The Marketing Funnel Is Dead. Let's Have Dessert.

Last week’s post on lead scoring attracted more positive attention than I expected. This was doubly surprising because first, I didn’t think lead scoring was such a hot topic and second, I don’t really agree with the approaches I described.

To clarify that second point, I’m not saying what I wrote was wrong or insincere. Rather, I consider it an accurate description of an approach I find problematic. The approach was using lead scoring as a way to define lead stages. My problem is the concept of lead stages themselves.

This verges on heresy, but I’m having an increasingly hard time with lead stages as a way to organize a marketing program. Of course, stages make perfect intuitive sense, and they’re ultimately based on the AIDA (Awareness, Interest, Desire, Action) model of the sales process that has been around for more than 100 years.*

But we all know in our heart of hearts that real buyers don’t follow such an orderly sequence. Indeed, there has been a fair amount of research questioning the validity of AIDA and similar “hierarchy of effects” models. The fundamental criticism is that decision making isn’t as rational as AIDA suggests because emotions play a much stronger part than AIDA allows. I’d also add – without a shred of empirical proof, thanks for asking – that B2B decision processes flit among stages in no particular sequence, depending on who asks what questions at any given moment. This randomness is abetted by the Internet, which makes information appropriate to all stages equally accessible on demand. But I suspect the process was always more chaotic than marketers cared to admit.

I’d further argue that buyers’ interests are especially fluid early in the purchase process, which is where marketers are involved. It may be more structured towards the end where salespeople can shepherd buyers through a defined set of stages. No, I don’t have any evidence for this either.

The point is this: if buyers don’t move through a fixed set of stages, then it doesn’t make sense to use lead scoring to determine which stage a buyer is at. Nor, for that matter, does it make sense to structure lead nurturing programs to lead (or follow) buyers from one stage to the next. As I said, heresy.

But any jackass can kick down a barn.** I wouldn't discard the funnel model without offering a better alternative – and by better, I specifically mean more effective at producing productive leads. Here’s my two-part modest proposal:

- within nurture programs, leads should be offered whatever materials they are most likely to select next, based on their recent behavior. This is exactly the same as offering customers the products they are most likely to buy (think Amazon book recommendation or Netflix’s movie suggestions) and it can be based on similar advanced predictive modeling technology. And, just as Amazon and Netflix offer more than one option, nurture programs should also offer several items – within limits, since too many choices can depress response. There’s an important humility in offering choices: it recognizes how poor we are at predicting what people want.

- for lead scoring, the goal is to predict which leads the sales force will like. I chose that word carefully – it’s not a question of whether sales will accept a lead, but whether they’ll decide it’s worth sustained effort. Yes, there could be a “like” button that lets sales rate the leads, but don't be so literal-minded.  It would be simpler and more effective to check how much activity sales has invested in the lead within, say, thirty days after they received it. Leads that sales is working are, by definition, leads that sales thinks is worthwhile. Leads they don’t work should never have been sent to them. This approach doesn’t magically solve the problem of connecting marketing leads to sales results, but it’s easier than tying leads to actual revenue.

Of these two proposals, the first one is the more radical since it implies a change in the structure of nurture campaigns. Today, sequential campaigns are the gold standard and complex branching structure are the mark of sophistication. A campaign that just presented the most relevant materials would have a vastly simpler structure – essentially a big loop that kept coming back with more messages, which would only differ in which offers they included. The sophistication would lie in the offer selection, not the campaign logic. Lead scoring's only role would be to run in the background and continuously assess whether a lead is ready to send to sales.

Even this choice-based approach doesn’t fully discard a sequential model. You need something to help decide what kinds of content to create, and the most logical tool is the content matrix that marketers already use to ensure they have content for all personas at all buying stages. But while you’re still cooking a full range of dishes, you’re offering them as a buffet rather than a fixed-course dinner. If a customer wants to eat dessert first, why argue?


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* Usually attributed to Elias St. Elmo Lewis in 1898, although there is some controversy.

** Sam Rayburn, although I bet he didn't originate it.

Using a Purchase Funnel to Measure Marketing Effectiveness: Better than Last-Click Attribution But Far From Perfect

Summary: Many vendors are now proposing to move beyond "last click" attribution to measure the impact of advertising on movement of customers through a sequence of buying stages. This is a definite improvement but not a complete solution.

Marketers have long struggled to measure the impact of individual promotions. Even online marketing, where every click can be captured, and often tracked back to a specific person, doesn’t automatically solve the problem. Merely tracking clicks doesn’t answer the deeper question of the causal relationships among different marketing contacts.

Current shorthand for the issue is “last click attribution” – as in, “why last click attribution isn’t enough”. Of course, vendors only start pointing out a problem when they’re ready to sell you a solution. So it won’t come as a surprise that a new consensus seems to be emerging on how to measure the value of multiple marketing contacts.

The solution boils down to this: classify different contacts as related to the different stages in the buying process and then measure their effectiveness at moving customers from one stage to the next. This is no different from the “sales funnel” that sales managers have long measured, nor from the AIDA model (awareness, interest, desire, action) that structures traditional brand marketing. All that’s new, if anything, is the claim to assign a precise value to individual messages.

Examples of vendors taking this approach include:

- Marketo recently announced new "Revenue Cycle Analytics" marketing measurement features with its customary hoopla. The conceptual foundation of Marketo’s approach is that it tracks the movement of customers through the buying stages. Although this itself isn’t particularly novel, Marketo has added some significant technology in the form of a reporting database that can reconstruct the status of a given customer at various points in the time. Although this is pretty standard among business intelligence systems, few if any of Marketo's competitors offer anything similar.

- Clear Saleing bills itself as an “advertising analytics platform”. Its secret sauce is defining a set of advertising goals (introducer, influencer, or closer) and then specifying which goal each promotion supports. Marketers can then calculate their spending against the different goals and estimate the impact of changes in the allocation. Credit within each goal can be distributed equally among promotions or allocated according to user-defined weights. While such allocation is a major advance for most marketers, it’s still far from perfect because the weights are not based on directly measuring each ad's actual impact.

- Leadforce1 offers a range of typical B2B marketing automation features, but its main distinction is to infer each buyer's position in a four-stage funnel (discovery, evaluation, use, and affinity) based on Web behaviors. The specific approach is to link keywords within Web content to the stages and then track which content each person views. The details are worth their own blog post, but the key point, again, is that the contents are assigned to sales stages and the system tracks each buyer’s progress through those stages. Although the primary focus of LeadForce1 is managing relationships with individuals, the vendor also describes using the data to assess campaign ROI.

Compared with last click attribution, use of sales stages is a major improvement. But it’s far from the ultimate solution. So far as I know, none of the current products does any statistical analysis, such as a regression model, to estimate the true impact of messages at either the individual or campaign level. They either rely on user-specified weights or simply treat all messages within each stage as a group. This lack of detail makes campaign optimization impossible: at best, it allows stage optimization.

Even more fundamentally, stage analysis assumes that each message applies to a single marketing stage. This is surely untrue. As brand marketers constantly remind us, a well-designed message can increase lifetime purchases among all recipients, whether or not they are current customers. It’s equally true that some messages affect certain stages more than others. But to ignore the impact on all stages except one is an oversimplification that can easily lead to false conclusions and poor marketing decisions.

Stage-based attribution has its merits. It gives marketers a rough sense of how spending is balanced across the purchase stages and lets them measure movement and attrition from one stage to the next. Combined with careful testing, it could give insight into the impact of individual marketing programs. But marketers should recognize its limits and keep pressing for solutions that measure the full impact of each program on all their customers.