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Better data collaboration will boost industries beyond digital advertising
May 31, 2023
Data collaboration has been an especially hot topic in digital advertising. Privacy changes by Google and Apple as well as fresh regulations from California to China have incentivized advertisers to seek new data sources to target audiences and measure the efficacy of ad spend.
But the digital media industry is hardly the only one that can benefit from improved data collaboration. Many other verticals, such as retail and consumer-packaged goods (CPGs), finance, travel and hospitality, and healthcare can benefit from the intelligence at scale that enhanced, anonymized, and secure data collaboration provides.
Here is how each of those industries can benefit from data collaboration and why the practice is difficult, but becoming easier, to implement.
Retail and CPGs
CPGs cannot rely on just one retailer to understand the performance of their products. They need to source and combine data from many retailers often working across tens of thousands of locations. For example, let’s say a global CPG company, which owns many brands in its portfolio, wanted to understand product performance by location. It would need to source, pool, anonymize, and normalize data from several, if not dozens, of retailers.
Solving this problem would help retailers save supply chain costs, refine product allocation across markets, and enhance product development. With a better understanding of which chip flavors perform in each market, the CPG company could streamline materials sourcing and product distribution. It could also get a more granular understanding of high-performing flavors and double down regionally instead of making product decisions based only on top-line sales figures.
Another domain that could benefit from better data collaboration is finance. Consider fraud detection. One bank may suspect that a specific individual or organization is engaging in fraudulent activity. But if the bank wants to identify a pattern of behavior, it may need to connect the dots across several financial institutions. By sharing anonymized data that can still be queried for pattern detection, banks can collaborate to root out fraud without sacrificing consumer privacy or competitive advantage.
Alternatively, financial institutions may wish to understand market trends by examining activities across banks without compromising the privacy or security of any one institution or consumer. Asset managers cannot know exactly who’s transacting with whom at what price point, but they can query anonymized, aggregated data to better understand trends. Privacy-safe data collaboration makes that possible.
Travel and hospitality
In travel and hospitality, data collaboration can open up customer intelligence and partnerships that allow consumers to get more out of loyalty programs. For example, Delta, which has a partnership with American Express, might want insight into the transaction history of American Express customers to identify additional partners with whom Delta regulars can spend their miles. This would help Delta offload points for customers who have racked up too many without using them while empowering customers to get the most out of their cards and American Express to better serve its cardholders with attractive promotions.
But as in other verticals, Delta may not want or be able to view the transaction history of individual American Express customers, nor would American Express necessarily be able to view the travel history of Delta’s fliers. By collaborating in an anonymized and secure environment, the two firms can enhance their intelligence without diving into any one consumer’s history.
In healthcare, the stakes of superior data collaboration are especially high. Consider a company running trials for a specific medication. Those trials may run at different sites across borders with limits on data sharing. By unifying the data across different sites with privacy controls in place, a pharmaceutical company could empower multiple labs to run analyses on the datasets and more quickly arrive at solutions to complex problems.
Why data collaboration is hard — but getting easier
Data collaboration is challenging because companies need mechanisms to anonymize, encrypt, and normalize information. This has only been getting more urgent as regulations pile up and companies face fines for failing to comply with requirements that they give customers control over the use of their data. In addition to protecting data, organizations also need to make it easy to query so that data across multiple sources can be standardized and patterns easily detected.
While the usefulness of better data collaboration is not limited to the digital media industry, that vertical’s focus on the opportunity has spurred significant investments into better technologies and practices. As a result, data collaboration is getting more approachable, a development that will benefit businesses across all industries.