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What is data collaboration?

  • Graham Tricker
  • 4 min read

Big data is here, it’s just unevenly distributed. In the third post in our series about data collaboration, Graham Tricker explains why data collaboration solves the problem of the gaps in your understanding of your customers.

The world currently generates about 328.77 billion Gigabytes of data a day. That’s enough to fill 218 billion Blu-ray discs. But in the middle of this astonishing glut, most businesses still don’t have access to the data they need to build a comprehensive understanding of their customers.

The problem is that many businesses still have customer data warehoused in complex infrastructures, so stakeholders are unable to access the data they need. Even when you can access your own customer data, it only provides part of the picture. No-one has the complete customer journey captured. And the problem is about to get worse. Privacy concerns will soon spell the end of the third-party cookie. This technology allows internet users to be tracked as they browse, and has been marketers’ main source of consumer data for the past 25 years. It also evolved into a less-than-optimal way to share customer data between platforms, for example by sending cookies to media platforms, or sharing third-party datasets on cookies, or by brands deploying pixels on other brands’ websites. 

Fortunately, there is a solution: data collaboration.

Data collaboration

Data collaboration simply means bringing together data from a number of sources so that all contributors benefit. 

For brands, there are four main types of data collaboration:

  • Collaboration across the enterprise. This aims to break down silos and democratise data within the business, so that everyone has access to the data they need to do their job.
  • Collaboration with peers (peer-2-peer). Complementary brands can pool resources to deliver a better customer experience. The classic examples are a CPG brand and a retailer, or a hotel chain and an airline.
  • Collaboration with agencies. Safe, secure access to the brand’s data enables agencies to deliver a better experience to the end customer across any media channel. The reverse allows brands a deeper, more detailed understanding of the performance of those channels.
  • Collaboration with data providers. This could involve suppliers of third-party demographic or psychographic data, such as Experian. Or owners of purchase data, such as Mastercard.

Data haves and have-nots

Some organisations are data-poor. For brands that sell through third parties or retail channels, the benefit of these collaborations is a more complete view of their customers. This then drives better insights and improves acquisition. For example, we helped Jaguar Land Rover build a collaboration with price comparison site Carwow. The site enables car buyers to configure their ideal vehicle, book a test drive, and get a price. This means Carwow knows when a potential JLR customer is in-market, even if they’re looking at a rival brand. This one piece of information means JLR can improve its marketing by only targeting people who are actively looking to buy a new car.

Meanwhile, data collaboration gives data-rich businesses more opportunities to monetise their data. In the case of retailers it has created the phenomenon of retail media. For example, we’re working with the Co-op, the UK’s second-most visited grocer. They’re using our data collaboration platform to give brands access to their first-party member data in a privacy-centric way. That means the brands can improve the targeting of their digital media campaigns across the Co-op’s online properties, and on the open web. And it creates a new revenue stream for the Co-op.

And these collaborations aren’t only transactional. They can also deepen partnerships and deliver strategic benefits. For example, data collaboration between a retailer and a CPG brand means both can develop a better understanding of their mutual customers. That means the retailer is able to sell more of the brand’s products; a win-win. A great example of this is the partnership we’ve supported between Italian pasta giant Barilla and Carrefour to promote the brand’s Gocciole range of cookies. 

Beyond that, greater trust between the two parties encourages greater experimentation, since success will benefit both. We’ve seen this in our work with Boots in particular over the past few years. Allowing brands access to Advantage Card data – via data collaboration – to inform their ad targeting on Boots’ online properties was a business success. It also led to the formation of Boots Media Group and the expansion of improved targeting to the open web.

Doing more with less

The explosion of digital channels and the continued growth of ecommerce are increasing the scope of marketing. At the same time, costs are increasing and disposable income is being squeezed, with  a knock-on effect on brands’ marketing budgets. Gartner reports marketing budgets have fallen from 11% to 9.1% as a percentage of total revenue over the last four years. In other words, CMOs are being asked to deliver more with less. 

This is driving big swings in spend away from unaddressable, unmeasurable media channels. Instead, it’s going into those that allow brands to better utilise their customer data to understand which levers to pull to drive growth.This is where data collaboration is key. In my next post, I’ll take a deeper dive into these value unlocks, and at how brands like British Gas, LookFantastic and Barilla have maximised growth through data collaboration.