4 ways to move forward with confidence in a privacy-first world
Posted: Sat Jan 18, 2025 8:06 am
Marketers are under pressure as the economy and privacy regulations continue to change at a rapid pace. 89% of marketing decision-makers say they are under pressure from business leaders to prove ROI, according to research recently commissioned by Google and Kantar.
As a result, it’s more important than ever to find effective ways to measure how advertising is working, belarus phone number material while keeping privacy in mind. Against this backdrop, how can you feel confident in making decisions that set your business up for growth?
Artificial Intelligence (AI)-powered solutions can strengthen trust and deliver better outcomes without compromising privacy. But to get the most out of them, you need to lay the groundwork and get the essentials right . By building your first-party data strategy and establishing a privacy-first digital marketing foundation, you can unlock better measurement and effectively collaborate with AI to drive business outcomes.
If you want to deliver results today and drive sustainable growth in the future, focus on these 4 key areas.
Lay the foundation by putting privacy first
Privacy and performance are not mutually exclusive. AI-powered solutions allow you to balance them and unlock advantages for your business. That’s because AI’s predictive and analytical capabilities deliver improved ROI while filling measurement gaps created by the phasing out of third-party cookies.
The first step is to implement a first-party data strategy . To do this, you need to communicate carefully with customers when seeking their consent on how their data is or is not used. Research suggests that a proactive approach to privacy can give marketers a significant advantage with consumers.
In a recent Google-Ipsos survey, 49% of respondents said that a positive privacy experience with a second-choice brand would convince them to choose it over their preferred brand.
Once you’ve built a long-standing foundation of first-party data, you’ll be able to perform more accurate measurements and gain a clearer view of the customer journey. Let’s see it in action.
The marketing team at Calendly, an appointment scheduling automation company, knows 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.
By tagging the entire site, Calendly defined the type of user who would sign up for an account and drive adoption across a broader team. It then united the brand’s online and offline data to better understand the customer journey. Within 10 months, Calendly had a complete view of its highest-value customers and prospects.
Additionally, this site tagging implementation helped the marketing team convince executives to invest in a long-term data and measurement infrastructure. Jessica Gilmartin, CMO at Calendly, says, “By connecting Google’s AI with our product and customer data, we were able to demonstrate to our executive team the ROI of our marketing investments. It was a complete game-changer for us.”
Once you’ve made strides in collecting first-party data, AI-powered solutions like modeling, predictive segmentation, 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 responsibly managing people’s data.
Unlock insights that can help make great marketing decisions
Collecting data in a privacy-friendly way is just the first step. One natural follow-up opportunity is to use AI-powered insights to better understand what’s working well. For example, the Google Ads Insights page uses AI to help you predict recent search trends, understand changes in performance, and discover new audiences that may not fit your typical customer profile. These types of insights offer an alternative view of your customers’ characteristics and behaviors, including their engagement with your ads, so you can connect with them in more meaningful ways.
Search agency Solutions 8 used Google AI to uncover surprising insights for a food company. Solutions 8 ran a Performance Max campaign for its client, a manufacturer of non-perishable food products targeting a specific type of customer: “doomsday preppers.” Using Google Ads Insights, the agency discovered that the browsing audience far outnumbered the client’s traditional audience. With that insight, it created assets for this previously nonexistent customer segment and launched a new campaign for the browsing audience.
By combining first-party data with insights, marketers can take decisive action that improves ROI and business results.
Boost business results with Google AI
Google AI can help you achieve more accurate campaign performance by predicting future consumer behavior and constantly optimizing based on your KPIs.
For example, German online retailer Baur turned to Google Analytics 4 predictive audiences for a recent Google Ads campaign. By targeting an audience of prospective buyers, it achieved 56% sales growth and an 87% increase in conversion rate. In fact, the company estimated that only 70% of these customers could be reached using these predictive audiences in Google Ads.
You can also use audience and performance data to inform AI-powered solutions that maximize results over time. For example, Smart Bidding , uses Google AI to optimize your bids in each auction and increase conversions based on your goals. With Smart Bidding, French automotive brand Citroën saw a 16% increase in return on ad spend (ROAS) by implementing a value-based bidding strategy .
Lean in experimentation
Don’t just take our word for it. We encourage you to adopt an iterative mindset so you can operate with the greatest confidence possible. A spirit of experimentation will validate that your measurement and Google’s AI-powered solutions work in a world with fewer individual identifiers.
For example, advertisers using marketing mix models (MMMs) should use testing to calibrate them. A single experiment can be enough to effectively tweak your MMM. When Google commissioned Nielsen to use NCSolutions’ sales lift results to calibrate its mix models, revenue and ROAS attributed to YouTube increased by an average of 84% .
Previously, most of that volume was attributed to underlying variables (brand distribution and pricing), so reallocating that volume to YouTube improved overall marketing results.
