by Dave Sutton
4. Data May Be as Valuable as the Brand Itself. Customer data and insights into their relationship with a brand may end up being more valuable than the brand itself. Data has become the fuel for contextual marketing engines. Without data, there is no actionable insight. And without insight, marketers are flying blind. So, this raises an interesting question: how can a brand fully own their data if they are outsourcing execution and analysis to an agency or another third-party firm? Moreover, with the recent discov- ery of under-the-table rebates and lack of transparency in media buying practices, serious trust issues are raising questions about the risk and the value of outsourcing.
Artificial Intelligence platforms offer a way for marketers to bring execu- tion, analytics, and data in-house. Agencies will certainly continue to be a great resource for ideation and creative production. However, with AI, there is no reason why a brand couldn’t manage the execution in-house, own the data, glean insights dynamically, optimize offer efficiency, and grow revenues.
5. Marketing and Innovation Produce Results; All the Rest Are Costs.
As Peter Drucker rightly pointed out: “Marketing is the distinguishing,
unique function of the business.” Chief Marketing Officers have tremen- dous revenue growth responsibilities to the business—many CEOs are relying on their CMOs to deliver growth and ROMI (return on marketing investment).
CMOs, in general, have one of the shortest tenures in the C-suite because of the pressure and urgency to generate results. Disruptive new marketing technologies represent a double-edged sword for marketing leaders. On one hand, they offer ways to help marketers cut through the clutter, distin- guish the brand, and win customers.
On the other hand, marketing technologies can just as easily cut into and damage profitable customer relationships with interruptive and irrelevant campaigns. CMOs will seek out innovative AI-based Systems to execute their Strategies to deliver revenue growth and cost reductions—all while mitigating the risk of damaging customer relationships and ultimately tar- nishing the brand.
“Because the purpose of business is to create a customer, the business enter- prise has two–and only two–basic functions: marketing and innovation. Marketing and innovation produce results; all the rest are costs. Marketing is the distinguishing, unique function of the business.”
— Peter Drucker
The common thread behind all the reasons that AI will transform marketing is the pace of change and sheer magnitude of new technology that marketers must deal with on a daily basis.
The fact that many marketers aren’t trained properly to use the technol- ogy intensifies the problem. Artificial Intelligence and Machine Learning are poised to solve many of the complexities that exist within Marketing Systems today—allowing marketers to get back to what they’ve always been good at: Strategy.
Consider the story of the New York Harley Davidson dealership that saw 3000 percent growth in sales leads. That kind of growth is more commonly associated with a startup, not a legacy a brand like Harley. It’s a real outlier—especially when it’s a legacy brand so entrenched in American culture that you could argue it is synonymous with bald eagles and freedom.
So, how did this iconic brand increase their sales leads by almost 3000 per- cent? Predictive analytics, powered by AI and machine learning.
Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.
AI Systems don’t need to waste effort researching and creating customer per- sonas. They possess the processing power to plow through massive rows of data to find real customers in the field. By determining what actual online behaviors have the highest probability of resulting in conversions, the machine can then identify potential buyers online who exhibit these behaviors and begin convers- ing with them automatically.
At Asaf Jacobi’s Harley-Davidson dealership in New York, Jacobi transformed lead generation for the business using the same AI System used by Evisu Jeans: Albert.
With help from Albert, the dealership went from getting one qualified lead per day to 40. In the first month, 15% of those new leads were “lookalikes,”
meaning that the people calling the dealership to set up a visit resembled pre- vious high-value customers and therefore were more likely to make a pur- chase. By the third month, the dealership’s leads had increased 2930%, 50% of them lookalikes, leaving Jacobi scrambling to set up a new call center with six new employees to handle all the new business.
At Jacobi’s dealership today, Albert performs many of the time-consuming, manual tasks which human marketers are unable to perform at the speed and scale required for efficient and effective customer interactions. The AI tool enhances overall marketing productivity by complementing the role of human marketers.
Man versus Machine?
Quite frankly, some people have a healthy fear of Artificial Intelligence (AI) and the potential for unintended consequences of a future where machines have taken control of the world and reign over humans (think about the plot of The Matrix or The Terminator).
Although experts predict that one-third of our jobs will be replaced by robots by 2025, this isn’t a reason to worry — it just means it’s time to adapt. The true losers of the AI and Machine Learning economic shift will be the laggards and late-adopters during this transition.
The transformative nature of Artificial Intelligence (AI) technologies and Machine Learning will be far reaching. Machine Learning will drive an entirely new wave of software applications and platforms that can revolutionize human- computer interaction, and much like the Internet, social media, and mobility waves, it will redefine entire consumer and enterprise markets.
