The Promise of More Customers Lies in Data Collaboration

In late February, LiveRamp will hold its annual RampUp conference in San Francisco, which is billed by the event organizer as the world’s premier data collaboration event.

The conference promises to show how leading brands such as Delta, L’Oreal, Eli Lilly, and Disney are putting data collaboration in practice, revealing “the strategies that you can deploy today to maximize reach, optimize performance, and measure impact.”

Instacart, CostCo, TikTok, Best Buy, MGM Resorts, Fidelity Investments, and Harley Davidson will appear on stage. These brands will talk about how to share data to grow revenue. 

One of the panelists is Kristi Argyilan, Global Head of Advertising at Uber, who will address the future of commerce media and how it will be powered by “bold innovation and strategic collaboration.”

Effective orchestration between media owners, brands, agencies, and technology players in the adtech and martech sectors will be key if data collaboration is to become a reality.

The industry heavyweights know they have to lean into data collaboration to expand their addressable market, secure new customers, and grow their pie as privacy regulations bite, and they prepare for a world where Google’s third-party Chrome cookie no longer offers access to an easily identifiable digital audience. 

However, there are significant challenges in creating an effective data collaboration strategy, as outlined by consultancy firm Winterberry Group in a report released this month. Not least is the challenge of ensuring that audience data is actually of value. 

“Garbage in, garbage out” remains a fundamental challenge in realizing the full potential of data layer investments. The effectiveness of leveraging data hinges on its accuracy, consistency, and validity for intended purposes. While incomplete data was once a significant obstacle, advancements in AI have mitigated this concern to some extent. However, challenges such as siloed information, inconsistent formats, outdated data, and evolving privacy regulations persist, collectively undermining data reliability and demanding immediate attention from marketers,” the Winterberry report said. 

The consultancy’s report, Demystifying the Data Layer, is the result of surveying 200 senior marketing, data, analytics, and technology thought leaders across the US, UK, France, and Germany and conducting in-depth interviews with over 50 industry experts and influencers across the supply chain of data management and identity solutions.

Part of the challenge for advertisers is the complexity of the data collaboration solutions (DCS) market, as outlined by Adobe, which recently outlined the emergence of five models, each offering their unique features, advantages, and considerations. Those models are:

• Standalone DCSs that serve as point solutions, allowing for composable systems that work across partners with similar or interoperable capabilities.
• DCSs with embedded identity to provide data interoperability between partners within a permissioned environment.
• Data warehouses or data lakes with integrated DCSs to enable the frictionless movement of data between data layer components.
• CDPs with integrated DCSs that enable seamless activation for both adtech and martech use cases. 
• Walled gardens with embedded DCSs that are the primary facilitation points for sharing within their ecosystem.

The data clean room is where brands are housing their sensitive customer information, as noted by the Winterberry Group. “As the market seeks to limit the movement of proprietary data outside of private environments, Data Clean Rooms emerge as preferred platforms for secure data collaboration across organizational boundaries,” their report says. 

Furthermore, the consulting firm says the focus will now shift to brands seeking to create a robust data strategy, creating a market that will soon be worth more than $30 billion.

“In response to the critical need for a privacy-compliant, secure, and actionable data layer, investment in data, data services and data technology is forecast to grow from $27 billion in 2024 to $33.8 billion by 2027, reflecting a commitment to leveraging data as a strategic asset for driving business growth and enhancing customer experience. As organizations adapt to these shifts, the journey toward architecting an effective data layer remains pivotal in shaping the future of marketing and advertising.”

Data clean room and identity vendor InfoSum believes another critical element will be measurement, as advertisers are concerned that making large investments in platforms such as CDPs (Customer Data Platforms) are under-utilized and don’t provide value.

“How many impressions did our campaign generate? How many clicks? What was your ultimate click-through rate, CPM, cost per acquisition, or revenue per click? Advertisers today need top-of-the-line measurement solutions (including audience verification, reach and frequency, attribution, media mix modeling, and incremental lift) to assess the effectiveness of their marketing campaigns,” InfoSum’s Vice President of Product Devon DeBlasio wrote. 

De Blasio added: “But in today’s fragmented advertising ecosystem, measurement often calls for media exposure data (typically in the form of individual impressions) from multiple data sources to be joined and matched with the advertiser’s conversion data (or its partners’ data if the advertiser has little first-party data to start with, like a CPG brand). More often than not, one of the parties jumps the gun and shares sensitive personal data with the others. Or everyone gets lost on their way to the legal department, and nothing gets done.”

In the adtech world, DSPs are working with brands to unify data and share insights between in-house and agency teams. This move to data sharing across teams is likely to increase as agencies and DSPs tackle the avalanche of information on their dashboards. 

Further innovation will be vital, not the least the stunning arrival of AI-optimized data clean rooms and marketing tools that can make it easier for brands to model, create, and action multiple sources of data almost instantaneously. 

The next evolution will likely be the application of AI software to a brand’s first-party data, as touted by GrowthLoop Chief Data Strategy Officer Anthony Rotio.

“We’re at the point with AI where everyone seems to be using it for marketing and content creation. That means your competitors are using it too. So how do you stay competitive in a world where AI is ubiquitous? The next frontier is using that AI on your data cloud with your most valuable resource: your first-party data. If you want to build something that’s super personalized to your customers, having your data as something that only you [and AI] have access to is a competitive differentiator,” says Rotio

Data vendors will likely be engaged in an intense battle for market share as AI-optimized data collection and personalization drive the next wave of collaboration.