Before the great adtech boom, the advertising model was straightforward – if not simple. Possibly the first and most well-known unifying marketing principle was the famous “Four Ps” that dominated the “modern” marketing machine for years. This model was deployed by best-in-class companies like P&G and it guided everything from product development to “promotion.” End of story.
Then “digital” happened and the old model collapsed in a heap of bytes and algorithms and platforms. As marketers struggled to make sense of it all, technologists helpfully (snark alert), filled the void by creating architectures organizing marketing technology into ever fragmenting segments.
This is when we see organizing marketing models circulating like confetti at an adtech party – dazzling at first but a nightmare to clean up in the sober morning that follows. There was LumaScape eye-chart schemas to help marketers bring structure to the thousands of companies that entered the adtech space over a relatively short amount of time. There was the PEO model – Paid, Earned, Owed which then evolved into the Paid/ Earned/ Shared/ Owned (PESO) model to integrate the explosion of adtech.
All these models were created by adtech firms to help marketing adopt automation. The promises were alluring – unlock customer engagement while reducing costs including, hopefully, paid media costs.
The “Paid/ Earned/ Owned/ Shared” Tech-scape
Figure A. Source: Pyxl – http://thinkpyxl.com/blog/peso-model-pr
As a unifying models go, these organizing principles failed precisely because they needed marketers to adapt to adtech when adtech should reflect how marketers work. Worse, as marketers frantically tried to adapt to adtech as fast as possible, it turned out to be a distraction from the harsh reality that these marketing models were stuffed with tech but thin in creating recognizable outcomes around the very human business of customer conversion.
Yet the enduring allure of marketing tech attracted marketers like a moth to a flame. Unhappily, like the proverbial moth, many a marketer have combusted on a pyre of incomprehensible data and an ever-muddled understanding of the impacts of marketing on a business.
So if the unifying marketing models of the last 10 years have outlived their usefulness, what will take its place? The answer lies in shifting to a human-centric unifying principle of digital marketing that reflects how humans make marketing and how humans respond to marketing.
Embrace the New Unifying Principle of Digital Marketing: BRAND-TO-DEMAND Marketing.
I first heard the term, Brand-to-Demand, in 2016 from a colleague who has since passed away*. I never knew if it was her idea or she got it from somewhere else. Doesn’t matter. What does matter is that it created a very different model that put brand advertising and demand generation marketing on the same, unified communications continuum. Savvy marketers know how to move users from one stage to another effortlessly whereas less sophisticated marketers create herky-jerky user experiences that are hard to monetize because measurement data is silo’s and/ or aggregated but still lacking real intelligence.
To embrace a people-centric, Brand-To Demand unifying principle, we must both; 1) dismantle heretofore sacred truths and 2) replace these outdated “truths” with a unifying theory of adtech that is, no surprise, not about tech at all. It is about resisting automation as a silver unifying bullet and to be disciplined first create the unifying principle’s strategy that aims clearly at key acquisition outcomes – the prize at the end of the unifying process.
This is a two-step process:
Step 1 – Confront the reality of adtech promises made and broken.
Doubt The Promises of Automation Efficiency
The most lethal arrow to aim at the heart of automation-centric unifying models based is to truly accept these platforms will ever result in a cost reduction for marketers.
Let’s take as an example some of the top CRM platforms. They often come with sales modules which, maddeningly IMHO, are separate from marketing modules. How can this be? It’s obvious that a marketing behavior should lead to a sales potential and back again. By segmenting these functions between two separate modules, the platform makes bank because the platform is more expensive to buy.
But we’re not out of the “cost” woods yet. As these platforms evolve with new features, they often require new employees or consultants to configure and operate these systems. Too too often, it turns out the extra cost of these platforms do not pay for themselves because it takes even more money to buy another platform to put all the data pieces together to tell an even more confusing story that has, alas, many pretty charts.
A workable unifying principle of adtech is to assume automation platform efficiency may never be a net gain for the organization. It will make some tasks easier, but you will be well-served to understand that the cost/ value equation of automation platforms lies in executing specific tasks – not as a platform to reduce overall acquisition costs.
Once you finally realize that this will probably never realize a cost savings for the organization, it then is incumbent on marketers to reconcile the fact that operational costs will increase much faster than customer engagement or outcomes. This fact is unlikely to change in the near future – possibly never.
