Marketing data paints a picture. The more data you have, the better the picture. So it should logically follow that the Internet of Things, with its mountains of new, behavior-rich data, has the potential to turn merely competent marketers into digital savants using innovative marketing technology to power insights that seem downright futuristic.
That scenario does play out, at least in theory. To apply it to the real world, though, there are some obstacles to overcome. Data requires interpretation to be of any value to marketers, and the influx of information from new IoT sources is like receiving news dispatches in a foreign language. You need to have an interpreter—analytics technology that can understand the context of this data, and its relationship to other incoming information.
Traditional methods of marketing attribution—and even more recent innovations born out of new digital marketing channels—provide relatively good insights considering the data available to marketers through those channels. But the Internet of Things blows the lid off of available data: Not just the immense volume, but the types of data, and the innumerable new implications created by a single new stream of information. IoT data is so rich and diverse that it makes even recent improvements to digital marketing attribution seem, by comparison, basic and punchless.
Think of it this way: Executing marketing attribution in the past was like trying to draw a picture with only the eight basic Crayon colors. You can get the point across, but nobody will call it art. Adding IoT data to the mix is like upgrading to that coveted 64-Crayon box set. You don’t just have blue at your disposal, you’ve also got navy blue, cerulean, even aquamarine to choose from. It’s an incredible asset—if you use it the right way.
Data doesn’t just come from computers and smartphones anymore. It comes from everything. When you use Netflix, wear your FitBit, set your home’s Nest thermometer, log on to social media, make a credit card payment, or even walk into a retail store, you’re providing data to a device designed to collect information.
Globally, there are already billions of mobile touchpoints at play. And billions more are on the way, as IoT is leveraged for kitchen appliances, in-home digital assistants, garage door openers, door locks, and so on. This information is generated in several different ways. Consumers may take direct actions with an IoT device that triggers data transmission, or their activity may be monitored, recorded and then passed on down the line.
Given the proliferation of IoT devices, especially in the developed world, there are often instances where multiple devices are tracking the same information, albeit from different perspectives and for different purposes. As you try on blouses in a smart dressing room of a retail store, the smart mirror may be tracking the items you’ve tried on, while the store’s beacons are tracking your footfall activity and time spent in the store. Your health wearable may be tracking your heart rate, and your phone may be utilizing your location data even if you aren’t actively using the device.
Not all of these separate data streams come together at any common destination, but the example still illustrates just how easily multiple IoT data streams can be leveraged to understand the context and behavior of any given moment. The challenge for marketing attribution is significant: Effective attribution must understand how to put this information together, how one data stream relates to one another, and what the resulting insights mean, if anything. That’s a more significant undertaking than standard marketing attribution practices, which boil down consumer behaviors to broad-brush data points like path-to-purchase and search keywords.
Marketers won’t be doing these calculations by hand, mind you. Instead, they’ll need to lean on analytics solutions capable of interpreting data from IoT sources, which could mean learning how to use new analytics tools and the features they offer. There’s a clear path to installing solutions that help organize and understand the new IoT data flooding into your organization, which will help your human capital tackle other upcoming challenges.
It’s important for marketers to keep in mind that the Internet of Things doesn’t create new variables that affect purchasing and conversions. In most cases, it merely illuminates variables that have gone overlooked, and have perhaps been hidden to marketers.
As Forbes points out, Walmart used such sophisticated insights to conclude that berry sales are higher on days with warm temperatures and low wind, while hamburgers are a more popular purchase on hot, dry days. Through this next-level understanding, the company can create marketing campaigns and messaging specifically addressing these factors. It can even adjust prices for products according to the anticipated demand for such items.
There’s no end to how this data can be used to ask questions that you’ve never thought of asking. Your retail store may use product sales to assess the effectiveness of playing an item on an in-store mannequin. It’s a decent measure of success, but only part of the picture has been painted. Through IoT, you can analyze the amount of attention those mannequins receive from shoppers independent of how they drive sales. Are shoppers stopping and looking at the mannequin? Are the displays getting customers to look more closely at products? Based on the number of consumers that try on the displayed item, what percentage purchase it, and does a low number suggest that the item is poorly tailored?
Your organization may never have asked these types of questions before. It makes sense why they would go unaddressed, since asking questions that can’t be answered is pointless. But now, IoT creates opportunities that require marketers and brand leadership to rewire their brains and ask all the little questions they’ve never considered.
When the right marketing technology and data acquisition channels are used, marketing attribution isn’t another hurdle to overcome—rather, it’s a gateway to much better brand experiences. Even if you resist such an evolution for your own operations, consumers will eventually come to demand it.
Those demands come in the form of continued personalization. If you run a retail store, your company needs to leverage IoT data to build personalization into the brick-and-mortar experience. Digital and in-store content should be consistent in its messaging to individuals, and consumers should feel that the company understands their specific interests.
If you run an online business, predictive analytics should be used to anticipate consumer behavior and interests, and to make prescient recommendations of products and other experiences. As Global Big Data Conference suggests, data can help determine where and how these predictive actions should be used for maximum effect.
Ultimately, more engaging experiences, including those leveraging innovative content like augmented reality and virtual reality, can be instrumental in building a deeper relationship with consumers. It sounds cutting-edge right now, but the proliferation of IoT will turn such innovations into standard practice for brands.
The Internet of Things is bringing massive disruption to marketing attribution, among so many other technological changes. But like so many other forms of tech disruption, it’s change that will ultimately improve how brands connect with their audiences.