There’s a lot to unpack here, so let’s break it down. The insights include:
- Where the opportunities lie.
- The Backstory: The death by incrementalism.
- The “sea of sameness.”
- So many “tech” platforms, so little differentiation.
- AdTech over experience — What the #$&^!
- Let’s build the future together.
Where the opportunities lie.
Where do we go from here? Let’s start with “and now for the rest of the story”thanks to Paul Harvey. We’re at another inflection point in the maturing of what we consider to be “digital.” As we bifurcate what digital actually is into discrete experiences and channels such as voice, customer engagement, in-store, device, app, legacy web, digital experiential, ML, AI, VR and MR, among other hybrid engagement models, the reality is most investment today is focused on AdTech, MarTech, ML and AI within the PE and VC categories and at the enterprise level.
The interesting perspective, having spent 27+ years in digital strategy, is there’s one common equation that continues to elude most organizations. That “common equation” is simply desired outcomes. Nearly a century later, we continue to operate blindly as it relates to understanding of audience desires and successful outcomes. The latest ML and AI-based models do little to improve on past performance of behavioral attribution, targeting / re-targeting, personalization, etc. Whether stylist companies such as Stitch Fix, thredUp, Trunk Club or airlines, hotels, financial services companies, brick and mortar retail, etc., the level of customer understanding and alignment of the relationship to desired outcomes on both parts remains an ill fit, at best.
With this context, there are two key areas of opportunity, one of which is a future state belief.
It’s been nearly 28 years since the Tim Berners-Lee released the source code for the world’s first web browser and the experience has, for all intent, not fundamentally changed. The reason is simple — the way we monetize hasn’t changed. From the 1940’s on, airwaves have monetized through advertising. Newspapers monetized through a hybrid model of subscription and advertising. Think about today’s experiences. What’s changed? Retail. What’s changed? The fact that we collect data, build what we believe are “sophisticated models” using a myriad of MarTech and AdTech and attempt to guess what will create a “dopamine hit” that leads to a defined transaction will clearly be laughable decades from now.
The reality is simple. We guess, rather than know. We assume, rather than ask. We spend hundreds of billions with an understanding that the current approaches and supporting SaaS tools deliver < 3% return. The answer is as simple as the challenge: ask and reward. By ask, it’s an actual question with a desired outcome that’s rewarded. Today, we know so little about desired behaviors and intended outcomes; yet, we assume through ML, AI, etc. that we can guess what will motivate an action. The concept of transparency is counter-intuitive to the industries we’ve created. We’ve amassed a plethora of survey technologies, 3rd party data broker solutions, 1st party cookies, pixels, tags, etc. We’ve developed category after category of SaaS platforms without taking into consideration a simple concept: ask questions, reward customers and eliminate wasted investment and audience frustration.
Transparency is a basic, foundational principle. Today, there are hundreds if not thousands of “views” of Bob Morris. Each one is the equivalent of the story of the blind man and the elephant. Each perspective is based on a slice of interaction possibly augmented by a series of web interactions coupled with 3rd party appends. That approach hasn’t changed in decades. Why companies fail to expose what they know about a person with the goal of rewarding behavior that provides accurate understanding of desires, preferences, goals, etc. is beyond mind numbing. Transparency goes two ways. Companies provide what they know, and customers / prospects clean and augment the data and maintain it. Ultimately, this data should become a unified profile that lives across digital channels, accessible by companies, monetized by the individual as access is granted and new data appended. The result is reduced spend, reallocation of investment in valuable experiences, offers, and ultimately, investment in product quality, new innovation, adjusted pricing, etc. A recent analysis of ad spend by one of the largest auto insurers in the U.S. demonstrates the value of transparency. For each current / active policy (13M), the company spends $82 USD in policy premiums per customer to advertise to acquire the next “new” customer. Think about the logic behind that spend. Simply, ask… is it transparent?