The reality is that no matter how much marketing costs go up, it is a black hole of expenses because the whole system relies on the devil in the data details which then requires a whole new set of technologies and technologists to sort all the data to make it at all useful.
Unless you change the game and simplify the data requirements for ROI measurement, you will not improve your ability to see clearly in the data fog.
Step 2: Activating the new unifying principle of adtech: BRAND-TO-DEMAND Marketing.
The Brand-To-Demand mindset is the model to solves two key issues facing marketers today; over reliance on automation that is misaimed and overstimulation from data that confuses rather than clarifies.
This model changes the game because it is able to unify the many and fragmented tech touchpoints available, like chat or email or even podcasts, into a natural experience that recognizes Brand-To-Demand is a fundamentally unified communications process that is topic-based, (communications always is topic-based). It is not about technology or automation.
In this context, like all communications plans, there is a strategy and tactical roadmap. In the Brand-To-Demand unifying principle, this means a strategy and plan that merge data architectures with on/ off line media channel performance.
Strategically, the unifying principle of Brand-To-Demand is designed to activate a communications sequence about topics users find important. By tapping into the rhythms of user topic discovery, you can understand how users move from “brand” content to conversion. In short, you can measure the topic journey to conversion with precision but with clarity to understand what is driving results.
Tactically, this also means you should radically prune to only the data you need to only measure outcomes. You’d be surprised to realize how much data is superfluous to the mission-critical business of measuring outcomes. Too much data is like too much clutter in a room – you can’t see the dimensions of the room at all.
Then we are left with the question about how to determine the critical data path of measurement?
This is where we can innovate by merging the power of topic data and marketing automation (ie – in CRM systems) to become highly productive. A topic-centric paradigm frees marketers from trying to untangle the Gordian Knot of identity. By worrying less about specific data profiles, and just focusing on aggregated topic journeys to conversion you can clearly see the critical topics that lead to outcomes. Once you simplify the data in the Brand-To-Demand unifying model, you understand what happened in the past and what to do in the future to increase results.
No need to worry about merging online/ offline media since you are measuring the topic campaign level expenditures – not any specific channel.
No need for privacy-busting profile personas or expensive data “enrichment” data layers that defy effective targeting in the real world.
No need for expensive consultants and dashboards to measure every behavior or interaction that is superfluous to measuring actual outcomes. By simplifying the model needed to understand clear outcomes, a Brand-To-Demand’s unifying model centers on bringing structure to the mission-critical topic journey to conversion process.
Putting it all together.
Here is the structure for how this works in the real world.
Figure B: Source: engageSimply 2023 ©
1) “Brand” – New Audience Generation: This is about getting net new audiences into the brand funnel as efficiently as possible. Functionally this includes SEM, contextual media, content development platforms, PR, social and paid media.
2) “To” – Inbound Audience Management: These activities are gears that propel users toward an optimized experience – all based on topics but with an automation kicker. Examples here include inbound marketing automation such as email capture for a new research paper, content recommendation engines, email marketing and even corporate social responsibility programs. The “To” phase is the critical step that moves marketing leads to the sales lead funnels. The communications element here is to determine the what criterion qualifies a lead to graduate from a marketing lead to a sales lead. Once these criteria have been established, then automation adtech is well equipped to execute.
3) Demand – Audience Conversion: This is the “show me the money” part of the equation. Key components here are A/B testing platforms, sales automation, lead qualification/ generation, demo’s, digital directories, events, and resource allocation modeling.
As a user moves through the Brand-To-Demand journey, the unifying principle is to honor the topic journey to conversion as a process – not a one-time event or something that can be coerced. The vision of an evidence-based Brand-To-Demand is a marketing model where the user’s topic conversion experience is the only important unifying principle.
It is possible to achieve a human-centered, automation-powered structure geared to user engagement and conversion. It is all driven by intelligence, Topic Intelligence (.ai) to be precise.
* Author’s note: Laura Misdom was Marketing Director at leading organizations including AT&T and Avaya. Her clarity of vision was an inspiration to me then and continues to inspire me today. In her honor, I offer any organization an adtech architecture audit gratis. My mission is to help companies keep what’s good, ditch what’s bad and learn to know the difference.