How data collaboration opens up a world of possibilities for marketers


For several years now, the world has been evolving in an increasingly global market. As a result, many industries have become more interdependent and hyper-competitive, including retail, consumer staples, travel, and hospitality, among others.

This has led to the rise of collaborative partnerships between peers (and sometimes even rivals) in an effort to combat disruption and integrate the value chain. According to a recent report from Winterberry Research, 70% of executives surveyed in the US and UK are currently collaborating with other organizations to share first-party data or are considering starting up.

Typically, any data collaboration activity, whether intra-company or inter-company, is built on a foundation of trust. Cultivating partnerships, building trust, and gaining mutual benefit can be time consuming, and sometimes leads marketers to waste money after evil.

However, as the tech landscape evolves, so does collaboration. Next-generation technology that protects data, restricts its movement, and governs access and use eliminates many of these historic issues and enables greater scale between partnerships. When data owners can retain ownership and have clear control at all times, more possibilities become reality.

In retail, for example, e-commerce data often exists entirely separate from the data generated by in-store operations. Imagine what information merchandisers could glean if they were able to analyze transactions and other relevant data throughout the customer journey?

3 types of collaboration and their value

To broaden thinking about data collaboration across industries, it helps to categorize potential partners based on what you want to accomplish each other:

Relentless competitiveness, even across divisions, has long been a barrier to collaboration, but not anymore.

Innovative collaboration: This is a partnership between companies that may not have obvious audience overlap and association, which makes it attractive. The partnership offers a chance to unlock new information about your mutual consumers that you might not have discovered otherwise. For example, if you are an automotive brand, you might want to partner with a big box retailer to find purchasing information that will help you curate new posts.

Transactional collaboration: This type of small collaboration can help eliminate blind spots in the customer journey. From a data science perspective, this typically involves parsing fixed predefined queries on fixed taxonomies. While the potential for discovering new information may be small, the value of aggregated responses can still provide insight to improve the customer experience. One example is how restaurant groups and QSRs partner with delivery companies to spot macro trends in inventory and resource planning.

Close collaboration in partnership: It’s a trusted, peer-to-peer collaboration with a strong business case for working together. Retailers and CPG companies, for example, can partner up to build customer intelligence, reveal product affinities, and optimize a common go-to-market strategy. Over time, this strategic relationship can increase customer life value and improve long-term loyalty.

Relentless competitiveness, even across divisions, has long been a barrier to collaboration, but not anymore.

By using a secure haven for data collaboration, transaction and media data can be imported from partner networks and used to develop valuable business information to develop customer intelligence. Even in highly regulated industries, marketers can securely collaborate to further illuminate the customer journey and measure marketing activities with greater efficiency and accuracy. It also allows marketers to test less obvious partners than they might have avoided due to the time required to determine value.

Why privacy technology helps make it all possible

Leaders know that determination doesn’t always require sacrifice. Trends in technology to improve privacy and greater data utility allow global leaders to choose paths that will truly elevate the business, without compromise.

To make collaboration both easier and more secure, marketers and analysts are using a number of Privacy Enhancement Technologies (PETs) to ensure data collaboration meets strict consumer privacy standards. while enabling data analysis of key metrics, such as Return on Advertising Spend (ROAS).

PETs are an ever-evolving group of technologies that help businesses comply with data regulations and partner requirements for data use. In addition to adapting a privacy-by-design architecture built on consumer choice, transparency, and control, an organization can better orchestrate business-to-business and intra-enterprise collaboration across clouds in a transparent and privacy-friendly manner. .

Enabling collaboration on data today means working with partners who know how to maximize the value of data without compromising privacy, unlock opportunities across the enterprise, and turn the customer experience into a competitive advantage. With so many existing opportunities available to executives today, anything less should be considered unacceptable.


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