How I Leveraged My 5-Year-Old to Prepare for AI

Over the span of my career, I have had opportunities to mentor future data-driven business leaders. The advice I used to give primarily revolved around the hottest analytical tools and certifications and how to tell stories through data. Five years ago, however, my advice evolved in a very dramatic way, based on a reasonably benign event.

Over the span of my career, I have had opportunities to mentor future data-driven business leaders. The advice I used to give primarily revolved around the hottest analytical tools and certifications and how to tell stories through data. Five years ago, however, my advice evolved in a very dramatic way, based on a reasonably benign event.

My wife, our two daughters and I were on a multi-state road trip. Early on, we decided to make a pit stop. My wife gave the girls $5 each to buy goodies for the road — with no conditions. Unleashed from the shackles of healthy snacking, my older daughter set about making the most her newfound economic freedom. Analytically inclined, my oldest began optimizing for the right combination of quantity, quality and taste that would provide her with the maximum overall satisfaction. My younger daughter (five years old at the time), quickly picked up her favorite fruit candy, asked my wife for a suggestion and purchased that, as well. Eager to get back on the road, I asked my oldest to finalize her decision quickly. My request was met with a look of sheer horror and frustration as she frantically searched for the optimal basket of goods that $5 would buy. With hope that the optimal solutions was only minutes away, she begged for more time to no avail.

Back on the road, my younger daughter offered my wife a substantial portion of the candy she had recommended. Astonished, my wife says, “Sweetie, if you share that with me, you will have less for the trip.” To which my daughter replied, “That’s okay, Mom. I know you like these candies. Can I have another five dollars?” To which my wife uncharacteristically replied: “Of course!” Shocked at these turn of events, my older daughter protested “What? No fair, you can do that!?”

Data Is an Equal Opportunity Enabler

I often think about that incident; especially when I am trying to help clients achieve better results through analytics. This incident is a great allegorical example of why data-driven decisions, when done well, can improve specific results, but many times fail to change the overall game. A 2015 study by KPMG identified operational efficiencies as the primary beneficiary of data and analytics in the near horizon and a more recent study in HBR also confirms that most data and analytics success is still focused on low-hanging operational opportunities. In both reports, business leaders also recognize the transformational opportunities of data and analytics. However, they will also identify an acute need for new and unique skill sets to make those transformational changes a reality.

This brings me back to the car ride. Before you assume this is a lesson about how customer empathy beats algorithms, I can assure you it is not. Not only has my younger daughter’s strategy failed on several other occasions, but I have also seen plenty of well-researched market advice from customer-centric strategy firms fail, as well. Nor do I believe this anecdote implies optimization leads to strategic myopia. (This is also not about which kid I am betting on, as they both manage to amaze and worry me in equal doses.) Instead, the lesson for me is that while analytical rigor can be foundational to disruptive innovation, the optimal solutions algorithms provide only reflect the audacity of the optimizer’s vision.

The body of recent research on successful disruptors dispels the belief that they are solely the product of a brilliant idea conceived by a highly intuitive visionary. Instead, their very existence is often an optimization exercise involving many experiments. Not only do successful new entrants go through many failed iterations, but they also emerge through the crucible of other competing ventures with similar industry disrupting objectives. Once emerged and unleashed, there is still no guarantee that the new ventures are the absolutely optimal solution. One needs only to think of MySpace, AOL and Yahoo if there is doubt. As a result, the body of knowledge on innovation is now focusing around the concept of failing fast, failing early and failing often. A critical component of the “failing for success” strategy involves testing, measuring, and optimizing rapidly and regularly and but also involves having a broad view of the playing field and the bravery to challenge existing assumptions.

AI Whisperers Wanted

The career implications of these trends for data-driven talent are significant. As analytics takes a central role in strategic business functions, it does not necessarily mean that my fellow quant jocks will rule the future. This is because traditional optimization algorithms are just beginning to transition into artificial intelligence-based solutions with the ability to learn on their own and at some point human talent will no longer be needed to build models. If you are in analytics today, it will be important to keep up with the evolution of AI solutions, but even more critical is developing your analytical creativity and bravery.

