Data Fundamentals You Need to Implement to Enable GenAI and Increase Personalization

The technology landscape is evolving and new tools like generative AI are poised to provide powerful audience insights, but many organizations aren’t taking advantage.

The rapidly evolving analytical capabilities of advanced, data-powered technologies are providing compelling opportunities for broadcasters, streamers, publishers, advertisers, and other media enterprises to improve their traditional and digital advertising strategies. But Capgemini has found that many companies in this sector are struggling with this significant transformation of the media landscape – and the root cause of their challenge can often be traced to infrastructure fundamentals and inadequate data practices.

Understanding audiences dominates discussions. Media organizations are under increasing pressure to better understand audience behavior, and the challenges around this were the topic of much discussion at this summer’s gathering of industry leaders at Cannes Lions. To share insights about the issues, Capgemini joined a cross section of the advertising and media industry at Cannes to engage in a series of panel discussions organized by the Coalition for Innovative Media Measurement (CIMM).

While specific challenges varied by organization and each had its own point of view, it was clear companies need to combine data in multiple formats, from several sources, to build more insightful audience profiles. Participants raised a number of key issues, including:

• How to successfully target specific audience segments in both short- and long-form content

• How to measure the overall performance of a campaign more accurately and with more granularity

• How companies can use advanced technologies such as Gen AI to reduce cost and accelerate these activities

Rising above these challenges will require the right combination of technologies powered by generative AI. Tools and methodologies such as media mix modeling, and multi-touch attribution coupled with the corresponding upgrades in sentiment analysis, social media analytics, and demand analysis will promise to make media companies more agile and effective.

For example, media mix modeling can leverage data to determine the effectiveness of various marketing efforts on product sales, while multi-touch attribution can identify how each marketing touch point influences a customer’s conversion from interest to action. Generative AI can amplify the effectiveness of these solutions, increase the effectiveness of predictions and recommendations, and enable business leaders to interact with the data through more intuitive, natural language interfaces when tracking performance.

At the same time, these technologies can help enterprises stay ahead of increasingly complex privacy laws and regulatory measures that govern how they can – and cannot – use data to better understand their audience. This is a significant and growing challenge, and success is critical – as failure can result in serious consequences. These include financial penalties and loss of trust by consumers.

Pay attention to three essentials. But companies can only take advantage of these powerful tools if they have prepared an appropriate data and infrastructure foundation. To achieve this, Capgemini has identified three essentials every company should embrace.

Aim for top-quality first-party data. Companies able to capture, validate, and analyze their first-party data – the data collected from subscriptions, logins, and direct interactions – will enjoy a significant competitive advantage over those that cannot. Effectively analyzing its first-party data improves the organization’s ability to optimize its media mix and improves the results from multi-touch attribution tracking. What’s more, firms that properly collect this data are able to combine it with information from other sources – in privacy-compliant ways – to unlock even broader audience insights.

Deploy unified data platforms. It’s important to ensure the enterprise’s data platform can capture data from all sources – including applications, databases, structured and unstructured data – from within the company and via third parties such as Nielsen, VideoAmp, iSpot.tv, and Comscore. Not only will this enable organizations to effectively draw insights, but it will also prepare the organization to support the needs of Gen AI to deliver predictive analytics.

Insist on infrastructure excellence. It’s critical that companies build out a governance and compliance framework on their data platforms. This will enable the large language models that power generative AI to train across multiple, decentralized servers while keeping data local to those servers and enhance privacy. In the meantime, ensuring that a highly federated consumption layer is in place enhances dashboards and reporting tools to facilitate data-driven decision making.

Proper fundamentals unlock new capabilities. Ensuring these fundamentals are in place will enable enterprises to take advantage of new analytical services powered by Gen AI. For example:

• Contextual advertising is a powerful alternative to cookie-based marketing that leverages AI to analyze the content of a webpage and place ads that are relevant to the content being consumed by the visitor.

• AI is also driving personalization, which tailors content recommendations in response to the visitor’s behavior and preferences without relying upon third-party cookies.

• Real-time analytics enables organizations to make immediate adjustments to their media mix based on current performance data.

• AI models can be used to dynamically allocate ad budgets across different channels and campaigns in real time, maximizing the effectiveness of each marketing dollar.

• AI is also enhancing the power of incrementality testing – controlled experiments such as A/B testing or holdout testing – to improve how companies evaluate the true effectiveness of specific marketing activities or channels.

• Generative AI can leverage large volumes of data to predict media performance, estimate the impact of each marketing channel, and optimize media mixes in real time.

• AI can also help companies remain in compliance with all applicable privacy laws and regulations governing data collection and use, in every jurisdiction in which they operate.

Powering audience understanding, at scale. In today’s rapidly-changing business and technology environment, media organizations must be agile as they adapt their advertising strategies to thrive – and engaging the right strategic technology partner is a must.

Capgemini works closely with its clients in this sector – at all levels of maturity – to provide the data clean rooms, data integration, and data analytics that all companies need to succeed. To do this, Capgemini draws upon its global network of technology partners, its expertise in multiple industrial sectors, and its experience in helping organizations navigate business process transformation.

In addition, Capgemini has developed a broad range of use cases that leverage generative AI and other advanced technologies to help clients in this sector address specific objectives and deliver tangible value.

To learn more, please contact: Camila Fierro at camila.fierro@capgemini.com