one level beneath the raw number of MQLs, however, this approach to optimization would not be possible.

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