2. Consolidation— Today, conversations revolve around Containers, Headless, MACH, ML, Blockchain, ____Ops. etc. while the fragmentation of experience, volume of vendors and requirements for discrete skills / experience continues to compound the issues. For the audience, the proliferation of channels and lack of integration creates an inherently frustrating experience. I’ll use a real example. My daughter turned 16 yesterday. As a fun, scavenger hunt / TikTok experience, she and her sister decided to see what “free” items were available for people on their birthdays. A simple search and voilà! — so many opportunities. But, wait… she had to begin w/ registering w/ a website or an app. She then had to receive a confirmation code via text or an email, which meant she gave her phone number, email, date of birth, gender, in many instances she had to turn on her location services and on and on… In the end, 3 companies were able to provide her with the birthday “gift” they claimed they could fulfill. So, why only 3? First, system integration issues — in some cases the email confirming registration didn’t arrive within 24 hours, so her birthday passed. In some instances, the app doesn’t update hourly or daily. In one large, highly recognized brand, it takes up to 3 days for your registration to be activated — What? And in some instances, it’s a multi-step process with registration on the app, an email is sent with a confirmation link, which then links to a website, not the app and then you have to login to the app — Again, what? And yes, TikTok is the single largest beneficiary of this exercise capturing more insights and data than those companies attempting to monetize with product sales vs. ad sales.
The concept of frictionless remains elusive. The plethora of use cases that are unique to sites and app platforms, the idea of moving from device to device (e.g. Alexa, Google Home, site chat, text, email, web app, etc.) with each channel leveraging a different set of data and therefore a uniquely discrete persona makes each channel a frustrating experience. Few companies have solved for this issue and those who have are only beginning to tap the opportunity before them. This is where the future vision becomes part of the narrative. The reality appears to be consolidation, but it requires a fundamental shift in how we value industry collaboration. The answer is simple, yet incredibly complex. The use case is included below. Think about this for a few moments and provide your perspectives after you’ve finished reading this thought piece.
We use a laptop to work within an OS with specific SaaS tools (e.g. MSFT Word, Excel, PPT, Safari, Outlook, Teams, Slack, Mural, Evernote, Adobe Creative Cloud, etc.). The question is why is the operating system separate from the web? Why do we have web apps, apps, texting, email, etc.? Why is each channel discrete? Why do we drop pixels, tags, cookies, etc. on web experiences while tracking app usage differently? Why does my Alexa experience not align to my desktop experience, my browser extensions or my chat session? Today, we operate similarly to the 50’s, just across different digital platforms. What once was direct mail, phone (landline), television advertising and radio is now “digital,” yet neanderthal, knuckle dragging at best.
The future is defined by a consolidated interface — effectively a common app interface with a single view of the audience where value exchange is based on mutual understanding through transparency and common functions delivered consistently. Yes, we will look back on today’s version of digital as we do silent films.
What will drive change?
We’ve begun a slight shift as it relates to the data captured and stored on individuals as an outcome of GDPR, and now Apple has stepped in, not because they’re such a great corporate citizen fighting for the rights of the individual and their “ownership” of their personal data, but because others were monetizing off of their platform and they weren’t. What is a transparent layer of understanding anyway? We guess and we assume as an industry. We think we know what people mean, what they want, what they prefer, but we really don’t know. It’s why 0.0004% of advertising converts. When we break down digital engagement it essentially falls into three categories:
Utility as a whole is represented in apps we use, many of which contain paid levels that provide an opt-out function for advertising and data collection and monetization. Beyond apps are experiences that are highly task oriented from contactless payments to Amazon’s new Dash Cart and devices such as the Peloton. When we think of utility, the concept of autonomous vehicles becomes a clear use case, although there is an element of entertainment involved, but that’s for those who catch a glimpse of the person passing at 70 mph asleep behind the wheel.
Information today is served through a variety of ways with most being ad supported, focused on data collection and targeting / retargeting. As an industry, companies haven’t evolved from the 1940’s approach to “free” content supported by ads or premium gated content in return for payment or a willingness to provide additional layers of access to personal insights.
Entertainment is everywhere and yes, the monetization model is primarily driven by personal behavior and the collection of data. Snap, Instagram, Facebook, TikTok, Pinterest, etc. all make money using effectively the same approach with minimal variations.