Why Brand-Tracking Needs an Overhaul

Have you noticed how disconnected brand-tracking has become with actual consumer behavior? You might run a great new ad or build a new positioning in the market, and the tracker may even show an uptick in brand consideration. Nevertheless, when it comes to hard behavioral metrics (such as purchase volume), they remain unaffected.

Branding
“Branding,” Creative Commons license. | Credit: Flickr by Limelight Leads

Have you noticed how disconnected brand-tracking has become with actual consumer behavior? You might run a great new ad or build a new positioning in the market, and the tracker may even show an uptick in brand consideration. Nevertheless, when it comes to hard behavioral metrics (such as purchase volume), they remain unaffected.

Underlying Trends

According to a new study by Trinity Mirror, almost 70 percent of consumers don’t trust advertising and 42 percent distrust brands and view them as self-serving. Several other studies are finding similar conclusions. Despite this trend, it may be premature to say that brand advertising no longer works. Rather, the larger consensus seems to be that brands must find new ways to convey authenticity and sincerity beyond the ad. In many cases, brands are responding by focusing on brand purpose and brand experience in addition to traditional brand communication.

When it comes to brand-tracking, the problem is that most trackers are still tied to the traditional linear relationship between stated brand consideration and sales. While always a bit tenuous, the relationship made much more sense in the era of push marketing. Now, however, the consumer’s purchase decision process has fundamentally changed. More and more, consumers develop brand preference through experiences and by observing brands living up to their stated brand purpose. Not only does this new dynamic take time to measure, more importantly, but it also requires a well thought out measurement strategy. Let’s assume one of your brand propositions is “valuing the consumer’s time.” In this case, more important than measuring consideration is tracking if the consumer actually views you as valuing of their time. Furthermore, where in your transaction chain are you living up to that promise and where do you fail? Can you confirm this through behavioral data, such as a decrease in abandoned website shopping carts or fewer billing inquiries?

How Brand-Tracking Needs to Evolve

First, brand monitoring needs to be part of a larger consumer intelligence database. Integrating brand with NPS data, customer experience data and behavioral data is critical to understanding how your brand is performing. One significant advantage of this approach is that you may find that all the underlying brand principles are tracking upward, but brand consideration remains unchanged. Knowing this early may save you millions in investments on a brand strategy that is potentially not providing the market advantage you hoped for. Without tracking the underlying brand principles, you would be left wondering if the strategy is bad or if the execution is not working.

Next, build a custom brand measurement strategy. Because great brands are now structured around a unique purpose and experience, measurement strategies cannot be off the shelf. I commonly encounter brand-trackers that create more questions than they answer. While this can be spun into a positive, in pragmatic reality it wastes time and delays decisions. The underlying reason this happens is that companies fail to measure the specific changes and perceptions they are uniquely trying to affect.

Revisiting the brand proposition of “valuing the consumer’s time,” do you know how you will actually measure success on this proposition? When is the right time to ask the consumer? Is it solely the consumer’s responsibility to tell you how you are doing? What other ways can you listen to consumers besides a survey? What can you know from their behavior?

Having a clear vision of the underlying experience, behaviors, and perceptions you are trying to create and knowing how you will measure them will go a long way toward understanding how your brand is resonating in the market.

Recruiting Tech: Is a Robot Interview a Good Brand Look?

I often talk and write about the explosion of marketing technology and how it can lead companies to focus on tactical wins while ignoring or hurting long-term consumer brand development. I would also apply the same caution to recruiting technologies.

You get an email from the CEO titled, “How do we become a destination employer?” You know this is a not-so-subtle hint in reference to the last “VP of Sales” candidate who came in a T-shirt, jeans and flip flops; or perhaps it is in reference to the one before, who averted eye contact and often gave one-word responses.

To get ahead of these pitfalls, some companies are using recruiting technology platforms to filter out duds early in the process. While the platforms are indeed powerful and have the potential to add data and structure to a process that has historically been very subjective and disorganized, this is another great example of the “land of shiny objects,” where the ability to do cool things has outpaced the strategic thinking of why things should be done. In this case, we find a budding industry that has built powerful tools to help companies design interviewing and recruiting experiences that work for their needs. However, I was curious as to what impact this is having on the Employer Brand from the perspective of the candidates, and if employers are going to get burned. I spoke to a friend who came across this experience during her job search, and she had some interesting insights to share.