Machine learning is a specific method of data analysis that automates analyti- cal model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly pro- grammed where to look. Machine learning is the area of AI that will have the biggest impact on the discipline of Marketing in the next 5-10 years.
As we have seen with other disruptive technologies in different sectors of our economy, machines are better suited to perform certain types of tasks than humans. Likewise, humans are better suited to perform certain tasks than
machines. And perhaps most interesting, there are process areas where humans and machines can complement each other to optimize productivity.
From marketing operations to marketing execution to customer engagement and marketing analytics, AI will transform the way that marketers work. AI will not only enhance overall marketing productivity by complementing the role of human marketers but also replace the role of humans in many parts of the marketing organization. In the chart below, we’ve characterized the type of tasks where machines outperform humans and vice-versa.
A Framework for Predicting the Winners and Losers
Today’s marketers need to prepare for the revolution of AI and machine learning, and clearly articulate how they will utilize artificial intelligence to enhance cus- tomer experiences, increase ROI, and boost operations efficiency. We’ve devel- oped a framework to help marketers begin to understand how AI, and more spe- cifically, machine learning will disrupt the traditional “marketing value chain.”
Like most processes across the various functions of a business, not all market- ing processes are the same. Even within the marketing department, processes can be very different in terms of their basic characteristics. Marketing processes can be characterized by three dimensions:
Level of Complexity. Complexity is the degree of difficulty that marketers experi- ence in collaboration, coordination, and decision-making to get their work done. An example of a low complexity process might be sending out an email. High complexity processes might include things like customer data mining, predictive modeling, strategic planning and creative design.
Level of Predictab
ility. Predictability is the degree of difficulty for a marketer to determine in advance the way a process will be executed. Low predictabil- ity process examples might include managing customer interactions on social media channels. High predictability processes might include handling marketing budget requests.
Level of Repetitiveness. Repetitiveness is the frequency that a marketer executes the process. A process executed only once a year has a lower degree of repetitive- ness than a process executed every day. Examples of a low repetitiveness process might be developing a brand architecture for a new product. A high repetitive- ness process might be managing an online chat with prospective customers.
Broadly speaking, marketing processes with high complexity, high predict- ability, and high repetitiveness are logical targets to be managed by machines. Most Marketing Execution and Marketing Analytics processes fit this character- ization and we expect that AI will likely replace most human activities in these areas over the next several years.
By contrast, marketing processes with low predictability are not seen as good targets to be managed by machines. It is challenging for a machine to design and
adopt new procedures “on the fly.” Low predictability processes require the mar- keter to exercise judgment and apply originality to define alternative solutions and/or redefine processes, thus being an area in which humans excel.
As AI continues to pervade our everyday lives, the next generation of market- ers will be “AI natives,” much like the prior generations of “mobile and digital natives.”. They will have a redefined relationship with technology, which will fur- ther remove elements of friction in daily activities, making room for increased productivity and creativity.
“Prediction has always been critical to marketing planning and responsive- ness, but this was done by marketers to anticipate what consumers would buy. In the future, consumers will be using predictive tools that will decide what to buy for them.”
— J Walker Smith, Chief Knowledge Officer, Brand and Marketing, Kantar Consulting
Are the marketing and advertising industries ready to scale AI? Not quite. But there are signs of disruption. Agencies are building services on top of AI technologies, and there are already some mature AI-based marketing technolo- gies established that go well beyond audience targeting. These early adopters are gaining an advantage through the proper use of the new tools.
There’s little doubt that AI will transform marketing as we know it. As new technology emerges, it’s more important than ever for marketers to get the basics right.
According to a research report by OneSpot and Marketing Insider Group, nearly half of consumers won’t spend time with branded content if it’s not rel- evant to their interests. 88% of consumers say that personally relevant content improves how they feel about a brand. In other words, personalized content has become more of a necessity rather than just a nice touch.
When marketers are untethered from the mundane matters of the day-to-day and allowed to focus their mind on more strategic endeavors, the results can be astounding. As we witnessed in the Evisu, Nike and Harley-Davidson stories, this is the true power and benefit of unleashing the ghost in the machine.