By directly validating what works, you can combine your own learning with Google AI to make more accurate measurements and get results for your business.
As a result, it’s more important than ever to find effective ways to measure how advertising is working, belarus phone number material while keeping privacy in mind. Against this backdrop, how can you feel confident in making decisions that set your business up for growth?
Artificial Intelligence (AI)-powered solutions can strengthen trust and deliver better outcomes without compromising privacy. But to get the most out of them, you need to lay the groundwork and get the essentials right . By building your first-party data strategy and establishing a privacy-first digital marketing foundation, you can unlock better measurement and effectively collaborate with AI to drive business outcomes.
If you want to deliver results today and drive sustainable growth in the future, focus on these 4 key areas.
Lay the foundation by putting privacy first
Privacy and performance are not mutually exclusive. AI-powered solutions allow you to balance them and unlock advantages for your business. That’s because AI’s predictive and analytical capabilities deliver improved ROI while filling measurement gaps created by the phasing out of third-party cookies.
The first step is to implement a first-party data strategy . To do this, you need to communicate carefully with customers when seeking their consent on how their data is or is not used. Research suggests that a proactive approach to privacy can give marketers a significant advantage with consumers.
In a recent Google-Ipsos survey, 49% of respondents said that a positive privacy experience with a second-choice brand would convince them to choose it over their preferred brand.
Once you’ve built a long-standing foundation of first-party data, you’ll be able to perform more accurate measurements and gain a clearer view of the customer journey. Let’s see it in action.
The marketing team at Calendly, an appointment scheduling automation company, knows 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.
By tagging the entire site, Calendly defined the type of user who would sign up for an account and drive adoption across a broader team. It then united the brand’s online and offline data to better understand the customer journey. Within 10 months, Calendly had a complete view of its highest-value customers and prospects.
Additionally, this site tagging implementation helped the marketing team convince executives to invest in a long-term data and measurement infrastructure. Jessica Gilmartin, CMO at Calendly, says, “By connecting Google’s AI with our product and customer data, we were able to demonstrate to our executive team the ROI of our marketing investments. It was a complete game-changer for us.”
Once you’ve made strides in collecting first-party data, AI-powered solutions like modeling, predictive segmentation, 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 responsibly managing people’s data.
Unlock insights that can help make great marketing decisions
Collecting data in a privacy-friendly way is just the first step. One natural follow-up opportunity is to use AI-powered insights to better understand what’s working well. For example, the Google Ads Insights page uses AI to help you predict recent search trends, understand changes in performance, and discover new audiences that may not fit your typical customer profile. These types of insights offer an alternative view of your customers’ characteristics and behaviors, including their engagement with your ads, so you can connect with them in more meaningful ways.
Search agency Solutions 8 used Google AI to uncover surprising insights for a food company. Solutions 8 ran a Performance Max campaign for its client, a manufacturer of non-perishable food products targeting a specific type of customer: “doomsday preppers.” Using Google Ads Insights, the agency discovered that the browsing audience far outnumbered the client’s traditional audience. With that insight, it created assets for this previously nonexistent customer segment and launched a new campaign for the browsing audience.
By combining first-party data with insights, marketers can take decisive action that improves ROI and business results.
Boost business results with Google AI
Google AI can help you achieve more accurate campaign performance by predicting future consumer behavior and constantly optimizing based on your KPIs.
For example, German online retailer Baur turned to Google Analytics 4 predictive audiences for a recent Google Ads campaign. By targeting an audience of prospective buyers, it achieved 56% sales growth and an 87% increase in conversion rate. In fact, the company estimated that only 70% of these customers could be reached using these predictive audiences in Google Ads.
You can also use audience and performance data to inform AI-powered solutions that maximize results over time. For example, Smart Bidding , uses Google AI to optimize your bids in each auction and increase conversions based on your goals. With Smart Bidding, French automotive brand Citroën saw a 16% increase in return on ad spend (ROAS) by implementing a value-based bidding strategy .
Lean in experimentation
Don’t just take our word for it. We encourage you to adopt an iterative mindset so you can operate with the greatest confidence possible. A spirit of experimentation will validate that your measurement and Google’s AI-powered solutions work in a world with fewer individual identifiers.
For example, advertisers using marketing mix models (MMMs) should use testing to calibrate them. A single experiment can be enough to effectively tweak your MMM. When Google commissioned Nielsen to use NCSolutions’ sales lift results to calibrate its mix models, revenue and ROAS attributed to YouTube increased by an average of 84% .
Previously, most of that volume was attributed to underlying variables (brand distribution and pricing), so reallocating that volume to YouTube improved overall marketing results.
By directly validating what works, you can combine your own learning with Google AI to make more accurate measurements and get results for your business.