When we launched our data marketplace earlier this year, we set out to transform how the industry discovers and activates privacy-safe audiences and maintains addressability across display, mobile, and connected TV (CTV). Yieldmo was one of the first adopters and their story speaks volumes about what’s possible when flexible tech meets premium data.
Large retail brand boosts in-store traffic with Yieldmo and Experian
Yieldmo, an advertising platform known for its inventive, AI-powered creative formats and privacy-first inventory, partnered with Experian to support a leading athletic retailer’s campaign focused on driving in-store traffic. The goal? Attract in-store shoppers likely to purchase from competitors, particularly during key sales windows.
Using Experian’s Audience Engine platform, which includes our proprietary and third-party data marketplace, Yieldmo built a high-performing, self-serve targeting strategy that included both conquesting and in-store shopper segments. With the ability to easily combine Experian Audiences and Partner Audiences, like those from Alliant, Circana, Webbula, and Sports Innovation Lab, Yieldmo quickly built precise apparel and footwear audiences. Using Experian’s identity graphs in Audience Engine, Yieldmo increased cross-channel addressability to maximize campaign scale and impact.
“Experian’s data marketplace in Audience Engine fills a critical gap, letting us quickly search by brand, build smarter conquest segments, and activate custom audiences fast. The platform is flexible and the support is hands-on and reliable.”
Abby Littlejohn, Director of Sales Planning at Yieldmo
With self-serve setup that cut down manual work, the ability to build highly tailored audiences, and expected lift in store visits, Experian helped the team achieve standout results.
“We selected Experian as our primary third-party data partner based on contract ease, audience quality, and speed. Through Experian, we can find high-performing audiences from multiple providers that meet our client’s targeting objectives. We include Experian audience segments in 80% of formal RFP proposals and are in active discussions on how to optimize for future campaigns—making Experian a go-to partner for third-party targeting.”
Nelson Montouchet, AVP, Strategic Partnerships, Yieldmo
More data, more reach: Experian’s data marketplace fuels smarter targeting across ad platforms
Today, just months after launch, Experian’s data marketplace is gaining traction across the ecosystem.
Over 10 platforms, including leading supply-side platforms (SSPs) and TV platforms such as Madhive, OpenAP, and Optimum, are now actively utilizing our data marketplace to enhance their activation capabilities. As privacy rules tighten and many identity signals start to fade, a lot of activation platforms are finding it tougher to reach their audiences. This is where our data marketplace shines, with one of the most comprehensive identity graphs out there, 126 million households, 250 million individuals, and over four billion active digital IDs, we make it easy to activate audiences while keeping addressability high across channels. We preserve accuracy when scaling to digital IDs via our identity graphs since Experian is rooted in offline data, which provides better connections and smarter targeting.
“Our long-standing partnership with Experian and breadth of Experian’s data marketplace, combined with the interoperable, direct matching methodology of our Open Identity solution, make it possible for OpenAP to enable advertisers and agencies to use best-in-class data partners to build audiences with the highest fidelity and consistently reach audiences at scale wherever they are consuming content across premium video.”
Chris LoRusso, Chief Business Officer at OpenAP
Experian’s data marketplace has grown to include over 20 premium data providers, such as:
“We’re thrilled to bring PlaceIQ’s privacy-first, visit-based audiences to Experian’s marketplace, giving brands quick and easy access to high-intent shoppers. From recent big-box customers to yoga-studio regulars, advertisers can add real-world relevance to campaigns across every channel.”
Brian Bradtke, Head of Partner Development, Precisely PlaceIQ
These partnerships bring unique value to platforms looking to understand and engage audiences more effectively, whether through physical location intelligence, sports and fandom insights, or behavioral intent signals.
What’s next
We’re focused on expanding our data ecosystem and helping platforms and marketers turn fragmented data strategies into a unified competitive advantage. If Yieldmo’s story is any indication, this is just the beginning. Let’s connect and explore how Experian’s data marketplace can help you drive more revenue, scale your audience reach, and stay ahead of privacy shifts.
