In my previous articles, I explained a bit about how an inspired application of digital analytics to any firm’s marketing strategy demands a broad-lens view of the consumer, a focus on more than just whether or not someone converts, but who, when, why, and what may stand in their way during their consumer journey.
Commonly, we look at marketing as a funnel, an ever-narrowing channel that captures as many consumers as is possible on one end and delivers them somewhere specific on the other. While many marketing organizations realize that the funnel is wide at the top and narrow at the bottom, surprisingly few strive to understand the intricacies of the unintended outflow: where loss occurs in the funnel, especially in the context of different types of customers.
A funnel-type breakdown is helpful because, in the most ideal use of this idea, it helps us organize our efforts into tiers—picture a series of horizontal cuts across your funnel. At the top of the funnel, we just want to be noticed. As things progress, we retain interest by satisfying the needs of the consumer (earning ourselves a relationship), before finally looking to close at the funnel’s bottom. Even after the sale is complete, the follow up and service we provide continues to serve the funnel, as repeat purchases, upgrades, etc. come into view.
This is well traveled ground, and it’s just one form of the marketing lifecycle (not everyone has a funnel). Despite having a deep understanding of these concepts, traditional marketing tools, especially those designed to measure the performance of marketing channels like email, display, search, and social, don’t allow us to see into the funnel at all. We’re stuck knowing where the consumers go in and ultimately how many come out on the other side. As the funnel narrows, there are readily accessible data—where our sales are being lost or gained, relationships weakened or strengthened—that beg to be brought into an environment where it can be used to understand and optimize channels more effectively.
A Hypothetical Example
Of course, it’s much more complicated than merely understanding where conversion is lost outright by assuming the funnel is telling us the truth. Let’s say we are an e-commerce site with only two products for sale, and one massively outsells the other. Is this is sign that the more successful product is intrinsically better suited to our audience? Maybe or maybe not.
It’s equally or even potentially much more a result of our marketing design that’s shaping that outcome. How are we messaging? How is the experience for each product competitive with other sites where these products are offered? How is our pricing? How is the product photography, impression that support is available, shipping costs, quality of the site, etc. versus the other places a consumer will look for this item? No doubt we can manipulate those numbers if we know what’s propelling our consumers towards one product over the other, especially if it’s all a self-fulfilling prophecy.
To bring this example home, I was once working on a campaign where sales for one company’s product plummeted for a whole month and its other products continued to perform. The search agency could not figure out the problem, and the client thought the product was out of style (despite massive click volume in their search campaign). What was the problem? The product was out of stock. Yes, you read that right. OUT OF STOCK for a month and nobody figured it out, and everyone wanted to blame the search campaign for not producing sales that were impossible to produce.
Don’t Lose Your SaaS
One of the best examples of how marketing affects sales can be seen in software as a service (SaaS), where products are tiered rather than individually packaged (think Basecamp, Zendesk, or something similar with basic, premium etc. plans). What proportion of subscribers are settling for the basic package? Is that number, that ratio of low-margin to high-margin buyers really optimal? And I don’t just mean optimal for the company; if the higher package is better suited to the customer, why aren’t they buying it? Are we losing buyers in higher tiered packages because our marketing is failing to engage with one or more audiences at some critical point in the funnel, or is the language we use to describe our features presented as our own flurry of buzzwords rather than connectible verbiage that resonates with the consumer? When it comes to the forensics of why the basic plan is preferred, can we shift the lens to see each audience individually, which preferences are motivating the slices of our customer base? Can we then pinpoint the exact moment in the funnel where the decision to settle for the basic plan was made?
Traditionally, no. This is data beyond our reach. Part of understanding what’s happening in the marketing lifecycle is exactly this: being able to break our consumers down into “personas,” sorted by the unique factors that bring any given customer base together. If we want to fully understand the marketing lifecycle, we have to understand the segments of that lifecycle and, most importantly, how each type of consumer—each persona—progresses through those segments. Today, almost zero campaign management platforms offer this functionality (but it is available in your analytics tool data).
In part two of this article, we will look more closely at the sales funnel to understand the steps in the process.