In the early days of digital, back when the term most frequently used was “multimedia,” there were no pre-defined “best practices” or standards. Each solution was bespoke, focused exclusively on solving for a unique business proposition. From experience, whether developing a strategy for how to design a solution to allow consumers to configure a Dodge truck at home or how to specify a bowling alley with costing, while rendering the design in 3D on the fly, we were pioneering and solving in parallel. Today, we live in a digital world of MarTech and AdTech where templates, no-code, low code, containers, headless, DMPs, CDPs, attribution, retargeting, AR, VR, MR, ML AI, etc. represent the breadth and depth of investment and focus. With nearly 10K SaaS solutions in the Marketing Technology Landscape https://chiefmartec.com, we’ve reached a point where the differentiation between each platform and competitive solutions is nearly indistinguishable.
In 2012, the company I co-founded was selected as the strategic partner for GE Capital as they undertook a daunting task of standing up a digital “only” bank in response to Federal requirements. This consumer deposit focused bank had to be in-market within 6 months of the time of our initial engagement. With the requirements for the initial release of the bank complete, 14 categories of technologies were defined including 72 vendors that were to be evaluated through a RFP process and in-person presentations in support of validating use cases. Today, based on the same requirements, this exercise would be exponential in scope. By mere estimation, the number of categories would be 40+ and the number of vendors would entail nearly 600 companies.
The proliferation of technologies that are “me too” has been overwhelming in an era of essentially free cash with VC, PE and alternative financing readily available. So, if this is the case, why is nearly every new feature set, new capability, new tool, etc. an incremental step, at best, from existing solutions?
The answer is actually quite simple. First, the digital industry as a whole is effectively driven by a herd mentality. For anyone that’s raised capital, the business case must contain a plan to capitalize on an opportunity that is clearly defined. In order to define the opportunity, it has to have benchmark(s) to provide context for investors. These benchmarks define expectations for rates of return, multiples and market demand for acquisition, IPO or EPS contribution. Although VC tends to lean to higher risk, the reality is their portfolios must represent a balance of significant exits with those that result in business failures. Second, we live in a copy and paste world. Innovation within the digital industry is based on improving on existing concepts. This isn’t a “universalism,” as there are solutions that are breakthrough or breakout, but most are quite simply a repeat with slight enhancements. When you review Scott Brinker’s Marketing Technology Landscape, it’s inherently clear why there are so few SaaS platform categories. It’s simply because they’re all just dimensions of one another. The difference between Adobe Experience Cloud, Salesforce Marketing Cloud and Oracle Marketing Cloud is reflected in “incremental” methods, functions and capabilities. Just by way of brand names, note the herd mentality reflected in the term “Marketing Cloud.” Vendor selection in many instances is based on preference, bias, relationships, pricing and presentation quality. Simply put, it’s a race to commoditization.
Let’s take a moment to delve a bit deeper into the theme of “death by incrementalism.” Have you ever asked yourself why so many site and app experiences are similar? First, someone of influence decries a “best practice” and from there it’s sacrosanct. So a 3 x 3 or 4 x 4 grid of product images and descriptions on a static page layout is going to deliver the best customer experience and highest conversion? Actually, the answer is No, it’s not. However, because the Lemming have turned right and plunged off the cliff, so goes the rest of the industry. By creating standards, commonality, etc. companies create inherent audience bias, which in turn makes it difficult to change design patterns as they’re just that “different.” We’re, as humans, trained by companies to expect a specific experience, not that it’s better or worse, just simply trained to know that when the site or app refreshes, there’s already a foundational expectation for what the template and experience will include. There’s no need for interpretation or adjustment because the minimum expectation has been met. So it’s with this in mind that companies test. They do A/B and multivariate testing but rarely make substantive changes. For performance marketers, these changes include color, font size, copy (Get a Free Quote vs. Get a Quote or Limited Time Only vs. Limited Availability, etc.). We live in a digital world in which success is measured not by innovation and risk taking but by imitation and lack of imagination. Think for a moment about the difference between Instagram, SNAP and TikTok. Each new feature release is essentially a copy of an existing capability within one of the other platforms, while those features being copies were actually a copy of another platform from 5–10 years prior. The lack of innovation is built on the premise of imitation and incrementalism.
