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
While effective affiliate marketing relies on two groups, the publishers (affiliates) who display advertisements online and the advertisers (merchants) who aim to increase sales for their online shop, incorporating insights from Experian Marketing Services’ Hitwise can strengthen affiliate programs.
New data from Experian Marketing Services’ Simmons® ConnectSM mobile and digital panel sheds light on the way smartphone users spend time using their phone, with the average adult clocking 58 minutes daily on their device. On average, smartphone owners devote 26% of the time they spend on their phone talking and another 20% texting. Social networking eats up 16% of smartphone time while browsing the mobile web accounts for 14% of time spent. Emailing and playing games account for roughly 9% and 8% of daily smartphone time, respectively, while use of the phone’s camera and GPS each take up another 2% of our smartphone day. *Activities include use of a smartphone’s native features dedicated to each activity as well as downloaded apps whose primary function falls under the given activity. For instance, “watch video” includes the act of watching video on the smartphone’s native video player as well as use of video apps such as YouTube, Netflix, etc. iPhone versus Android users Smartphone users may constantly debate which operating system is supreme, but we see clear differences between the ways consumers use their phone depending on the operating system that runs it. For starters, iPhone users spend an hour and fifteen minutes using their phones per day, a full 26 minutes more than the typical Android phone owner. Additionally, iPhone and Android smartphone owners use their phones in markedly different ways. For instance, 28% of the time that Android users spend using their phones is dedicated to talking, whereas iPhone users spend only 22% of their smartphone time talking on the device. Android owners also devote a greater share of time visiting websites on their phone than iPhone owners. On the other hand, iPhone owners spend a disproportionately greater share of smartphone time than Android owners texting, emailing, using the camera and social networking. Note on time spent It may surprise some to read that an activity like watching video accounts for such a small share (less than 1%) of the typical adult’s daily smartphone use. However, for the charts above to sum to a single daily total it was necessary to calculate individual activity contribution using a base of all smartphone owners, including those who don’t spend any time engaging in a given activity during a typical day. The chart below provides additional insights into the time spent engaging in the major smartphone activities examining only those individuals who engaged in each activity during a 24-hour period. I’ve also added into the chart a reach and frequency metric to indicate the popularity of each activity and the number of times per day that individuals engage in them. In the chart, the activities with the largest bubbles are those in which the greatest share of smartphone owners engage during a typical day and include the usual suspects: talking (79%), texting (76%), visiting websites (62%), emailing (61%) and social networking (52%). Activities with the fewest daily participants are: watching video, which 2.3% of smartphone owners do during a typical day, and reading, which just 0.5% of smartphone owners do daily. Given that nearly 98% of smartphone users don’t watch videos on their phone during a typical day, it’s easier to understand why video comprises such a low share of the average adult’s daily smartphone use. However, the chart above reveals that those who do watch video on their phone spend, on average, 5 minutes a day watching videos spread out over 4.2 different viewing sessions. For more information on consumers’ usage of smartphones, digital tablets, computers and other traditional and digital media platforms, check out Simmons Connect.
New health information exchanges are prompting data quality efforts, as state and local healthcare agencies look to electronically share patient data.