Our fascination with AI-enhanced cars is nothing new. If you’re of the pre-Millennial age, you may remember KITT from Knight Rider, an advanced microprocessor that was built to learn, think and interact with humans. Fast-forward to Minority Report, Total Recall, The Fifth Element ... and, of course, let’s not forget the Batmobile. Elon Musk, founder of Tesla, even cites Star Trek as one of his earliest influences. As fiction starts to blend with reality, Google calls this the “Age of Assistance,” about which co-founder Larry Page once said, "the ultimate version of Google … would understand exactly what you wanted, and give you the right thing.”
Google Assistant anticipates your future car journeys, notifying you in advance if it suspects traffic delays. Piecing together data from where you work and your home address, common travel times and routes, Google can anticipate that your future travel journey may be disrupted.
Connected data, software and technology are making “moments” that are no longer just reactive. Driven by consumer demand, brands are able to anticipate “moments” before they happen, assisting people with utility, informational and directional experiences that enrich their lives.
The dawn of the age of assistance
In 2016, mobile overtook desktop for the first time. The most significant impact of this change was that people’s online consumption grew exponentially. Each new “moment” created gave rise to a deeper understanding of the context behind people’s behaviour. We started to have more data than we knew what to do with.
With smartphones at the center of the experience, people were able to use their devices in greater ways; they began connecting them together, blending multiple pieces of hardware into one connected “ecosystem.” We began speaking to our devices, controlling our homes remotely and ordering products from our cars.
Software rose to this challenge too, piecing together data from across our connected devices to create new experiences, proactively anticipating future “moments” based on knowledge of our past and current (real-time) behaviours, helping marketers better understand their consumers.
Artificial intelligence sits at the heart of the assisted experience. Using data about “you” and “your” world blended with worldly knowledge about “your environment,” it’s able to anticipate your needs.
We’ve seen this type of assisted experience documented in Google’s patent applications, where they envisage people watching a television show being able to ask Google, “Who’s that actor?” and without explicitly notifying the engine of what they are watching it will return an answer.
“Right user, right time and right place” becomes a commodity
Programmatic is synonymous with algorithms and intelligence; often deployed “behind the scenes” making subtle decisions about media buys, driving the mantra of “right user, right time and right place.” The difficulty was, when aspiring to the “right user, right time and right place” mantra, minds ruled over hearts.
It had the idea, just the wrong way around.
Instead of approaching matters starting with tech to data to creative, beginning with the moment and ending with the customer, the better option is starting with the customer, from moment to creative to data to software and concluding with tech.
As a result, programmatic’s mantra is becoming a commodity, where it now offers little competitive edge to a brand’s marketing suite. For example, will adding third-party Experian or Sojern data really create a competitive edge to your media buys, knowing all of your categories are using them, too? Will personalised creative of what a consumer just visited on your website really create a competitive edge, considering they looked at the same product at five similar websites?
Customer-first approach is key to adding value
Rather than setting off with the ambition of creating a single customer view to connect your customer experience, reframe the challenge to, “How do I add value to customers?” Working backwards from the customer first, look to identify where programmatic can assist and add value in this order.
Being customer-centric, you have to understand customers’ “needs” in aggregate, and on an individual basis. Through research, identify common and individual “needs” along the customer funnel, determining the role your brand can play in solving those needs.
Pivoting from each “need,” determine how your brand can assist consumers by solving each individual need and providing a proactive experience.
Knowing the brilliance and constraints of programmatic creative, craft an experience that reflects your ambitions to assist your consumer.
Connect the data you have about aggregate and individual customers, identifying gaps and opportunities to acquire unique data that will let you deliver an assistive experience.
Using a “feedback loop,” data has to work with creative to determine what is and isn’t possible, knowing that some aspects of data are often hard to come by.
Building on data, lean on algorithms or AI to programmatically identify the “right user, right time, right place” using machine learning to spot trends in behavior that add to your assistive creative.
Let the technology house and conduct the relevant parts to make all of this possible.
More of the Same Isn’t the Solution
Evolving programmatic isn’t doing more of the same; adding more data or having more personalised creative. It’s re-imagining the value programmatic can bring. Assistive programmatic is moving from classic ads that people want to block or avoid, to:
It’s about enriching people’s experiences while giving them a reason to care about your brand. It’s determining the moments where you’re able to assist your customers and working backwards to establish the creative, data, software and technology you’ll need to activate it.
It’s programmatic, Jim, but not as we know it.