The sea of sameness.
“At a minimum, suck the least.” This is an actual quote from a C-Suite executive at a Fortune 50 company. The fear of change is greater than the implications of the change in many instances. We’ve built the foundation of corporate cultures on risk averseness, not risk taking. Think about this for a moment. When was the last time you recall a colleague being fired or losing their role / responsibility because they were too conservative in their decision making? I’m confident most will be challenged to remember a time. On the other hand, risk taking is considered a trait that’s inherently a contradiction to consistency and continuity in operations and desired outcomes. It’s the adage of “No one has ever been fired for hiring [Insert company name]. The sea of sameness is based on the premise that whatever exists must, at a minimum, be correct from a foundational perspective. Websites all look and operate essentially the same. Blogs essentially all look and operate the same. Apps, well? There’s a difference here, but it’s based on what are sometimes very unique business objectives. Where the business objectives are consistent (monetize content via ads, deliver influencer content, etc. they’re the equivalent of field mice) try to tell the difference.
The sea of sameness comes from a number of key elements that intersect with one another. Among these you’ll find:
- Incrementalism (Nearly identical SaaS platform functionality / capabilities)
- A template driven world of design
- Inflexible APIs
- A “paint by numbers” approach to CX — Technology first over experience
- Legacy systems exposed to the Web — effectively green screens ported to the web without consideration for value and usability
- Commonality of data and analytics products provide the same answers and recommendations (the Lemming scenario)
- Too much disparate and conflicting data to be effective
- Risk aversion — The world of quarterly EPS adherence
Taken into consideration as a collective, the items above represent the core of why so many digital experiences are nothing more than a reflection of the previous experience delivered by a competitive brand.
A straight forward example is the difference between low end commodity retail and mid-market / higher market retail web experiences. Neiman Marcus is essentially indistinguishable from Sears or JC Penny’s digital shopping experience as it’s nothing more than a template driven experience.
I’m going to deviate for a moment. Not that it’s a good or bad thing, but let’s take a moment to address the elephant in the room. We define ourselves through the lens of enneagram, Myers-Briggs, etc. as unique amalgamations of personality; yet, we’re expected to align to a consistent, template driven digital experience that’s nothing less than homogenized. The question is why, and the answer is very straight forward and disappointing, at the least. We don’t reward innovation in digital when defined through the lens of revenue. Yes, we reward innovation as an exercise in creativity — God only knows how many self-serving / aggrandizing awards the industry gives out each year, but not when it comes to anything that might create “risk” to EPS.
So, as a very thoughtful Rick Shaughnessy has said for decades — “We live in a world where everything is a race to beige.”
So many “tech” platforms, so little differentiation.
What the #*!&$! are we doing? Seriously, if I make one, two or even three, outreaches to a PE or VC contact, I can raise funds to build another look-alike platform with a few “unique” capabilities and, voilà! another new MarTech platform arrives on the market. Sadly enough, money is as close to free as we’ll ever see in our lifetimes, and there’s more of it chasing existing ideas than there are unique ideas themselves.
With a consistent approach to solving for the same challenges, the digital industry as a whole has become a combination of a M&A frenzy and a free-for-all when it comes to “copy and paste” functionality. On one hand we have companies that focus on a specific issues such as chatbots, Know Your Customer (KYC), etc. On the other, we have large enterprise scale platforms built by Adobe, Sitecore, Salesforce, Watson, ServiceNow, Acoustic, Episerver, Microsoft, Oracle, etc. that contain within their core platforms either an open API to connect to these solution providers or a competitive set of features, either acquired through M&A or copied / replicated, for all intent and purpose. With this in mind, the Marketing Technology Landscape now resembles the most complex, mind-boggling puzzle you’ve seen in a long time.
As an industry, we collectively use the same use cases. For that matter, the industry uses personas, which are so outdated as a methodology. I’ll leave this subject for another thought piece, but the concept of a near real-time, data driven persona engine that influences design and programmatic through ML is beyond a decade late in being developed. Because the same use cases are used, the overarching solve becomes the same, resulting in common tools and technologies that deliver the same experience across brands. The more embedded a technology becomes the more common the experience. In one way this creates a “known” or expected CX and outcome for audiences, while in another it creates a homogenized approach that easily delivers a consistent outcome, whether positive or negative.
