By Chris Hogg, Chief Revenue Officer, Lotame
You’re going to be hearing about data collaboration a lot this year, and not just from trade press headlines or slick presentations at Cannes. Judging from recent acquisitions and product launches, data collaboration platforms are going mainstream and straight into the core of agency, brand, and media owner tech stacks.
Of course, in ad tech, we’ve all seen how often the “next big thing” can fizzle out into another forgotten technology. But for those burned by prior overhyped trends, worry not: data collaboration isn’t a buzzword — it’s a strategic imperative in an advertising ecosystem both powered and challenged by data.
As we navigate a landscape left in a state of constant flux by privacy regulations and the long-awaited disappearance of third-party cookies, 2024 is set to be the year of data collaboration.
So, what exactly is data collaboration, and why is it so crucial — especially now?
Data collaboration is the art of weaving together insights from diverse sources to unearth valuable patterns and drive informed decision-making.
Those who work in advertising will have encountered a variety of data collaboration in closed platforms operated by the likes of Google and Amazon, allowing brands and agencies to onboard data to be matched with their own. Data collaboration platforms operate similarly, though instead of a tech giant on the other side of the exchange, it can be whoever each party wants.
This may also sound familiar to anyone who has explored data clean rooms. These are one of the many technologies that form the basis of data collaboration, though their one-to-one nature means they are only suitable for massive data sets, otherwise, match rates are too low to be useful.
However, connect to the wider market of data and universal identifiers, then bring in AI-driven modelling, and even modest data sets can be leveraged for valuable insights. With the right partnerships, a vague “auto buyer” target segment can be filled in with granular details, becoming, for example, “women over 35 with families and a dog living in the suburbs” — in other words, the perfect SUV buyer.
At a time when the fundamentals of audience intelligence and targeting are being upturned, data collaboration is a beacon of hope. It empowers organisations to enrich their first and second-party data, wean off their reliance on third-party cookies, and wean off of their dependence on third-party cookies in a privacy-conscious environment.
The rise of data collaboration is fuelled by several key trends:
- The erosion of device signals diminishing advertisers’ targeting capabilities and publisher ad revenues
- Increasing dominance of walled gardens and retail media platforms rich in exclusive first-party data
- Regulatory shifts emphasising privacy protection and data leakage prevention
But how does data collaboration address these challenges?
Whereas initial collaborative technologies favoured those with the most resources, brands of all sizes stand to gain from data collaboration platforms that simplify onboarding and data transformation. The role of machine learning and predictive modeling cannot be understated here, both in accelerating data processing speed and surfacing the patterns that hide behind the data.
Without having to have teams of data scientists on board, brands can grasp how their products resonate with consumers, benchmark campaign performance, and enrich audience profiles with previously inaccessible details. Due to the sophistication of the technology required to run them, data collaboration platforms could not exist at any point but today — which is perfect timing, given the challenges the industry faces at this time.
Data collaboration also opens avenues for data monetisation, allowing organisations to license their first-party data for analytics and insights. Anyone with a pool of consenting users or browser/device data might be sitting on hidden data riches, just waiting to be leveraged through a strategic partnership.
Moreover, data collaboration fosters deeper partnerships between the buy and sell side, facilitating targeted customer acquisition and encouraging media investment across a more diverse array of properties than just the walled gardens. This will be a particular boon to open web publishers which saw the value of their audiences erode during the cookie era.
The benefits extend beyond brands and publishers, too. Data suppliers can tap into new revenue streams and witness increased media spend, while consumers experience more successful advertising campaigns, more engaging communications, and more user-focused products and services.
Finally, data collaboration will form the connective tissue between the various data sets and technologies that promise to keep ad spend and revenues flowing in the post-cookie, privacy-first web. The future of advertising will not be concentrated on a single solution but a portfolio of them united with data collaboration platforms that enhance behavioural and contextual approaches alike.
To survive these stormy seas, we need to break down the walls both within and between the many component players in the digital advertising ecosystem, embracing a “rising tide lifts all boats” mindset. Data collaboration is that tide, and by all pitching in, we can establish a more ethical, diverse, and resilient industry.
