
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

On some level, collecting data and analyzing it to find meaningful conclusions has always been part of how marketers go about connecting with consumers. Their strategies have improved dramatically over time, though. Perhaps in a previous era, marketing executives were only able to make sweeping generalizations about large swathes of the population. But, as marketers have gathered more data on individual consumers, they’ve found ways to fine-tune their searches. They’re no longer messaging to groups in vague terms. Smart Data Collective recently examined the marketing world’s transition away from broad stereotyping toward better targeted forms of data mining. Josh Brown, a member of the marketing team at business and IT consulting company Iconic Mind, argues that this era of overgeneralization is coming to an end. We now have the capability to zoom in on the specific customer. “Big data is how successful companies are building more detailed models of consumer behavior,” Brown wrote. “Instead of relying on the traditional demographic models that marketers used when we were operating in a mass consumption environment and had nothing better, big data capitalizes on developing market trends to allow businesses to become far more specific when segmenting their customers.” Brown cited Amazon.com as an example. The online superstore is notable for its targeted recommendations of products that shoppers see every time they log on to the site – the advisements are impressive because they’re usually right up the customer’s alley. Amazon doesn’t generate these ideas by making guesses based on whether the consumer is old or young, male or female – instead, the site takes in specific information about people’s buying histories and looks for similar products. This approach is quickly becoming mainstream. It’s not hard to understand why – people don’t like being reduced to profiles of their demographic characteristics. Consumers are expecting more from the companies they do business with. Thanks to the rapidly improving technologies that companies use for data collection, marketers can be more targeted and make more intelligent interactions. However, to take advantage of these new technologies, marketers need to maintain high quality data. Without a data quality strategy, customer information will be spread out across the organization, making it difficult to make intelligent marketing offers. To learn more about improving your understanding of consumers, check-out our infographic on building a single customer view.

Adam Garone is the CEO & co-founder of Movember, the annual world-wide charity movement dedicated to changing the face of men's health – all through the power of the moustache. To date, over 3 million moustaches have been grown and supported for Movember, raising more than $440 million to change the face of men's health. Adam kicked off day two of the EMS Client Summit by saying he’s a lucky guy because he gets “to wear a 1993 porn stash year-round.” That line got a laugh, but Adam’s storytelling around Movember really caught the attention of Summit attendees. Adam had learned that prostate cancer affects as many men as breast cancer does women, and while discussing this fact over beers with his brother in Australia, the idea for Movember was born. They took the Aussie slang for moustache (“mo”) and combined it with “November” (a good month for men to grow them) to create the name. That was in 2003 and over the last decade, Movember has become a global movement around prostate and testicular cancer awareness, as well as men’s mental health issues. Watch his full presentation below: [Watch video on YouTube] Here are some cool facts cited by Adam: Everyone who grows a moustache for Movember is a “celebrity ambassador.” Last year, 2.7 billion conversations about Movember and men’s health issues were generated during the month of November. Most foundations go out with a “fear-based message” (x number of men die from cancer each year, for example). Movember has never done that. They encourage nicknames (i.e., participants are called “mo-bros”) and want people to have fun with it. Adam’s message: don’t be part of it because you’re scared, but because you will be fine and you get to help others. Each year they totally revamp their brand, changing the look, feel and tone. A few years ago their theme was “The Modern Gentleman” and last year it was “Movember and Sons,” and played off the relationship between father and son. Movember raised $145 million last year. They put 10% of the funds into a pool that goes towards research around other diseases. Adam says this kind of collaboration is to help reduce the heaving competition amongst charities that typically compete for donations. Key takeaways when it comes to growing a foundation (or business) from the ground up: Start with a great idea – naivety is good Rely on strong leadership –have a clear vision and detailed plan and work really, really hard Recruit amazing people – preserve culture and values During rapid growth, keep it simple—stay true to your core Brand management is key – sometimes you have to say no to potential partners because they don’t fit with your brand (in a humble way, of course) Know your customers – inspire them to become your ambassadors Partnerships are key Never underestimate a room full of people

These days, there are a number of buzzwords being thrown around the marketing industry and the data management space. One of the biggest? Say it with me: Big Data. NPR argued last December that ‘big data’ should’ve been the “word of the year,” in part due to the re-election of President Barack Obama. Obama’s campaign managers didn’t let the Republicans’ monetary advantage discourage them. Instead, they gathered information on their voters and compiled important analytics based on that information. By handling this mass of data in an organized and well thought out process, they were able to more effectively appeal to voters and ultimately win the re-election. Marketers and corporations across the country were inspired by the campaign’s success, and have turned to big data to solve their problems as well. Anyone who catches the news on a regular basis, shops online, or owns a smartphone can see this evolution firsthand. However, it’s worth mentioning that this progression doesn’t necessarily mean “big understanding” or “big information.” Many companies are faltering in their efforts to harness big data and make real use of it. The pool of information is constantly changing, and as so many businesses rush to gather the data in real-time, it becomes even more challenging to keep pace and actively comprehend information as it becomes available. And the challenges go beyond the initial harnessing of the data. As big data continues to grow, companies are running into issues of incorrect and duplicate data in their systems. This erroneous data is a result of poor processes that companies have in place, and oftentimes begins at the point of data input. For a number of companies, data input is performed on a daily basis via their call centers. When incorrect data is recorded, it prevents sales representatives from getting leads in a timely manner, and hampers them further when they try to contact the correct individuals seeking assistance. The resulting slower response time then goes on to impact a company’s SLA and credibility to the population they serve. There is no doubt that when processed correctly, big data can be integral to a company looking to improve their understanding of the customer’s needs and wants. But data quality is an important consideration during the transition, and one that must be confronted before big data can reveal all it has to offer. To learn more about big data and how it relates to the data quality initiatives that may be taking place within your organization, watch Experian QAS’ webinar, “Ensuring Data Quality in your Big Data Initiative.” Learn more about the author, Erin Haselkorn