When you begin a requirements assessment sprint you quickly realize that it’s nearly impossible, and financially not viable to evaluate all of the SaaS tools that exist in support of each unique use case. We’re so far beyond that capacity that each addition to the technology landscape becomes almost laughable. The process of selecting the initial list of vendors that support AI based chat functionality on a recent initiative was literally mind numbing. Microsoft, for example, has their Bot Framework product, then they have the Azure Bot Services and Virtual Agents. Just determining which of their own products aligns and how the costing is addressed took nearly a week of discussions and Microsoft colleagues themselves didn't know the difference between their own competitive products. So, back to the “For the Love of _____” experience.
Simply put, too much money, chasing too few use cases with too little risk tolerance creates overlapping, highly indistinguishable SaaS platforms that result in digital experience that are beige at best.
AdTech over experience — What the #$&^!
If there’s a consistent theme when it comes to the need to rethink digital experiences, it’s one that resonates across the industry. First, too many experiences are built on monetizing personal behavior. Let me be clear, this is a serious issue. Second, the legacy construct that dates back to July 1, 1941 when the first paid TV ad debuted on New York station WNBT, remains little changed at the core of strategy. Yes, we have incredible amounts of 1st party and 3rd party data with ML and AI targeting engines, but the same rules still apply. Company A provides a “free” service in return for selling access to a company that wants to advertise to you. We’re just more sophisticated today, although that means very little when it comes to truly understanding audiences and intent, especially as it relates to timing of decisions and purchase behavior. Think about that for a moment. How often are you retargeted from a search on a site? How often have you purchased the product or service and continue to receive re-targeting for weeks or months? A terrific example of the failure of AdTech, media planning and buying strategies can be found in the auto insurance category. Having led strategic initiatives in this space, I can, with authority, state that the average individual that searches on any term or phrase related to purchasing auto insurance will do so within a 48 hour window of completing their research phase prior to quote and binding phases. So, when Progressive continues to retarget a person for nearly 4 weeks, every impression they serve is an absolute waste of advertising space and the individual’s time.
The narrative is clear. With the proliferation of AdTech rivaling that of MarTech, let’s take a look at why this matters. There are those that will argue that AdTech and MarTech are essentially synonymous with the differences being reflected in the implementation within the funnel and, in fact, the same platforms can be used for dual purposes (e.g. DMPs). When we look at the proliferation of SaaS tools built for programmatic ad buying (DSPs) across channels including paid ads on Instagram, Snap, Pinterest, Twitter, LinkedIn, etc., it’s astounding. When we add tools for influencer marketing designed for brands to compensate promotion by individual (influencers), the breadth of tools becomes even more crowded. Where the overlap exists between AdTech and MarTech is in how platforms such as DMPs are used (e.g. website personalization, email campaigns, chatbot engagement, site side search, etc.). Where the platforms deviate is in the end objective. AdTech is intended to drive awareness and click thru. Yes, while there are arguments to be had for etherial constructs related to mental models and influence, the simple fact of advertising is brand+ message+medium+[known quantity / data]=outcome. Where MarTech aligns is specifically in context of the destination experience. While DMPs ingest, digest and express data across the boundary of AdTech and MarTech, the core of MarTech is focused on delivering the appropriate experience based on parameters served.
The fact that digital ad spend equated to $335B in 2020 with an average click thru rate of 1.75% and a landing page conversion rate of 2.5%, the approx. $147M worth of media value is 0.0004 of return on ad spend (RoAS). It’s difficult to find any other industries that have that poor of a performance and yet the investments continue to flow into new AdTech.
Let’s Build the Future Together
It’s time to rethink digital. It’s time to rethink business models. It’s time to ask why we look to the past to define the future. Add your perspectives and your comments. What’s your vision for the future of digital?
You can reach me on Twitter — @digitalquotient or on LinkedIn — https://www.linkedin.com/in/bobmorris/