A Candidate’s Experience With Recruiting Tech

Her first assumption, when informed about a video interview, was that it would be over Skype. Her first shock was learning that there would not be another person on the other end; but rather a technology platform, which would ask the questions. “It took me a while to understand that my first interviewer would not be a human. This was unfamiliar territory.” After she realized that she would be talking to a technology platform, her next reaction was a flood of questions, mixed with anxiety.

  • “What questions will it ask?”
  • “How much time will I have to answer questions?”
  • “What if I don’t like my response; can I have a do-over?”
  • “Will the employer be tracking how many do-overs, pauses and breaks I take?”
  • “Will the technology be analyzing facial expressions, ticks, as part of my answer?”

While the technology provider did its best to answer her concerns and was very supportive, there were some anxieties they could not address — such as the underlying reasons why the employer would put various time limits on questions, or if they would track the number of retakes and how that information would be evaluated.

During the interview, she spent hours in a locked room judging her responses and deciding if she should do a re-take or move on. “Being a perfectionist, this was not an easy process. On top of that, the unknowns were frustrating.”

She was eventually called in for an in-person interview and discovered an employer only trying to filter out non-serious candidates before investing time and energy on the next stage. Luckily for the employer, my friend was already familiar with the company, and so her negative experience was tempered by other information. Nevertheless, the experience did not reflect well on the employer.

My Take on Recruiting Tech

Despite my friend’s account, I found clear advantages to using recruiting technology platforms and, as a data-driven business consultant, I would encourage their use. However, I would also strongly suggest that employers think about the Employer Brand and plan more carefully before deploying recruiting technology.

I often talk and write about the explosion of marketing technology and how it can lead companies to focus on tactical wins while ignoring or hurting long-term consumer brand development. I would also apply the same caution to recruiting technologies, because I believe many companies are going to hurt their Employer Brand as they become enamored with new capabilities.

The right solution should begin with a vision of the Employer Brand you are trying to build and answer some important questions, such as:

  • When building the Employer Brand using technology, what will you measure and why?
  • What are the anxieties that might be created by injecting technology into the employer-employee relationship?
  • What are the trade-offs (short-term and long-term)?

While automation may be shrinking the workforce in the next decade or two (maybe not), most expectations are that the need for creative talent will increase. This means that your Employer Brand is likely to be a critical component of how companies will recruit the best creative talent. Getting lost in the land of shiny objects is not something competitive companies will be able to afford.

In the Land of Shiny Objects

I am honored and excited to become a regular contributor on Target Marketing. I am excited at the prospect of generating vibrant conversations on a set of topics that represent one of the biggest challenges marketing leaders face today. As a marketing consultant at the intersection of data, technology and customer strategy, I have observed — frequently — that there is a vast divide between brand/ customer strategy and data/technology strategy.

shiny object
(Image via The Marketing Moron)

I am honored and excited to become a regular contributor on Target Marketing. I am excited at the prospect of generating vibrant conversations on a set of topics that represent one of the biggest challenges marketing leaders face today. As a marketing consultant at the intersection of data, technology and customer strategy, I have observed — frequently — that there is a vast divide between brand/ customer strategy and data/technology strategy.

Multiple industry surveys report that few executives feel their analytics and technical implementation are well-connected and strategic. Despite the fact that most customer interaction is becoming tech-driven, the abundance of affordable tech options is leading to highly tactical and sometimes confusing customer experiences. The core issue is rarely the technology itself. Most solutions can work just fine at driving greater customer engagement and building brand equity. The real impediments are often organizational and strategic in nature.

The Real Problem in Marketing

Organizational challenges include overall resistance to change, but also the presence of silos where they do not make much sense. Although much has been written about this topic under the umbrella of digital transformation, it’s incredible how challenging the organizational factor remains. I hope to unpack some of the critical underlying factors in subsequent postings.

The strategic issues, on the other hand, are discussed less often. The problem begins with the marketing technology industry, itself. Driven by billions of dollars in investments, the industry has thousands of solutions in the market, each desperately trying to prove its unique value. I refer to this as the “land of shiny objects.” As marketing leaders attempt to navigate this landscape, it is easy to lose strategic focus.

In this blog, we’ll discuss ways in which marketing organizations regain their strategic bearings and leverage their tech stack for both short-term and long-term gains.