In just the next two years, according to Business Insider Intelligence, 34 billion devices will be connected to the Internet and only 10 billion of those will be the smartphones, tablets, and smartwatches that dominate the market today. By 2021, BI says that almost $6 trillion will be spent on Internet of Things (IoT) solutions like connected devices in the home.
All this means that marketers will have new channels through which to compete, because customers don’t invest in a connected thermostat or coffee maker so it can work just like the old offline version. They want something more. The need to create a unique experience will transform marketer’s lives. In this new world, the customer journey doesn’t end with a purchase, but instead the purchase becomes part of an ongoing relationship between the customer and the brand.
The best IoT devices interact in two directions and the most transformative among them will take advantage of both inbound and outbound channels. As a result, users are quickly growing to expect these devices to be contextual all the time. This means marketers need to react to data feeds that are larger, and do so faster than they ever have before.
Take the example of a company that sells coffee pods. With a traditional model, customers buy a subscription to deliver coffee on a regular basis. This model ignores consumption, and instead assumes that a customer needs coffee at regular time intervals. The result is either a backlog of coffee, or running out before the next subscription arrives. Either way, customers often grow frustrated and cancel the subscription.
A connected brewer that understands what beverages are being consumed and when they are being consumed can deliver the right pods when they’re needed. With an added layer of machine learning, the brewer can start to understand additional factors, such as day of the week, time of year, or any number of other data points. So, for example, the company could deliver hot chocolate when the weather predicts snow, or tea during a particularly dreary stretch. Now the full customer experience is not just about having coffee, but having the pods they like when they’re needed.
Importantly, these decisions shouldn’t be left to the device and the intelligence behind them. They need to start as suggestions – “A new auto delivery will ship in the next 2 days – would you like to delay this until next week?” The intelligence is in knowing the question to ask, and confirming easily with the customer right then, right there. Frictionless relationships win the revenue and the loyalty in interactive IoT.
To deliver on this kind of functionality, and help establish a high level of customer reliance, the devices must provide a truly transformative experience. That means having the right data and information at the right time. Ultimately, those companies offering the best quality experience through their IoT devices will emerge as winners.
This is no small task. When you add up the information coming from devices, and combine that with the existing information flowing from all digital channels, you end up awash in data in multiple volumes, of multiple varieties, at multiple velocities. Add to this the need to react to these devices and you have a situation in which marketers must feed the cycle of data, insight, and action to meet customer expectations of instant gratification.
Often this means bringing in outside information. Data points like real-time weather, which affects consumption of goods and services, are becoming key to the data mix. The same is true for data from other lines of business, like bringing in inventory demand data and shopping point data. Because if you’re trying to deliver product offers in real time, the promise you made to the consumer can only be kept if you let them know that you can deliver the product in a couple of days.
To make all this work you need two key components: A customer data platform that puts all the right data in the same place and a layer of orchestration, which is where the real-time decisioning occurs.
The customer data platform is about having all the data in one place, and then extracting the right data at the right time, and at the right level. This allows it to be consumed by other processes, messaging systems, and orchestration systems, and optimize that messaging over time based on business unit knowledge. You also need to combine this core data with data from other sources as well.
This means creating more than just a marketing database. You must ingest this data, run data quality on it, and then persistently identify sessions, cookies, devices, people, and accounts, then link them together so the data can be used effectively.
On top of this, you need an orchestration layer that includes analytics, business intelligence related to marketing operations, and other levels of planning. Then, the journeys and interactions can be coordinated across all these different channels, whether they’re IoT, digital, or even direct mail. The information about a person and their device behavior changes so rapidly, it’s no wonder that machine learning is playing an ever-growing role in marketing offer decisions.
In truth, the adjustment for marketers will be more about complexity. This is about delivering the right message through the right channel – or multiple channels – using the right media at the right time. And only then can you deliver the experience customers demand while also helping increase the bottom line.