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To our valued customers and partners, it’s been an exciting week here at Tapad! As announced in a press release this morning, Tapad is now a member of the Experian family. We’re thrilled to continue to grow as a leader in identity resolution under the umbrella of a global expert in data, analytics and technology. Tapad and Experian are deeply connected by our commitment to serving the needs of our customers; and with a focus on quality of the data we provide, we have a common goal for the future of identity in the advertising ecosystem. As part of this announcement, we wanted to assure you, our valued customer, that we remain deeply committed to serving you today just as we always have. Nothing will change in your daily operations with Tapad. Experian immediately recognized that the success and growth of Tapad was directly tied to the strength and depth of its team members. As such, the acquisition will not result in any changes to day-to-day contacts at Tapad, or processes with weekly graph deliveries and other product support. Experian’s faith and investment in Tapad’s future and the future of identity resolution underscores what we’ve always believed our products could achieve and that we will be able to continue serving brands, advertisers, publishers, and the advertising and marketing ecosystem for years to come. On a personal note, I am excited to be transitioning my role as Chief Operating Officer of Tapad to the General Manager position of a global business that’s achieved exponential growth over the past several years; culminating in this strategic acquisition that will no doubt bring even more value to our customers in the future. We remain committed to open communication and welcome any questions you may have. Thank you,Mark Connon | General Manager, Tapad Contact us today
Addressable TV has been through a transformation in the past year. Streaming content has become the most coveted space for creators and advertisers with the rise of new apps and platforms; but the influx of stay-at-home orders around the country have shifted television viewership as we know it, and streaming apps are popping up in droves to take advantage. So, how can you? With no shortage of opportunities to advertise on addressable TV and CTV, how does it fit into the media mix? And furthermore, how can you attribute this household-level device into your overall strategy? Tying it all together Layering addressable TV within digital ad campaigns couldn’t be easier today — but applying the right targeting and cadence between all of your digital efforts; and tying them together in attribution takes the right kind of data. Marketers can use CTV identifiers coupled with other device identifiers available in The Tapad Graph to not only target impressions but also map addressable TVs within the consumer journey; and unify strategies between household decision makers to better personalize messaging. 1 The Trade Desk Q2 2020 Earnings Call Transcript, August 2020; 2 iSpot Report, via Deadline, July 2020; 3 Flixed.io, January 2020 Contact us today
For the past several years ad-tech defined the value of identity at the individual level; made possible by the evolution of data, technology and machine-learning. But, earlier this year COVID-19 set in motion many shifts in consumer digital behavior. The more we’ve been working and learning from home, using devices that are shared amongst an entire household, the more apparent it is that marketers need to shift their strategies to align with these changes. Did you know the average household owns eleven or more connected devices? And the longer we’ve been at home, the more these devices are shared by multiple individuals. If you’re looking for a few simple ways to evolve from an individual focused strategy to a household strategy, here’s a good place to start: Audience segmentation Traditionally, audiences are built with a narrow focus on a single user, and what known attributes about that individual or their brand engagement can be leveraged for a targeting strategy. Now that screens are being shared between multiple users in a home, how can you be sure you’re identifying them correctly, and thus, segmenting them in the right buckets for targeting? The key lies in the ability to connect those points through identity resolution. Using ad exposure from household level devices, followed by a second engagement from an individual within that household can indicate a user is a better candidate for purchase or conversion than others. So before you build audiences for targeting, you can qualify them at the household level for segmentation with more confidence. Example: An auto advertiser uses audience segments from a third party provider such as ‘auto intenders’ to target individuals with new pricing offers. They would continue retargeting these users, unaware that some are connected in the same household, and thus are probably not all in the market to actually get a new car. By bucketing users that share a common household device within this third party segment, they can hone in on which individuals are actually in-market for a car and evolve their strategy to be more effective. Targeting Retargeting, frequency capping and sequential messaging have always been meant for an individual user — the more they’re exposed to your brand in a personalized way, the more likely they are to take the desired action. But, have you considered that multiple users could have a shared initial exposure to your brand? Today, you can target a household of potential consumers on a shared device like a CTV, and employ those retargeting strategies based on that common initial exposure. Starting at the household level, means you can compare movement through the funnel between different individuals in that household, and tailor your targeting accordingly. Perhaps you realize only one person in that household will convert and you tailor messaging to them more frequently, while confidently suppressing the other individuals. Example: a CPG brand uses OTT advertising, but doesn’t incorporate it within their sequential strategy, because they consider it just a ‘brand awareness’ opportunity. By using OTT more strategically as a household level engagement, it can reveal which individuals within a household are more favorable towards a brand further down the funnel. So, you can spend impressions targeting those users, rather than wasting impressions on multiple individuals within the household. Measurement Measurement and attribution are imperative to understanding the path to purchase and making strategies more efficient over time. Often that efficiency involves adding or removing devices and channels from a targeting strategy based on their contribution to an action or conversion by an individual. This year we’re seeing addressable TV devices explode in use, which are shared at the household level. Even desktop computers are being used by more people in the home due to COVID-19. So, assuming a linear path of attribution by an individual is missing the full picture. Identity resolution can help you understand where messaging was more effective for some users in the household than others, and leverage that insight to continue more effective strategies in the future. Example: Without a household view, a direct-to-consumer brand would assume all interactions from one device would be coming from a single individual, and that could create a higher cost-per analysis. By incorporating the household level devices into attribution models, they can find efficiencies between touch points of multiple users, and learn how those split off into individual paths to conversion. Not only can this DTC create a more effective model, but they can use that model to create cost efficiencies in the future. Contact us today