How Advertiser Sales Data Will Turn The Sales Funnel Into An Hourglass

We all know and love the sales funnel.  What a simple metaphor to describe a customer journey: start at the top with awareness and finish at the bottom with sales.

Each customer journey through the funnel yields important information about brand interaction, and each media platform throws off distinct information that supports its role in the eventual sale.

For decades, TV has lived at the top of the funnel. With nearly ubiquitous U.S. penetration and a 50-inch screen to generate awareness for brand messaging, its predictable and proven programming and advertising formats made it arguably the easiest medium to purchase.

For as many decades, Americans have been sampled by third-party companies to get an understanding of their demographics and certain declared behaviors. This information was tied to the programming they viewed — and, with it, audience targeting became a standard practice.

As digital advertising in all its forms has grown, so has the need to capture as much data about consumers as possible, leading to a meteoric rise in the use of data management platforms and customer relationship management systems.



One thing hasn’t changed in all these years of technology and advertising platform growth: Only  advertisers get to see the aggregated sales numbers at the bottom of the funnel — and, with it, information that informs their understanding of who is buying their products and how often.

Historically, this information has been used for below-the-line advertising tactics such as direct mail but not until now has it been used for television advertising.  We are entering the stage where anonymous data-matching techniques are improving enough that an individual’s television-viewing behavior can be directly matched to his or her purchase information.

This development will have a dramatic impact on how television advertising is bought and sold. In essence, advertisers will be able to look up from the bottom of the funnel, through the sales data, and see who was exposed to their message and the respective purchases they made – versus those who were unexposed to their message and the purchases they made.

With anonymous direct-matching capabilities, advertisers will be able to understand the relationship of awareness and attribution (top and bottom of the funnel metrics) that only TV can deliver. Additionally, with more and more advertisers using data management platforms, advertisers will be able to append additional behavioral information about their customers. This will further inform their planning and buying activities and influence their creative messaging strategies.

So if television now has the ability to show which viewers are prospects and which are existing customers, and advertisers can plan their communication strategies accordingly, I would argue that it is time to retire the sales “funnel” as the sole metaphor for a marketer’s audience engagement tactics and replace it with the “hourglass.” Why? because an hourglass is an actionable funnel, and with today’s dynamic marketplace being driven by actionable data, an advertiser’s relationship with a customer does not end when a consumer makes a purchase. It begins.

As consumers flow back and forth within the two funnels of the hourglass, black-and-white media metrics such as gross rating points and cost-per-thousand impressions will be colored by the reaction of the audiences as measured by their purchasing behaviors — also known as return on ad spend.

The clarity to define which target audience is responding will help advertisers answer the crucial question confronting TV today: “How do I know my TV advertising is working?”

“Hourglass marketing” and television’s newfound ability to measure awareness and attribution will answer this question — with the ultimate winner being the audience.

5 comments about "How Advertiser Sales Data Will Turn The Sales Funnel Into An Hourglass".
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  1. Ed Papazian from Media Dynamics Inc, May 22, 2015 at 1:27 p.m.

    John, I have seen many cases where branding advertisers have tried to relate their sales and other results ( company image, as an example ) to their TV and other advertising. Often, this is done via so-called ROI studies, but it is also a very common, albeit a less statistics-dependent process. So it is not true, in my experience, that cause ( audience ) and effect ( sales ) correlations have not been routinely made---even if the matchups are, sometimes, tenuous. What is true is that the response of particular consumers---as distinct individuals---has not been monitored because, in most cases, that hasn't been possible.

    As far as the wonderful new world of media that is fast approaching is concerned, what you are describing, if I take you literally, is a situation where the entire nation's TV viewing---minute by minute, channel by channel---is recorded and the specific sales activity of each "viewer" and viewing occasion is related to product sales. Of course, you realie that nothing like that is in the offing. No such database exists or is likely to exist.

    Instead, what you are talking about---I assume---is the idea of taking second party set-top TV home ratings from a sample of several million households and statistically "marrying" the findings on a show by show basis with third party marketing or product purchase information. The resulting indices will, again, be "married" to the findings from Nielsen's "small data" TV rating panel, to create a replacement for the "outmoded" age/sex targeting now used by TV time buyers. Now, they will focus on the buying habits of the audience---though not for specific members of the audience, of course. Last but not least, enter "programmatic" buying, using all of this ascribed and re-ascribed data, which will seek out the marketer's best sales prospects and buy those TV availabilities that do so at the lowest possible cost. This, we are told, will generate "undreamed of" targeting efficiencies----but it's still not viewer-specific.

    I appreciate the desire to develope new and better ways for advertisers to buy and use media---I really do. But we've got to imagine what can really and practically be accomplished, rather than fantasizing about some "ideal" that is unlikely to materialize.

  2. John Piccone from Simulmedia, May 22, 2015 at 2:38 p.m.

    Ed - I could have clarified the matching process better but did not want the focus to be about the data matching itself but more about the impact it will have on business outcomes and the audience targeting process. That being said, one thing that I do want to clarify is that it is possible today to isolate millions of set top boxes that nationally represent the US TV viewing population and directly match specific buying activity to their specific TV viewing activity. Once this match is done then the results are projected nationally. So to summarize there is NO modelling. It is directly matching impressions to transactions.

  3. Ed Papazian from Media Dynamics Inc, May 22, 2015 at 3:20 p.m.

    John, I agree that you can probably get a pretty good attribution match when combining the set usage data from a few million set top boxes with another source, but there are two problems with this. First, all this gives you is an index to be applied to the Nielsen ratings, you can't sell time to specific homes within the set top box sample, based on their actual product purchase behavior. Second, set top box ratings are for households not people, the two often produce very different answers, not only regarding size of audience but from a targeting standpoint, as well.

    I should also point out that a few million set top boxes intertwined with various third party databases covering only some of the products/services that advertise on TV is a far cry from "audience buying" on a national scale. All it gives you is a possible alternative to the customary age/sex "targeting" now in vogue for certain categories of advertisers; whether this will make a difference is also debatable. After all, we have had such data from single source surveys like Simmons, BRI, TGI, and MRI for decades and it wasn't used----not because it was human based rather than electronic, but because it's application was impractical. For example a typical TV upfront buy, involving 10 or 20 brands, is bought as if they were one large brand, not individually. That being the case, what index do you use to adjust your Nielsen ratings? Or do you average the indices for all 10 or 20 brands, weighted by ad dollars or GRP goals?

  4. John Piccone from Simulmedia, May 22, 2015 at 4:17 p.m.

    Ed - Thanks for the feedback. You are right that self reported data sets have ruled the roost in the past, however this new direct matching process will complement those systems while providing new clarity about brand specific return on ad spend for television advertising. 

  5. Daniel Caccamo from Convertant, May 26, 2015 at 7:10 p.m.

    Highly regarded as a channel that gets consumers interest in the awareness stage of a purchase journey, TV can also curate or nurture a potential customer in later stages. An example is that an auto purchase journey may be nurtured by the OEM in awareness and desire stages but it is in intent that a shopper makes a dealer choice. All purchase journeys are unique. The key to maximizing the revenue opprotunity will be to programmatically deliver the correct content to the right machine number/IP address at the right time. This is where big/fast data will become Good Data making all things work seamlessly together creating new ways to increase cutomer experience indexes.

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