Over the past year, we’ve shared practical tips to improve your advanced TV buys, answered your top questions about programmatic video, and shared industry resources to help you stay ahead with connected TV. But the questions we get the most from clients center around how they can prove their connected TV campaign had an impact beyond brand awareness, especially when it comes to driving actual foot traffic into their stores. As the best of both worlds, connected TV delivers the impact and experience of traditional television with the measurement capabilities of digital video. Still, one of the biggest challenges for marketers is how to measure success, particularly for advertisers who don’t have an ecommerce presence to track sales. How can they be sure their connected TV ads made an impact? We recently worked with a national furniture retailer that posed this same question. Their previous connected TV campaigns yielded positive brand awareness results, but they wanted to prove their connected TV ads could drive meaningful business results (like increased store traffic), while remaining cost-effective (meaning a low cost per store visit). Because this particular connected TV campaign was so successful – more than doubling in-store visits and lowering cost per store visit by 68% – I want to share the three steps we took to set up a foot traffic-focused campaign and some practical advice you can implement on your next connected TV campaign. Step 1: Build Your Foundation With Only Quality Inventory The foundation of any successful connected TV campaign (or really any digital campaign) is quality inventory. As the digital ad industry grows, more money is being funneled through it making it even more attractive for fraudsters. To protect your brand and your budget, you need to source the cleanest, safest highly viewable inventory. That’s the only way you’ll be sure that real people saw your ad. Just like other types of digital media, not all connected TV inventory is created equal. But typically the more premium the content, the higher the completion rates and the lower the risk of fraud. So, for advertisers looking to deliver high-impact connected TV experiences that outperform standard benchmarks, we recommend premium private marketplace (PMP) deals and full-episode player (FEP) ads. PMP deals are fairly straightforward – they connect advertisers with preferred top-tier publishers, like ESPN, History Channel, and HGTV, that play on connected TV devices. So, if someone is watching the Food Network on their Roku, we can serve commercials across several Food Network shows just like they would see on regular TV. FEP placements can be more difficult to uncover but are crucial to success. This is where a person streams 30- to 60-minute videos via a network’s app or website online, often with multiple ad breaks. For example, an FEP would include someone watching This is Us on the NBC app or on Hulu. Ads within FEPs are premier placements because they’re paired with long-form content, like a TV episode where viewers are likely to binge-watch. So advertisers can use FEPs to tap into a very captive audience. We knew a media strategy that started with premium PMP deals and FEP ads as its foundation could help us surpass our furniture client’s expectations. But viewers can’t click on a TV ad, so we had to rely on other indicators to tie customer visits back to the ad campaign, which brings us to step 2. Step 2: Identify Customers Across All of Their Devices It’s no surprise today’s consumers multitask across a wide array of devices and applications while watching television. The challenge for many marketers is matching individuals to all of those devices across independent ecosystems. For example, knowing that the user watching Hulu on their connected TV right now is the same person simultaneously browsing Pinterest on their tablet and is the same person that will log into their work laptop later tonight to check out the headlines on CNN.com. Making sense of the data coming in from different platforms and devices is important to understanding what customers want and need. But most technology platforms treat a single user as different people when they switch between devices. This is where a cross-device identity graph comes in. A cross-device identity graph typically comes from a third-party data company who owns a database of device IDs related to each other and to an individual user. Working with one of these data companies, like LiveRamp or Oracle, marketers can access data that identifies users who were exposed to their ads, no matter the device they are using. So when a person sees your ad on one device, like their smart TV, and then visits your brand’s site from their tablet, the identity graph makes the connection and tracks the touchpoints as a single customer. Capturing this large user pool of cookies and device IDs is an important step in setting up a foot-traffic attribution study. Because while online shopping skyrockets for books, electronics and even groceries, furniture is one of the biggest purchases where people still want to try it before they buy it. So this step was critical to helping bridge the gap between online and offline measurement for our client. Step 3: Set Up a Foot Traffic Attribution Study to Tie Visits Back to the Campaign The holy grail for any advertiser is proof that your advertising resulted in a sale. For advertisers in verticals where purchases largely occur offline, like furniture stores, online to offline attribution is more complicated. This is where a foot traffic attribution study through a location intelligence platform, like Placed or Cuebiq, can make all the difference. These companies collect data from opt-in users to determine the real-world behaviors of smartphone consumers, like their location or proximity to a specific retailer. The goal is to measure how many people saw your ads and then went into one of your stores. Here’s how it works: GPS captures device IDs as people enter your store. Then the platform matches those IDs back to the IDs of those who saw your ad through your cross-device identity graph. This gives you a clear answer on if your ads actually worked to bring in more foot traffic. By comparing your exposed visit rate to the unexposed visit rate (those who came into the store without seeing your ad), you can quickly calculate the lift from your ads. Plus, many platforms allow you to send panelists who visit your store a short survey to further evaluate product awareness and purchase intent between exposed and unexposed users. You can also apply user attributes and behaviors tracked in a foot traffic attribution study to optimize your campaign. For instance, if a retailer sees that Hispanic audiences had a low delivery compared to other demographics but demonstrated a higher lift in visits, that meant this audience was more likely to visit the store but didn’t have to see as many ads as other groups to do so. With this in mind, you could increase bids on impressions to Hispanics for better cost efficiency. However, it’s important to know that foot traffic attribution studies require a large volume of data to make these optimizations and comparisons. So you should work closely with your partner to ensure you have the scale necessary. Knowing the advantages of using a foot traffic attribution study, we set up one to track users who saw our client’s connected TV furniture ads and then visited a store location. This opened the door to impactful insights that not only helped us optimize the campaign for better performance but also allowed our partner to prove their connected TV ads positively impact a person’s likelihood to visit their stores. After running for nine weeks on premium connected TV inventory, the campaign doubled foot traffic into the furniture retailer’s stores. While the campaign delivered impressive performance results, our optimizations also ensured the campaign remained cost-efficient — saving on average $7.85 in cost per store visit. A win worth talking about! If you want to get results like these on your next connected TV campaign, it’s important to leverage the right strategy and build in the tools and metrics to tie results back to your ads. 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