Consumers engage with content and advertisements across various devices and platforms, making an identity framework essential for establishing effective connections. An identity framework allows businesses to identify consumers across multiple touchpoints, including the relationships among households, individuals, and their devices. Combined with a robust data framework, businesses can understand the relationship between households, individuals, and marketing attributes. Consequently, businesses can tailor and deliver personalized experiences based on individual preferences, ensuring seamless consumer interactions across their devices.
We spoke with industry leaders from Audigent, Choreograph, Goodway Group, MiQ, Snowflake, and others to gather insights on how innovations in data and identity are creating stronger consumer connections. Here are five key considerations for advertisers.
1. Embrace a multi-ID strategy
Relying on a single identity solution limits reach and adaptability. Recent data shows that both marketers and agencies are adopting multiple identity solutions. By embracing a multi-ID strategy with solutions like Unified I.D. 2.0 (UID2) and ID5, brands can build a resilient audience targeting and measurement foundation, ensuring campaigns remain effective as identity options evolve across channels.
A diversified identity approach ensures that advertisers are not left vulnerable to shifts in technology or policy. By utilizing multiple ID solutions, brands can maintain consistent reach and engagement across various platforms and devices, maximizing their campaign effectiveness.
“I don’t think it will ever be about finding that one winner…it’s going to be about finding the strengths and weaknesses and what solutions drive the best results for us.”
Stephani Estes, GroupM
2. Utilize AI and machine learning to enhance identity graphs
Identity graphs help marketers understand the connections between households, individuals, their identifiers, and devices. This understanding of customer identity ensures accurate targeting and measurement over time. AI and machine learning have become essential in making accurate inferences from less precise signals. These technologies strengthen the accuracy of probabilistic matches, allowing brands to understand consumer behavior more effectively even when data fidelity is lower.
Adopting a signal-agnostic approach and utilizing various ID providers enhances the ability to view consumers’ movements across platforms. This strategy moves measurement beyond isolated channels, providing a holistic understanding of campaign effectiveness and how different formats contribute to overall performance. By integrating AI and machine learning into identity graphs, advertisers can develop more cohesive and effective marketing strategies that guide customers seamlessly through their buying journey.
“What we’re finding is more and more identity providers are using Gen AI to locate connections of devices to an individual or household that maybe an identity graph would not identify.”
David Wells, Snowflake
3. Balance privacy with precision using AI
AI-driven probabilistic targeting and identity mapping provide effective solutions for privacy-focused advertising. Rather than relying on extensive personal data like cookies, AI can use limited, non-specific information to predict audience preferences accurately. This approach allows advertisers to reach their target audience while respecting privacy—a crucial balance as the industry shifts away from traditional tracking methods.
According to eMarketer, generative AI can further enhance audience segmentation through clustering algorithms and natural language processing. These tools enable more granular, privacy-compliant targeting, offering advertisers a pathway to reach audiences effectively without needing third-party cookies.
“I think the biggest opportunity for machine learning and AI is increasing the strength and accuracy of probabilistic matches. This allows us to preserve privacy by building models based on the features and patterns of the consumers we do know, instead of transmitting data across the ecosystem.”
Brian DeCicco, Choreograph
4. Activate real-time data for better engagement
Real-time data enrichment introduces dynamic audience insights into the bidding process, enabling advertisers to respond instantly to user actions and preferences. This agility empowers marketers to craft more relevant and impactful moments within each campaign.
“Real-time data enrichment–where data companies can have a real-time conversation with the bid stream–is an exciting part of the future, and I believe it will open the door to activating a wide variety of data sets.”
Drew Stein, Audigent
5. Create and deploy dynamic personas using AI
Generative AI transforms persona-building by providing advertisers with richer audience profiles for more precise targeting. This approach moves beyond traditional demographic categories, allowing for messaging that connects more meaningfully with each consumer.
By using generative AI to craft detailed personas, advertisers can move beyond generic messaging to create content that truly resonates on an individual level. This personalized approach captures attention and strengthens consumer relationships by addressing their specific needs and interests.
“One cool thing we’ve built recently is a Gen AI-based personas product that generates personas to create highly sophisticated targeting tactics for campaigns.”
Georgiana Haig, MiQ
Seize the future of data-driven engagement
Focusing on these five key innovations in data and identity allows you to adapt to the evolving media landscape and deliver personalized experiences to your audience.
Latest posts
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
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. Let's get to work, together At Tapad, we provide actionable insights for marketers to deliver better ad experiences to their consumers through identity resolution. Interested in learning more? Contact us today at sales@tapad.com for a more personal conversation about your identity strategy. 1 The Trade Desk Q2 2020 Earnings Call Transcript, August 2020; 2 iSpot Report, via Deadline, July 2020; 3 Flixed.io, January 2020
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. Get started with The Tapad Graph For personalized consultation on the value and benefits of The Tapad Graph for your business, email Sales@tapad.com today!