Does Advertising And Digital Behavior Lack A Unified Theory And Method For Measurement And Analysis?
Major brainpower and capital is spent measuring digital behavior in the context of the performance of customer acquisition sources. I mean referrers, like search (seo/sem), crm, emails, and other forms of paid, owned, and/or earned media;and, then spending mental energy and money optimizing digital customer experience for conversion and/or retention. Digital analytical evolution over the last several years should no longer support a focus only on the linear flow of acquisition to conversion to loyalty. The devolution of the "funnel" metaphor (are we not measurers?) makes sense because of the complexity of the digital and non-digital ecosystem, which has a multitude of customer touchpoints that lead to value-generating customer performance. Do you believe the linear "funnel" is insufficient? Is it really a "tumbler"?
The recurring theme of "measuring multichannel" and considering the impact of "cross channel" -- online, offline, and nonline -- is more than a nascent, emerging analytical gestalt. The multichannel ideal I postulated a few years ago requires review of organizational structure, cross-functional alignment, reengineered process, and improved technology -- as well as smart people. The multichannel ideal means truthfully bringing together the data from many different sources and analyzing the data in an integrated way to answer complex business questions that generate revenue or reduce cost. Telling "data stories" enables the creation of economic value through the detection of new insights that help leaders take action to improve the customer experience. For example, integrating data from the website, television (set-top boxes), mobile apps, social media, qualitative research (VOC and surveys) into a holistic, full view of the customer at various stages in the lifecycle.
Taking a step back from the grand vision of the multichannel customer experience and how analytics enables The Understanding, some "off-site" channels integrate well with digital analytics. Marketing campaigns like email and paid and organic search integrate fairly easily with site behavioral data. But it is more challenging to bring effectively together behavioral analytics with online advertising. I am not talking about simple campaign coding. Instead larger opportunities for more highly relevant, value-generating, linkages exist between off-site (and offline) advertising behavior and on-site customer behavior. Huge opportunities exist in this type of integration for a few reasons:
1) Online advertising represents 15% of the total advertising spend in 2011, a figure nearing $500 billion globally annually -- more than magazine and radio advertising "spend" in digital combined, which is predicted to grow at 16% percent per year forward into 2015.
2) Most agencies and online advertisers don't have a solid understanding of site behavioral data that results from media buying, placements, and exposures. Nor do they have the staff -- because there are not enough people around with this understanding.
3) Web analysts --- the people that do the digital data drilling -- are well positioned to comprehend the full customer lifecycle because they not only understand "digital" but also arguably optimize the most important part: the path to purchase and where the money finally changes hands online.
The (global) Internet industry requires a more integrated methodology, system, grand process that provides a data-driven narrative for proving advertising effectiveness and customer value generation from high-order ideas, such as awareness and favorability, rather than a more concrete and infinitely easier (and less expensive to measure) concepts like conversion to loyalty (and all the steps between).
No compelling mental or technical model exists, supported by data, for this ideal and digital narrative. A data-realized, business focused idea of how advertising relates to on-site value generation, beyond common attribution and media mix modeling, does not appear to exist today solidly and as unified whole. Parts of how this multichannel idea works and fits together exist in various systems, research, and data provided by vendors strewn across a global Internet landscape, mostly fragmented -- which to some degree, can be stitched together by well-resourced analytics teams (that hardly exist).
Again, I am talking about a data-driven, real framework and technology for communicating and proving how advertising creates value from and by digital on-site behavior. If you are an advocate of the linear funnel, such a theory for linking advertising to behavior to value creation might read something like this:
1) Creates awareness through differentiation.
2) Positions the product or service such that it evokes favorability.
3) Reaches enough people so the advertising strengthens the brand and supports or maintains brand equity.
4) Informs purchasing behavior via a certain frequency of exposures.
5) Leads to a site visit via clickthrough (direct) or view-through (direct).
6) Compels a direct purchase from which economic value is created.
7) Generates or sustains loyalty and reactivation during the next cycle of realization of the intent to purchase.
In 2011, brands have to, basically, break up this theory into its constituent parts to understand it. Web analytics can measure 5, 6, and some of 7, but what about 1-4?
1 and 2 are the domain of advertising research, brand awareness, and qualitative brand studies. Online response-based inputs to these studies can be integrated (via cookies or login) with past and future Web behavioral data. Some vendors are attempting to do this work today.
For 3 and 4 we have media planners using third-party tools that have few standards (but MRC accreditation!). Behavioral data from site analytics adds a dimension of customer performance to those media plans. In other words, site data can qualify reach with performance and correlate it to exposure on a referring site-by-site basis. Still companies are getting informed of only pieces of the theory above, in silos, from various sources, and rarely unified.
Taking a step back, if you are an advocate of the non-linear "tumbler," such a theory like the one below may apply (in a way Joel Rubinson helped me clarify):
· Seeking. You determine a need for something, such as a product (or service) in the context of not being aware of what you aren't aware. Then media like TV, radio, word of mouth, billboards, and maybe even the Internet help you gain awareness and identify what is favorable to you, which you may or may not be exposed via one or more messages that position the product (or service). Sometimes you just stumble upon what you think you may or may not need or want when you are looking for something else. As Joel says, "different media amplify that."
· Shopping. Simple to understand, but complex in the sense of "shopping around" and jumping back and forth between the "seeking" (via various media) and then from what may or may not come next or came before.
· Sharing. Amazingly complex. I tell you in the terminal of the airport, 10-4 you on my HAM radio or CB, sms you, call you, read it on the wall of the stall, read your Tweet, answer your Quora, like and listen to you on Facebook, see it on a video site, talk about it at dinner, read it in a magazine, hear a stranger talking about it on the subway platform, and so on and so forth.
And then the potential or actual customer jumps in and out and across these phases in parallel in our global culture of consumption. Hence, the "tumbler."
The current state, however challenging, seems like a huge opportunity to me. I often wonder why few, if any, people and companies, are truly stepping up to solve the multichannel question in the context of online advertising, the shopper experience and path to purchase across all phases of the customer lifecycle with a truly unified vision for fitting these concepts together to generate economic value.