Conclusion
o you remember the scene in the 2002 movie Minority Report when Tom Cruise walks into a shopping mall and he is bombarded with “personalized” holographic images for a variety of products? Brand stories and offers popping up all over the place interrupting him and attempting (unsuccessfully) to get his attention. Is this where technological innovation will lead us in marketing? If so, we’re looking forward to an inefficient and pretty creepy future! A flood of annoy- ing imagery, irrelevant and conflicting messaging, sensory overload, ad nauseam. Of course, this type of real-time, personalized marketing is with us already,
in a much more efficient and slightly less creepy manner. For example, consider web retargeting. You visit a website and a cookie is left on your computer. That cookie triggers targeted display advertising on other web sites as you continue to browse online.
In this way, a brand can attempt to win back your attention, remind you to go back to their web site, and perhaps even convince you to make a purchase. This is still an interruptive tactic, but if the brand story is simple, authentic and relevant,
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a retargeting strategy can be an efficient way to nurture your target customer and give them a reason to engage with you.
That said, retargeting still doesn’t address the underlying problem with digital advertising: very few people click on traditional banners. Most people have been conditioned to tune out noise as we browse the web. This phenomenon is some- times referred to as “banner blindness.” People almost never look at anything that looks like an advertisement, whether or not it’s actually an ad. Website visitors just intuitively avoid display ads when browsing their favorite web site destinations.
A study conducted by Google’s Doubleclick team in March 2017 found that across all ad formats and placements, the click through rate (CTR) is just 0.05%. That equates to just 5 clicks per 10,000 impressions! This fact alone should give transformative marketers pause as they consider the potential futility of driving direct response from online display or banner ads.
So, what does the future hold for marketing? How will marketing shift from interruptive technical tricks to truly transformational innovations?
Since the early 1990’s, Marketing Technology (MarTech) and Advertising Technology (AdTech) have rapidly evolved and dramatically changed how we connect, communicate, and collaborate, both as individuals and as businesses. We’ve witnessed the convergent waves of consumer electronics, mobility, social media, cloud computing, and big data reshape how companies go to market and connect with customers in relevant, productive and profitable ways.
Equipped with information and linked through social media, custom- ers will only continue to gain power and learn how to exercise it. As we look ahead to the year 2020, companies will need innovations to balance this shift in market power, keep up with customer demands and prepare to respond to these trends:
• “Mass Marketing” will take on an entirely new meaning as the masses will control much of the dialog (and all of the authentic advocacy) about brands and their reputations.
• Connected Customers will demand full control over the timing and process of communications and consumption, so businesses will be expected to meet customer needs as soon as they materialize via what- ever channel the customer has chosen.
• Marketing campaigns, once thought of as one-way communication
paths from brand to customer, will truly become two-way streets. Continuous engagement will be the norm and episodic campaigns will be in the rear-view mirror for most companies.
• Company marketing processes and the insights and intelligence embedded within them will coalesce. Not just because they overlap so much, but because the customer experiences them as parts of the same interaction.
• Static rules-based processes will just not be able to keep up with the pace of market change. Faster, smarter and more predictive marketing processes and decision-making will be required.
The future of marketing is now. And it’s going to be much better than what was portrayed in Minority Report
Based on our research at TopRight, we are expecting that Marketing Automation innovation will be shaped and governed by three significant shifts:
From Brand to Reputation Management
While you may think you or someone at your organization manages your brand today, it is really the external perception of the target audience that defines your brand. Making matters worse, social media channels give your target audience (and many others) an easy way to share opinions about your brand with thou- sands of others in an instant. This powerful and ubiquitous communication chan- nel has the potential to put your brand in constant peril and make your firm’s reputation vulnerable to rumors and viral misinformation.
This raises an interesting question for marketer
s in 2020: how will you manage a brand in a world where so many of the success variables are no longer in the company’s control? The short answer is: you can’t do it using traditional brand management techniques—you’ve got to reframe the problem.
Marketing Automation tools will continue to empower brand owners to actively monitor social media channels like Facebook, Twitter and YouTube, as well as track blogs, forums and online communities where conversations about the brand may occur. Whether the conversation is positive, negative, humorous, or just sarcastic, you must track the sources of such content and gauge the senti- ment and underlying emotions in order to protect and enhance reputation.
The key to making the transition from brand to reputation management lies on the examination of the company through a set of “filters” designed to gauge how you are shifting from a reliance on the traditional art of persuasion to the adoption of the disciplines of authenticity, as represented in the image below.
Systems must be deployed to monitor, segment and target the peer-to-peer conversations that represent the highest opportunity and/or risk to brand reputa- tion. When engaging a target audience member, marketing must be transpar- ent with regard to their affiliation with the brand and authentic in their delivery and tone. Disingenuous party-crashers are quickly exposed and ejected from the dialog with serious brand reputation consequences.
