Artificial Intelligence is ready for you. You are not ready for AI. I understand the thought alone may turn many of you away. The story wouldn’t start here if it wasn’t true for many marketing teams. I’ve been an observer, operator, and educator in digital marketing for close to a decade. Saying a lot has changed may be an understatement. AI is that next BIG change. But unlike other MarTech or AdTech, AI is not just another new technology. AI is not chat bots or your Tableau dashboard. It’s an integrated ecosystem of data, operations, technology, and management. That’s bad news for you right now… But it doesn’t have to be…
Digital Marketing House of Cards
Digital has made your job harder. The rise of the “born-on-digital” consumer changed the game. Their access to free and available information is greater than ever. In turn, their content consumption behaviors are changing. There are more communities and content providers than ever before, more devices which to access it all. Digital consumers now begin to favor chat bots and ecommerce over talking to you, or your sales team. David Ogilvy’s Direct Marketing looks like a stone axe. In response, there’s been a proliferation of new marketing roles, technologies, and channels to reach this new consumer.
Technology providers make their money solving a problem. They don’t solve the problem of the growing distance between you and your consumer. More choices adds complexity. Now you need a “stack” of solutions to solve the problem. Which means you need more expertise, more time to evaluate, and more opportunity to get it wrong.
All this change is forcing new roles and structures into marketing teams. Re-orgs happen so fast and frequently that many marketing teams are fractured, silo’ed, and left without a unifying strategy. The average tenure of a CMO keeps dropping and is now half that of the CEO — meaning every CEO fires at least one. All of this makes systemic change slow, or maybe impossible.
While you move slowly, the digital consumers evolve quickly. You’re over indexing on marketing technology and undervaluing data. Data and knowledge is growing within your organization. But actual insight? Maybe not. Often, marketing teams don’t “own” data. Vanity metrics become your answer to a problem not well understood. Marketing has fallen out of sync with the consumer. And the machine bloated. Change is slow. Insert artificial intelligence as the new shiny object.
AI is not a technology, but a data process that unlocks opportunities to augment marketing capabilities. Those opportunities are to understand, predict, engage, and automate for the digital consumer. AI requires access to good data, the right technology, the right people, and a process to unlock the disruption level stuff. For you, that’s hard.
A New Strategy: Data and Augmentation is the Differentiator
Better information and better insights are the new differentiators. How you collect, share, store, transmit and “use” insight becomes the difference between building relationships or becoming white noise. The fact is we all are in a knowledge-based economy. Competitive advantage is data rather than the traditional view of products, routines, capabilities and assets.
So how do you know you know?
Marketing needs a reboot. In 2018, focus less on MarTech, more on MarOps (marketing operations) where the two work in concert via a data-driven strategy. Traditional silos within marketing need to converge and mobilize around data. You need to create, own, and understand customer data. Look to gain access to other data sources such as sales, call center, analyst, and financial data. Also consider joining this data with data from outside your company. Being able to mine, refine, combine, and act on data requires a new operating model. Meaning, new processes, roles, and technologies. Build relationships with your CIO. They get it.
You will see roles like “technologist”, “operations professional”, and “data scientist” join marketing teams. Brand, demand, and digital marketers will coalesce on one team to craft and tell the story. Data scientists will mine and refine data sources for comprehensive, contextual understanding of the digital consumer. Technologist will own the MarTech, manage the AI algorithms, and help transform the story into deeper engagements. Operations will integrate and automate the end-to-end “data-to-delivery” process. Much of this is augmented through AI.
AI is Ready for You
You are, in fact, no stranger to machine learning. Even basic uses of segmentation and programmatic advertising is AI. New algorithms, processing power, and data is taking AI to another level. For example, psychographic targeting is not new. However, the psychographic targeting at the center of the Cambridge Analytica scandal took it to a new level. It’s a great example on the power of massive, comprehensive data sets powered by predictive algorithms have the capability to influence people.
With AI, we can now understand our customers like never before, processing massive amounts of contextual data to sense and predict behaviors.
When used the right way, that same combo can better predict our best customers, even before they are in the market. It can help us deliver more helpful, personalized content. Machine vision and natural language processing is inventing new ways to engage customers. As the digital consumer shifts to favoring self-service, you can now provide ambient interfaces to engage and delight them. There are many use cases of digitally savvy marketing organizations implementing AI and seeing results.
Example use cases for marketing — Media Industry example (McKinsey, 2017):
General opportunity in AI (McKinsey, 2017):
Those who reach AI maturity first will have a tremendous tactical advantage versus the competition.
How to be Ready
AI needs to be a CMO conversation. It starts with the right strategy. Not every organization starts in the same place. Start with clearly defined goals. Then have a data strategy centered around those goals. Start small and get an AI win under your belt. Identify narrow uses-cases ripe for available AI and acquire the data to activate the technology. Start planning for an AI Center of Excellence to operationalizes around data, technology, and expertise. The right team is critical. Build a diverse team, as creative, technical and operations skill sets are most effective in this new world of AI.
Example of integrated team (Source: MIT):
Finally, don’t do this alone. We’re here to help.