Looking to calculate your return on ad spend? It takes a lot of work, doesn’t it? According to a 2024 Wakefield survey of 500 U.S. executives, measuring the impact of marketing activities requires 28 data sources on average, roughly split between internal and external partners. For a global CPG brand or retailer, it’s not hard to imagine that number ballooning many times higher.
Bringing all this data together, amid the tectonic shifts of cookie deprecation and consumer privacy laws, can seem like a Herculean challenge. The vast majority (90%) of surveyed leaders note they’ve invested heavily in data collection, but not enough in measurement and analytics to fully leverage that data.
Fortunately, brands are joining forces to build a more holistic view of ad measurement, working together to get to insights faster, with less work. Let’s take a closer look.
Why ROAS has become mission-critical for brands
With the growth-at-all-costs era firmly behind us, you’re likely facing increased pressure to optimize spend. CEOs have cut budgets as much as 10-20% in the last two years, applying greater scrutiny to metrics like return on ad spend (ROAS). The holy grail of marketing measurement, ROAS approximates the sales generated for every dollar of advertising.
But, ROAS’ simple dollar figure obscures a more complex equation. Downstream and cross-screen measurements that inform ROAS rely on calculations from one or many data sources, and existing tools and processes are insufficient.
Nearly all (97%) marketers report challenges in using data they’ve collected to measure marketing impact, according to the recent Wakefield survey. 86% can’t fully measure the impact of campaigns in driving online and in-store conversions. Top areas of concern include:
- Marketing attribution (52%)
- Media delivery (49%)
- Audience engagement (41%)
Challenges of data fragmentation in ROAS analysis
When it comes to measuring ROAS or any marketing metric, there are three major data gaps that brands face – whether you’re a fast-scaling startup or a global brand adapting to customer trends.
Siloed datasets
While there’s never been so much data available to marketers, it’s also never been as fragmented as it is today. Your first-party customer data lives across multiple internal systems (e.g., sales, marketing, customer success), while third-party ad performance insights sit behind hard-to-reach walled gardens and streaming distribution partners, from Meta and Google to Disney and Prime Video.
To make sure ROAS accounts for every ad exposure and conversion, you need to bring these diverse datasets together in a unified view.
Highly manual workflows
Any marketing leader knows the laborious process involved in putting together even a single report. Traditional ways of measuring ROAS have been highly manual, with marketing teams piecing together PowerPoint slides from one CTV provider, SQL queries from a retail network, and log-in dashboard data for a social platform.
Instead, you want to bring together all ad reporting into a continuously refreshed dashboard, so any marketing or business user can get insights faster, from the data you’ve already collected.
Limited technical resources
Most marketing leaders wish they had twice as many data scientists and engineers to help drive data collaboration – the act of using technology to connect and analyze data from various internal and external sources to unlock combined insights.
According to Wakefield, nearly half (49%) of marketing leaders don’t have enough internal staff to develop a strong data collaboration solution. Even with a sizable team, 41% say it would simply take too long to develop a solution in-house. The right outside tech partner can streamline connections across these diverse datasets and empower even a small group of data scientists to build models and self-serve analytics for more business users.
Achieving ROAS clarity with data collaboration solutions
Despite the challenges of fragmentation, today’s data-driven marketers are pushing ahead. Most executives (76%) have already prioritized better campaign measurement, and nearly all (99%) feel their organization can accomplish more with better data collaboration, according to Wakefield. They’re also walking the walk: the vast majority (93%) plan to leverage third-party data collaboration technology by 2025.
To fuel the deepest possible customer insights, three in four marketers specifically plan to use data clean rooms – privacy-safe, strictly controlled environments that help advertisers and publishers compare datasets, while obscuring any personally identifiable information (PII).
3 ways to overcome data gaps and prove ROAS
Here are three key ways clean room – powered data collaboration can help address your data gaps.
1. Reduce cross-channel media waste
By matching first-, second-, and third-party data with retail and media partners, you can build a more holistic view of your audiences, each campaign’s reach and impressions, and cross-channel conversions.
Modern clean rooms are interoperable with major walled gardens, CTV streamers, retail networks, and other data owners. By connecting the dots to understand your full customer journey, you can optimize ad placements toward qualified audiences and identify high-engagement channels where you should double down.
2. Automate toward faster ROAS growth
Execution is more than half the battle with any analytics program. Rather than normalize and merge your datasets one-by-one, advanced clean room solutions simplify connections across all major clouds and walled gardens, and are continuously refreshed with the latest data from each source. Built-in automations around privacy, governance, scheduling, and portability can streamline implementation, reduce the time to value from any given data investment, and foster a quicker transition to data-driven decision-making.
3. Democratize access to ad insights
When bringing more data together, you also want to empower teams to arrive at their own insights. Look for clean room solutions embedded with privacy-enhancing technologies, such as various modes of encryption and advanced permissioning, which enable more business users to safely access these environments.
The rise of generative AI can power even more advanced use cases, helping non-technical marketers proactively discover the types of insights that can be derived from a given dataset. AI can also answer questions, such as which partner has the highest overlap for a specific product’s retargeting segment.
Preparing for the next chapter in ROAS measurement
Marketers are moving quickly to find solutions for a post-cookie, privacy-first advertising landscape. The old ways of measuring ROAS won’t cut it, and as the last vestiges of the cookie era expire later this year, many models will become obsolete.
By taking a new, collaborative approach to data and insights, your marketing team can write its own future. Privacy-forward technology is making it easier to share data, internally and externally, so that everyone can unlock more accurate and granular insights to build new brand and business value.
So, what are you waiting for? Check out the full Wakefield report for more findings and industry benchmarks, and if you’re looking to take the next step, our advertiser action plan can help.
