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AI-Driven Targeting for Startup Growth: Personalizing Ads for a High-Value Audience of 3.7 Million
The Old Way: Targeting Ads Based on Third-Party Data
In the past, companies relied heavily on third-party data to target their ads. This data was often acquired from data partners and used to build cohorts and segments for advertising purposes. While this approach allowed marketing teams to access large data sets, it also came with some challenges. The team couldn’t always trust the quality of the third-party data, leading to questions about its accuracy and origin. Additionally, as privacy and user data regulations became more stringent, relying on third-party data posed a potential liability for companies. A shift towards a first-party data strategy became necessary.
Challenges in Moving to a First-Party Data Strategy
Transitioning from a strategy that relies heavily on third-party data to a first-party data strategy can be a challenging process. First-party data sets are often less extensive than third-party data sets, resulting in a sudden loss of signal for marketing teams. While first-party data may include customer names and emails, it may lack additional details such as product affinity. Artificial Intelligence (AI) can bridge this gap by generating predictive insights from first-party data. These insights enrich customer profiles and increase the value of the first-party data set as a whole.
Using AI to Turn First-Party Data into Better Segmentation and Advertiser Outcomes
Companies that leverage AI for personalization see several benefits, including increased engagement, more clicks, higher conversions, and improved ROI. One brand that is successfully using AI for better segmentation and advertising outcomes is the Wall Street Journal (WSJ), a renowned news publication with a high-value audience. By partnering with mParticle Cortex, the WSJ has been able to generate predictive audiences based on their first-party data, increasing advertising performance while also ensuring data privacy.
Partnering with mParticle to Enhance Advertising Performance
The Wall Street Journal is known for its high-net worth audience of political leaders, business executives, and decision-makers. These individuals trust the WSJ’s journalism and use it to make important decisions in their daily lives. To help advertisers reach this valuable audience, the WSJ needed to leverage its own first-party data and develop a robust data strategy. By partnering with mParticle and its Cortex AI engine, the WSJ was able to build predictive audience segments and cohorts for advertising campaigns. This approach allowed them to create more effective ad segments using first-party data alone, resulting in higher conversions, click-through rates (CTR), and engagement.
The Benefits of AI-Driven Segmentation for First-Party Data
By utilizing AI-driven segmentation for their first-party data, the WSJ was able to significantly enhance their advertising performance. Instead of solely targeting individuals with specific job titles, they could identify users who were likely to be interested in an advertiser’s product based on their behavior in real-time. This approach broadened their targeting capabilities while increasing CTRs and conversions. Advertisers benefited from the WSJ’s ability to reach a wider audience of potential customers with similar interests to their target group.
Data Governance and Privacy Compliance
Privacy and data governance were crucial considerations for the WSJ throughout the implementation of their first-party data strategy. The company worked closely with their legal and data governance teams to ensure compliance with regulations and maintain data hygiene and accuracy. By centralizing and unifying all customer data in one place, the WSJ was able to streamline their data management processes and ensure the quality and reliability of their first-party data.
Benefits of a First-Party Data Strategy
The WSJ’s first-party data strategy has proven to be a game-changer for the publication. Advertisers trust them more and are more likely to spend their advertising dollars with the WSJ due to the quality and effectiveness of their ad targeting. The WSJ has seen a higher return on investment (ROI) for clients who use their first-party data products. By combining AI-driven segmentation with their first-party data, the WSJ has built a competitive advantage in the industry and set themselves up for continued growth and success.
Conclusion
Transitioning from a third-party data strategy to a first-party data strategy can be a complex process, but it’s crucial for companies that want to enhance their advertising performance while ensuring data privacy. By leveraging AI-driven targeting and partnering with mParticle, brands like the Wall Street Journal can unlock the full potential of their first-party data, create more effective ad segments, and achieve better outcomes for their advertisers. With the rise of privacy concerns and regulations, embracing a first-party data strategy has never been more important for startup growth.
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