The Internet Of Things Is Disrupting Marketing Attribution, And Marketing ROI Will Never Be The Same Again
In 2012, ultra-hip Guatemalan shoe retailer Meat Pack ran an unusual promotion via its mobile app. When customers who had downloaded the app walked into competitors’ stores, they were given an alert: they now had a 99% discount on their next in-store Meat Pack purchase. However, the discount would drop 1% every second, until the customer entered a Meat Pack store. With the clock ticking on the offer, customers literally ran from competitions’ stores — over to Meat Pack.
The campaign was clearly ahead of its time. Even today, few marketers use mobile so effectively. But the campaign is instructive, as it shows what’s possible when you know who a person is, where they are, and how they behave — and can interact with them accordingly. Put a little more technically: by capturing real-world, real-time analytics — and by making the analytics actionable — marketers have been able to achieve astoundingly disruptive engagement.
That’s just with mobile. With the emergence of a full-scale Internet of the Things (IoT), those capabilities will grow exponentially. What kinds of opportunities does that open up for analytics-driven marketers? And what should those marketers do today to reap the benefits of the IoT revolution? I could spend a lot more space than this article exploring these questions. For brevity, I’ll use focus on the six points below.
Disruptive Data Collection
On the most basic level, the IoT means more touch points through which to acquire data. We tend to think of these “additional points” as simply more objects that can track consumers in the same old ways: mobile phones could gather motion and position information; now, chip-enabled sneakers and smart shirts can, too. But the new opportunities of data collection aren’t just about more data points. They offer the promise of gathering more types of information, as well — like eye tracking through smart lenses, vending machines that use facial and other analyses to determine a customer details — or even forks that monitor how much we eat. As smart products proliferate and record data about everything consumers do, they’re learning about more kinds of things consumers do, as well. The marketing opportunities are astronomical (as are, of course, the responsibilities around privacy that come hand-in-hand).
One clear benefit of knowing consumers so well is the level of personalization that’s possible. If you can tell the difference between one snack machine user and the next, you can offer a different snack to each person — or even suggest a new snack to a target demo. Another example: if out of home networks can identify what kinds of cars are passing a pump, they can tailor gas station advertising for motorcycles, luxury cars, SUVs, and the like. And as self-driving cars become a commercial reality, the cars themselves could become a new kind of data-driven ad network, using location and individual-level insights to direct passengers to relevant stores en route (a capability which, to be sure, would require addressing any transparency issues involved).
As the example of the retailer Meat Pack shows, the kind of information that IoT provides can dramatically change the ways businesses engage consumers in stores, too.
That kind of insight is already being put to use today. Major venues are already using sensor tracking to understand the flow of foot traffic and purchase activity, and to optimize everything from store layouts to shop inventory to bathroom locations. Meanwhile, there’s enormous potential in optimizing experiences rapidly based on real-time insight. For instance, the events marketing team at SAP uses scan and sensor data (among many other sources) to know where event-goers are congregating within SAP’s events, and to optimize event content on the fly.
Identity-Based Attribution and Marketing Optimization
Another group of insights that IoT data provides is not about the ads themselves, but about the broader environment in which ads are delivered. Those environments influence ad performance in subtle but important ways.
Today’s sophisticated marketers already consider environmental factors like competition actions, pricing changes, breaking news, weather, pump prices and more to accurately evaluate marketing’s effectiveness. Walmart, for instance, has determined that berries sell best on days with low winds and warm temperatures, while hamburgers sell best on dry, hot days. The retailer can tailor marketing and messaging accordingly.
In recent years, marketing analytics has provided extraordinary breakthroughs into understanding the uncontrollable variables and their impacts on marketing effectiveness. But IoT promises to deliver unprecedented insight into these, because IoT can provide insights not just about broad conditions and trends but about the specific place an offering is served to a consumer, and the specific individual to whom it’s served.
As a result, IoT will provide answers to many questions that, until now, have been both highly critical and completely elusive. Is a billboard more effective in fast or slow traffic? Are consumers more responsive to sports advertising before or after a workout? Do coffee ads perform better with coffee drinkers who are tired, or who’ve had a good’s night’s rest? Marrying attribution analytics to information from location-based traffic updates, fitness trackers, and sleep trackers are providing answers in a state-of-the-art way.
Toward a Complete Conversion Path
Currently, the methods marketers use to follow a customer’s paths to purchase is split in two. On the one end, digital channels provide a detailed, yet still partial, window into consumer behavior. At the other extreme, offline channels — like traditional TV — provide no direct insight into how consumers interact with them.
For much of recent advertising history, there has been remarkably little middle ground. As a result, marketers often misestimate the impact of marketing efforts; old-school ‘media mix’ models and ‘digital attribution’ are telling marketers the wrong answers on a daily basis by being overly simplistic and short-term in their measurement. It’s a recipe for disaster as analytics shift from “nice to have” to “need to have.”
As we continue to shift to digital engagement via mobile devices, IoT and computers, consumers’ digital footprints vastly expand — and marketers can see how customers react to all marketing engagements. In some cases, that becomes possible when previously unconnected touch points join the grid. In other cases, that’s possible through proxy information via smart devices: even if a billboard investment, or a sponsorship activity, for instance, can’t tell you how many pedestrians stopped to look at an ad, mobile location data can.
In this world of Connection Science, marketers can now follow the complete conversion path across truly every touch point — and optimize marketing based on an entirely new view into how marketing actually influences sales. Not just short-term effects, but also brand equity effects (never picked up by the old-school legacy analytics methods that just look backwards).
The next stage in that evolution is an upheaval in the ways marketers can buy advertising. With IoT, marketers can leverage this real-time data for real-time advertising placement. This can only be powered technologically, not manually like most ads are still planned and purchased.
Agility and precision are the new weapons for marketers thanks to Connection Science. Those not adapting to this new reality will have their lunch eaten by more agile competitors. Actually, it is happening right now.
The Internet of Point Solutions
Of course, currently we’re still in the infancy of IoT-enabled marketing. Part of the reason is that we’ve only just begun to see the kinds of objects that can become web-integrated, and the kinds of information they can ingest and report back. Just as challenging, though, is the fact that IoT is still at the point solution phase — which makes it difficult for real-world objects to slip easily into unified marketing campaigns.
That point solution problem is actually twofold. The first piece is a technology problem: because of a lack of universal APIs, systems that could integrate, don’t. For instance, while nearly every major in-store point of sale system is radio enabled (it can connect to the Internet), these systems don’t easily connect to cloud-based CRM and marketing automation.
The second issue at play is one of standards. Different applications record the same data by different parameters — even down to using different field names to describe who a customer is. Web-enabled objects, meanwhile, often each have their own unique privacy policies. It’s hard to create coordinated experiences — much less real-time coordinated experiences — if sharing data across all the points requires a separate opt-in form at every point along the way.
To be sure, much of the solution to the problem lies outside of marketers’ hands: they’ll just need to wait for the technology to catch up with the vision. But there’s much marketers can do to steer today’s IoT along the right path. For one, marketers need to push for data and privacy standardization across every connected device within their company, and to push partners for more IoT-friendly open APIs.
That’s a heavy task. As with so much of the marketing role, it calls for CMOs to become the data and analytics champions across a wide swath of the organization. But it’s also worth the effort. After all, in the next wave of Connection Science, you want your analytics to send customers rushing out of competitors’ stores — and toward yours.