By Kristen Whitmore, VP, Consumer Intelligence & Analytics, Lotame
At the midpoint of 2024 we find ourselves at a data and analytics intersection. Never have marketers had access to so much data. Sophisticated data collection capabilities, tied to a broader ecosystem of ad tech and pub tech has created a sea of information that promises to unlock the secrets to building more sustainable businesses.
Rather than leading us to a brighter tomorrow, something appears to have gone terribly wrong.
Instead of a world where brands intrinsically know their customers and can thoughtfully anticipate their needs, they are wrestling with the vastness of the data pool and the proliferation of systems in which it is housed. This has increased the complexity of separating the signal from the noise, making it harder to extract actionable insights, causing some marketers to throw up their hands and wonder where the investment in these systems, storage, and personnel are paying off.
This is creating a new world of have and have nots.
Not so long ago, the big question was ‘how do we get this data’, and the winners could be separated from the losers based on those who could manipulate basic pub tech systems to collect and analyze enough information to understand the rudiments of their audience and its intentions enough to optimize audience targeting and offers. Now, there is a lot more data and many more systems.
However, the payoff is worth the effort.
Brands that can best manage and manipulate this complexity will unlock increasingly sophisticated insights into their customer relationships and will win the next battle for hearts, minds and relevance. Those that don’t will be left behind.
To tackle the data volume and system proliferation problem, brands desperately need effective, user-friendly analytics systems. But before they get there, marketers need to institute some sense of data uniformity and common definitions that can both be referenced back to, while also streamlining the addition of new data sources.
We recognize that there are no silver bullets here.
Though there is excitement regarding the advancements in data clouds and clean rooms, most brands’ data remains parked in silos, leading to a fragmented view of consumer activity that severely limits their ability to develop a full picture of their customers, where their budgets are going and how effective they are.
So, it’s a lot of data that lacks a common vocabulary, isn’t consistently interpreted, and exists in many different systems. No wonder there’s disillusionment.
Although successfully implemented analytics programs offer pathways to better business outcomes, many marketers find it challenging to prioritize analytics projects over initiatives that promise to drive more immediate marketing outcomes.
At the same time, even the most progressive brands struggle to implement regular and focused data-driven strategies in their marketing efforts, falling back on less sophisticated, but more familiar ways of running their campaigns.
Add in the fact that marketers, adtech companies and media outlets operate in a high-speed ecosystem of change–where policies and regulations can very quickly tilt the playing field on everything from cookie deprecation to consumer privacy and data consent–and you’ve got a challenging environment for the roots of a data-driven business culture to take hold and thrive.
Despite these challenges, we know that making the most of consumer and behavioral data is just too critical for the future of digital marketing. This is why brands must fight to overcome their own data malaise.
Finding Focus: Making Data Work for Marketers
The good news is there is a better approach and better analytics products out there, ones that can help brands overcome both data overload and widespread fragmentation. Picking the right partner whose products align with your goals, are easy and intuitive to use, backed up by a staff that can guide you on implementation and analysis are critical to decision making.
When doing your evaluation, think about the following:
- Do these tools allow me to measure and illuminate tangible results?
- Do these tools allow me to view the business through a different lens, in order to exploit a competitive advantage where one was previously hidden?
- Are these tools interoperable with the other systems in my stack, making critical data sets portable and easy for different working groups to exploit?
- Is there support available so that my team can leverage the expertise to implement, operate, and interpret the results?
It’s not enough to get it installed, however. Brands will also need champions to advocate internally to demonstrate that analytics are an integral part of improving marketing outcomes. To make this easier, try putting these best practices into place:
- Implement and maintain a data and analytics vocabulary across working groups to reduce the confusion that may exist between the different teams using the data. This way, you can ensure that everyone is talking about the same thing and in the same way. It’s amazing how often this trips companies up.
- Agree upon the sources of record for different aspects of your business and tune your analytics systems to read those signals most meaningfully against the supporting data so that there aren’t competing sets of information floating around your organization.
- Do not implement any major project or initiative without having an analytics framework in place for understanding and measuring the eventual success of the project. This will become your new truth for understanding if something has succeeded or failed, and how it can be tuned to ever-greater performance.
- Don’t make the mistake of siloing your analytics power — plug your analytics system into your broader tech stack so that analysis and optimization can take place in real time.
It’s one thing to find the right partner to help you wrangle and organize your data. To truly make it as insightful and actionable as possible, brands should look for an integrated analytics solution that plays well with others because choosing the right system, when connected to a company’s existing ad and marketing tech stack, can yield far more functionality while also reducing complexity and costs.
By rethinking data strategies and considering integrated solutions, marketers can turn their current data overload into an insight and action-oriented machine and stop wondering when the payoff will happen, because it will already have happened.
