I recently had the opportunity to join a panel at Google's Rethink ROI event, where the conversation centered on how brands are driving measurable results by investing in their data foundations. It's a topic I've spent more than a decade working on at Adswerve, and one that's becoming impossible for marketing leaders to ignore.
Data strength has always been built into the core of how we work at Adswerve. Whether a client comes to us for media activation, analytics, or measurement, the underpinning is always the same: a strong data model that everything else grows from.
The way we think about it, data is the prerequisite layer. It's what gives you the foundation to build smarter customer experiences, power those experiences with AI-driven intelligence, and measure outcomes with real confidence. You can't do any of those things well if the inputs aren't solid. Before you can optimize a bidding strategy or personalize a campaign or build a media mix model, the data has to be right.
And we're seeing that investment pay off across our client base. Clients who prioritize data strength consistently see stronger performance, and that impact is on par with what media and creative optimization deliver. Data isn't a support function anymore. It's a top-tier performance driver, and it’s critical to have a strong data foundation in place in order to stay ahead of the competition.
If you've been in marketing long enough, you've hit the data bottleneck. I've spent years working hands-on with Adswerve clients, and I can tell you that these bottlenecks show up in different forms at every size organization, even the organizations that work well cross-functionally!
But here's what we've learned works: start with a proof of concept. Get a win. Then take that win to your stakeholders as proof for why investing in data strength is critical to the business’s success.
The good news is you don't need to solve everything at once. If there's an out-of-the-box solution available, use it as your starting block. Google provides several that are designed for exactly this kind of quick proof point:
Once you've got those proof points in hand, you can build up to bigger initiatives. For instance, you can:
Organizations that are preparing their marketing data for AI activation are finding that the same data foundation powers both better campaigns and smarter automation. And for teams working with partner data, privacy-safe environments like data clean rooms offer a way to collaborate without exposing sensitive customer information.
Each step builds credibility and breaks through the gridlock a little more. The key is not to wait for perfect conditions. Start with what's in your control, prove the value, then use that momentum to tackle the harder structural changes.
I strongly believe that the fastest way to break down internal silos is to demonstrate wins. Teams move faster and more decisively when they can see the outcome in their own numbers.
Our work with Betterment is a clear example of the success a business can achieve when data strength is treated as a key capability. We started with the data foundation, bringing Betterment's marketing data together with their broader CRM data. That connected view meant we could more easily find valuable customers through richer profiles, sharper audience segments, and real targeting precision.
Those clean, connected inputs enabled us to build intelligence on top of the foundation, engineering a custom bidding script to optimize their media buying. The impact showed up across the board: a 10% reduction in CPA, 1,700 additional clicks, and a 40% improvement in impressions.
Betterment had undisputed proof that investing in data strength works, and their team had the wind in their sails. That kind of visible success is why data access for marketing teams should be a given, rather than a negotiation. With these types of business results readily apparent, data access becomes a company priority because there's genuine business urgency behind the request.
A strong data foundation also makes full-funnel, causal measurement possible.
At Adswerve, we're doing this work through marketing mix modeling (MMM), including with Google's Meridian, which we've been building on as an early certified partner. Marketing mix modeling becomes especially critical for channels that are harder to measure through traditional attribution.
For example, an app-based business we worked with ran a holdout test reallocating budget from linear TV into YouTube using Meridian. With that test, they were able to prove that shifting budget into YouTube increased app downloads while lowering acquisition costs.
With concrete measurement in hand, you can move past internal debate in boardroom conversations and present clear revenue impact to build a solid, finance-approved business case. Ultimately, showing that direct connection to revenue makes investing in your data foundation an easy decision.
Adswerve has been named a North American partner for Google's data strength programs, including GIP and DSPP, because this is the work we've been building toward for more than a decade. If your team is ready to move up the data maturity curve, we'd love to talk about where you are and what's possible from there.