Mounting pressure on legacy digital identifiers and expanding consumer data regulations recently prompted leading management consultancy, the Winterberry Group, to explore the marketing industry’s response.
With input from senior brand managers and research conducted across 26 industry leaders involved in the use of data and data collaboration, Winterberry published ‘Collaborative Data Solutions: The Evolution of Identity in a Privacy-First, Post-Cookie World’.
The paper highlights a generational opportunity for permissioned data partnerships to improve scalable insights, measurement and marketing activation dramatically. In short, harnessing a collaborative data strategy will provide marketers a competitive advantage. In the sections that follow, highlighting each of its major approaches, the focus is on overcoming challenges through collaborative data solutions.
Why collaborative data?
In the report, Winterberry identifies four distinct categories that make up collaborative data solutions: data cooperatives, data marketplaces, data exchanges and technical data environments.
The research suggests an expanding number of brands using multiple solutions and multi-party partnering across the industry to build the most successful collaboration strategies. Brands spanning the spectrum, from those with more data to those that have less, all have an equal opportunity to build a more strategic and collaborative data approach with the support of this research.
Still, the addition of multiple new solutions and partners can sound overwhelming, especially in an uncertain environment such as the one we find ourselves today. The good news is, streamlined approaches are simplifying the process.
Start with a data cooperative
So, how can a motivated marketer ramp up a collaborative data strategy without inflating the number of partners, contracts, relationships and data sharing streams? Data cooperatives offer streamlined and proven collaborative data environments, particularly for multichannel marketers with established first-party data resources.
Winterberry’s research supports this position, identifying that “data cooperatives are the most broadly adopted and accessible collaborative environment … [due to] early market entry and subsequent maturity.” Plus, the barriers to entry are low because they are “open to participants of all sizes, with limited requirements for advanced technology or data management for participating parties.” Of the surveyed brand marketers, 59.5% are currently leveraging cooperative data solutions, with another 26.2% planning to do so.
For brands that are already members of a co-op, Winterberry suggests that “to achieve the greatest benefit from the cooperative model, many members participate in two or three co-ops, reaping the benefit of a diverse set of contributors.”
What is a data cooperative?
Identified in the research as “the initial permission-based solution,” data cooperatives were originally designed to facilitate collaboration for direct mail marketers. The give-to-get model asks brands to contribute permissioned first-party data, which the cooperative anonymizes and aggregates, architecting and maintaining a collective analytic powerhouse that benefits all members. A cornerstone of this solution is the rich transactional data members contribute. Purchase behaviors and the ability to ingest digital signals across thousands of brands transform predictive models, providing “a powerful opportunity to find new prospects both online and offline.”
Crucial elements of this definition distinguish data cooperatives from other collaborative solutions. The first cooperative launched in 1992, almost a full decade prior to the launch of data marketplaces and well in advance of technical data environments and data exchanges. This head start means that while co-op driven solutions have a strong history rooted in offline data, they have evolved through digital transformation and continue to prove the value of integrating offline and online data. Three operational decades have also resulted in experienced and reliable systems of compliance and trust-building.
Co-ops can range from hundreds to thousands of contributing brands. Some require more detailed levels of data than others. And some focus on specific verticals to ensure powerful predictive signals that meet a particular industry’s KPIs. In all solutions, though, the large number of contributors ensures constantly refreshed data.
The collaborative benefit
The benefits of data cooperative solutions are robust — ranging from organization and enrichment of first-party data to customized analytics and access to unique data. With a co-op as the hub of collaborative data strategy, another key benefit is the rich partnerships these established companies have developed across the ecosystem.
As part of a cooperative, brands can easily partner with other members — a shared, permissioned environment reduces the amount of legal and logistical resources required to activate. Many co-ops also bring in third-party enrichment sources and connect to platforms, publishers, service bureaus and even walled gardens. These established relationships provide an accessible network for marketers to easily explore collaboration and activation opportunities both inside and outside the cooperative.
Other collaborative solutions — exchanges, marketplaces and technical data environments — have their own benefits and roles to play in long-term collaborative strategies. As solutions continue to evolve, the lines between each of these are likely to blur. For example, data cooperatives taking a cue from technical data environment strengths are incorporating data clean rooms to support their existing cross-member data collaboration processes.
For most marketers, establishing a partnership with a forward-thinking data cooperative represents a quick path to success. Many co-ops allow brands to test their solutions before committing to sharing data — test driving the data, gauging how the analytics team partners with others and exploring multichannel activations and compliance practices in action. Once contributing, brands will have ready access to data at scale, proven data science resources and established compliance practices. And their teams will be armed to focus on the superpowers that drive success, such as leading-edge brand development and compelling customer experiences.
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