Marketers are under strain as the economy and privacy regulations continue to shift at a rapid pace. Eighty-nine percent of marketing decision-makers agree that leadership is raising the pressure on them to demonstrate ROI, according to research that Google recently commissioned with Kantar.1
As a result, finding effective ways to assess how well your advertising works, while remaining privacy-conscious, is more important than ever. In this environment, how can you be confident when making decisions that set up your business for growth?
AI-powered solutions can strengthen confidence and deliver better outcomes, all in a privacy-safe way.
AI-powered solutions can strengthen confidence and deliver better outcomes, all in a privacy-safe way. But to get the most from these solutions, you need to lay the groundwork and get the essentials right. By building your first-party data strategy and setting up a privacy-first digital marketing foundation, you can unlock better measurement and effectively collaborate with AI to drive business results.
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To deliver results today and drive sustainable growth tomorrow, focus on these four key areas.
Lay the foundation while prioritizing privacy
Privacy and performance aren’t at odds. AI-powered solutions enable you to balance the two and unlock advantages for your business. This is because the predictive and analytical capabilities of AI deliver improved ROI while filling the measurement gaps created with the phaseout of third-party cookies.
The first step is to implement a first-party data strategy. This requires thoughtfully communicating with your customers when gathering consent about how you do and don’t use their data. Research suggests that a proactive approach to privacy can give marketers a significant leg up with consumers.
In a recent Google-Ipsos survey, 49% of respondents said a positive privacy experience with a second-choice brand would convince them to choose that brand over a preferred brand.2
Once you’ve built a durable foundation of first-party data, you can unlock more accurate measurement and gain a clearer view of the customer journey. Let’s take a look at this in action.
The marketing team at Calendly, a scheduling automation company, understands that a privacy-first marketing strategy is only as strong as the technologies that support it. So they built a privacy-safe measurement infrastructure that allowed them to focus on their most profitable customers.
AI-powered solutions like modeling, predictive targeting, and analytics can inform your measurement strategy.
Through sitewide tagging, Calendly defined the type of user that would sign up for an account and push for larger team adoption. Next, it joined the brand’s online and offline data to better understand the customer journey. Within 10 months, Calendly had a full-funnel view of its highest-value prospects and customers. Furthermore, this site-tagging implementation helped the marketing team convince leadership to invest in long-term data and measurement infrastructure. As Jessica Gilmartin, CMO of Calendly, shares, “by connecting Google AI to our product and customer data, we’ve been able to prove the ROI of our marketing investments to our executive team. It’s completely changed the game for us.”
Once you’ve made gains in first-party data collection, AI-powered solutions like modeling, predictive targeting, and analytics can inform your measurement strategy — even when you don’t have user-level data. This fusion of innovation and privacy will help you take your business to the next level while being responsible stewards of people’s data.
Unlock insights that can help you make great marketing decisions
Privacy-first data collection is only the first step. A natural follow-on opportunity is to use AI-powered insights to better understand what’s working well. For example, the Insights page in Google Ads uses AI to help you predict rising search trends, understand performance changes, and uncover new audiences that may not conform to your typical customer profile. Insights like these give you an alternate view of your customers’ characteristics and behaviors — including ad engagements — so you can connect with them in more meaningful ways.
By combining first-party data with insights, marketers can take decisive actions that lead to improved ROI and business outcomes.
Search agency Solutions 8 used Google AI to uncover surprising insights on behalf of a food industry client. Solutions 8 ran a Performance Max campaign for its client, a producer of shelf-stable food products marketed to a particular type of customer, namely “doomsday preppers.” Thanks to the Insights page in Google Ads, the agency soon learned that audiences with an interest in boating and sailing significantly outperformed the client’s traditional audience. With that knowledge, it created assets for this previously unrealized customer segment and started a new campaign for the sailing audience.
By combining first-party data with insights, marketers can take decisive actions that lead to improved ROI and business outcomes.
Drive business results with Google AI
Google AI can help you achieve more precise campaign performance by predicting future consumer behavior and constantly optimizing to your KPIs.
Experimentation will help you validate that your measurement is working in a world with fewer individual identifiers.
For example, German online retailer Baur turned to Google Analytics 4 predictive audiences for a recent Google Ads campaign. By targeting an audience of likely purchasers, it achieved sales growth of 56% and an increase in conversion rate of 87%. In fact, Baur calculated that 70% of these customers could only be reached using these predictive audiences in Google Ads.
You can also use audience and performance data to inform AI-based solutions that maximize results over time. Take Smart Bidding, which uses Google AI to optimize your bids in every auction and increase conversions based on your goals. Using Smart Bidding, the French automobile brand Citroën saw a 16% increase in return on ad spend (ROAS) by implementing a value-based bid strategy.
Lean into experimentation
Don’t take our word for it. We encourage you to adopt an iterative mindset so you can operate as confidently as possible. A spirit of experimentation will validate that your measurement and our AI powered solutions are working in a world with fewer individual identifiers.
For instance, advertisers who use marketing mix models (MMM) should use experiments to calibrate those models. A single experiment may be sufficient to effectively modify your MMM. When Google commissioned Nielsen to use NCSolutions’ sales-lift results to calibrate its mix models, the revenue and ROAS attributed to YouTube increased 84% on average.
The majority of that volume was previously attributed to base variables (brand distribution and pricing), thus reallocating that volume to YouTube improved marketing results overall.
With AI-powered tools at your fingertips, you can rest assured that you’re building the most effective and cost-efficient audience strategies possible.
By directly validating what’s working, you’ll be able to combine your own learnings with Google AI to enable more accurate measurement and deliver results for your business.
We’re at a critical moment in our industry. Our goal at Google is to give you confidence that your first-party data foundation, audience modeling, and measurement setup are all working hard to deliver results for you. With AI-powered tools at your fingertips, you can rest assured that you’re building the most effective and cost-efficient measurement strategies possible while respecting the privacy of your customers.
