How Beacons Might Alter The Data Balance Between Manufacturers And Retailers
As Salesforce integrates DMP Krux, Chris O’Hara considers how proximity-based personalization will complement access to first-party data. For one thing, imagine how coffeemakers could form the basis of the greatest OOH ad network.
“In 2017, marketers will integrate [Data Management Platforms] across their entire martech stack, providing better customer intelligence to drive decisioning from top to bottom in their marketing portfolio,” wrote Melissa Parrish, Sarah Sikowitz, and Susan Bidel of Forrester in a recent report. “Forward-leaning companies will connect this marketing brain to their enterprise CRM systems to drive better customer experiences.”
A month after Salesforce closed on its $700 million acquisition of DMP Krux, the company held a press briefing to explore some of the ways the two will fit together.
For one thing, Salesforce is promising “new improved cross-channel ad delivery management, the ability to power digital ads using any data in Salesforce and AI-powered Einstein Journey Insights dashboards enable marketers to segment and activate audiences like never before to deliver the right message at the right time on any channel.”
One key component in that is the role of Internet of Things devices like beacons. During his presentation, Chris O’Hara, Krux’s global head of data strategy, noted the potential of beacons as a first party data source. As the two companies complete their integration, we asked him about the ways beacons are likely to evolve as a CRM tool over the next year.
GeoMarketing: How do you see the value of beacons for brand marketers?
Chris O’Hara: Brands like consumer packaged goods marketers tend not to have access to first party location data. What they’re trying to get to is sales attribution, specifically closed-loop attribution.
How might a beacon assist that in a brand or store’s marketing program?
Take, for example, a maker of a meltable cheese. To understand retail activity, they might geofence a Walmart, Target, a 7-11, and local supermarket to see where a consumer is shopping. In a typical scenario, once a customer gets in close a beaconed location, the marketer can send them an SMS message, “Here’s 20 percent off the block of cheese.” Then, once they’re in the store, because the beacon picks up user location within feet, the brand knows that the shopper is near the endcap, where there is a large cheese display.
Then you go and you buy the cheese. You go up to the counter, submit your mobile coupon. I authenticate you as a user. Then I see from the consumer’s relationship with the POS system in the store, they bought the cheese, chips, salsa—because the brand is targeting people making nachos for the Sunday game. Also, they bought a six-pack of beer, which gives an interesting view of cross-brand purchase portfolio data.
Then, because I have that purchase data, and because I’m using a Data Management Platform, I can look back on all the media exposure that occurred and say, “Not only did I capture an offline interaction with an endcap in a store, but he’s seen the SMS, he’s seen the mobile ad, and the video ad. He’s seen three display ads. He’s also interacted with my website. Now, I can start to do fractional attribution against those touch points and I make an informed guess that includes actually includes an offline activity. Now I’m getting closer to real closed loop attribution.”
We’re looking at direct data. It’s not panel-based. It’s not survey-based. It’s based on the fact that technology interacted with a real human. Of course, for all that to come together, that requires a phone with location services on. It requires the SMS to work, and the person to look at it. So, there are obviously barriers to doing this at scale in today’s world.
How do you expect that kind of use to evolve, especially as Krux and Salesforce become fully integrated?
We’ve been looking ahead at a lot of possibilities. Take a company that makes single-use coffee machines. That brand’s interaction with their end user today from a data standpoint is zero. Someone buys the machine. They go to buy the cups, or pods, they brew them at home or the office and the manufacturing brand never knows what happens after that.
What if I could put a beacon in that machine, so we could can tie that beacon to every single use?
It could be the home, office, it could be user’s a hotel room. Once I connect that beacon–that IP-enabled device–I’ll be able to see everyone with a connected device around me. I know what the mom’s brewing, the dad’s brewing and the daughter in the household. I know it’s Starbucks in the morning. Dunkin’ Donuts in the afternoon, and Twinings Tea at night. Now, I know by individual what brands they’re drinking, what their habits are. Maybe, I have the analytics onboard the machine. If you’re 200-cup a month customer and your machine is operating in a faulty manner, or the water’s not hot enough, maybe I’ll send you a new machine because I don’t make money on the machine, I make money on the cups.
You’d be able to personalize the marketing of coffee cups and pods on a deeper level.
Right. You can imagine the possibilities. If you’re just a 20-cup a month customer, I’ll send you a coupon for 20 percent off. There’s also obvious use case of, “I know you bought 40 cups from my online set. I know you’ve drank 30, time to send you that offer for the next 40 pods before you run out.”
What if I had 400 million devices in circulation in the US? Then also, imagine that I put a 3.5-inch LCD screen on top of the machine. It can feed you a video about how to make a perfect latte, or even an ad. All of a sudden, my coffee maker that’s in people’s homes, offices, hotels, gives me the largest out-of-home advertising network in the world. If you think about that, that’s a very aspirational use for this.
How do you think that capability would change the marketing dynamic between manufacturers, retailers, and CPG brands in between?
Right now, the manufacturers are at arms-length from their customers, because the retailer has all the purchase data. But, now if I had this data and I had it at scale, I could actually go to the people who make the cups. Brands like Dunkin Donuts, Folgers, and Starbucks, would all know more about their customers and their drinking habits than they’ve ever had access to before.
There’s also all kinds of interesting things about geo-location in general and consumer preference, and choice. I’m completely fascinated by it, particularly as we think about all the changes coming in 2017.