Audience data is one of the most valuable assets in today’s digital advertising landscape. But operationalizing this data to reach custom audiences across different media platforms at scale poses significant challenges for many advertisers. This issue that will only become more acute as data sets grow more sophisticated and the advertising industry moves towards a "cookieless" future, in which first-party data and consumer privacy become increasingly important.
The good news is that there are a variety of solutions on the market designed to make activating your audience data easier and more accessible than ever before. In this article, we’ll explore how to make the most of primary data to reach local audiences at scale.
You’ll also learn:
- Why activating first-party data sets will be key in the “cookieless” advertising future
- How to properly structure and utilize data as your agency’s secret sauce
- The role automation and AI play in scaling personalization efforts
- How to build a playbook that addresses your most critical advertising operational challenges
Even with Google backpedaling on cookies, first-party data activation remains critical for advertisers
Before we get into how to activate data, we need to start with a little history lesson. This is because recent shifts in advertising highlight the growing importance of first-party data for crafting effective strategies.
Back in 2023, nearly 75% of digital advertisers still depended on cookie-based targeting, with 16% of marketers saying that “the end of cookies will be ‘devastating’ to their businesses.
This continued reliance on third-party cookies is pretty staggering, especially considering that Google announced its Chrome cookie depreciation plan in 2020. The reluctance of advertisers to adapt to this significant change is understandable, though. Many advertisers argued a lack of resources and budget to explore and implement untested, cookieless solutions.
Then, in mid-2024, Google essentially said, “Just kidding,” scraped its cookie depreciation plans. This sent the advertising industry reeling once again. After nearly four years of working on targeting alternatives without third-party cookies in Chrome, was all your agency’s work for naught?
Not exactly.
Even though Google changed its stance on going cookieless, it’s still drastically changing how advertisers can target audiences. For example, Google is still pushing Privacy Sandbox, which leverages APIs instead of cookies to protect individual consumer privacy while giving advertisers targeting tools. It’s a decent workaround, but it’s an imperfect solution if your agency wants to target users in the most meaningful and impactful way possible.
Let’s also remember that Chrome doesn’t rule the web. eMarketer estimates that nearly 90% of browsers will still be cookieless in the future, even with Google’s recent reversal on cookies.
Long story short: your agency must find viable audience-targeting alternatives that don’t rely on third-party cookies.
The answer? Using first-party data sets within your advertising strategies.
The most successful agencies approach the process holistically. We’ve boiled the best practices into the following “action plan” framework.
Structuring audience data for activation: your 3-step action plan
Your audience data is a critical component of your core value proposition in an increasingly competitive (and cookieless) advertising environment. But how can you get the most value out of your audience data sets so it becomes your agency’s competitive advantage?
The way you structure, activate, and utilize data can make or break how accurately (and strategically) you can use audience data in your campaigns. These new advances in audience targeting and data-powered automation are creating a new paradigm.
To fully activate your audience data at scale, your team must navigate three key stages: data identification, data evaluation, and data segmentation. Each stage represents a critical checkpoint in the strategic journey from simply possessing data to unlocking its full potential.
Let’s take a look at these stages in detail.
1. Audit your first-party data assets for quality and structure
Identifying what sets your data apart from competitors or other industries can reveal significant competitive advantages and hidden opportunities.
Start by auditing your existing data with these questions:
- Do you know the breadth (the range of data points you've collected) and depth (the volume or instances of each data point) of your data?
- What makes your first-party data unique?
- How can your data “secret sauce” be utilized effectively in different strategies for your customers?
Data quality is equally important to evaluate. Is your data normalized and consistently formatted, or prone to manual errors? If your data is poorly formatted, it will impact your ability to scale with tools like automation and AI down the road.
Understanding the balance between deterministic data (data based on exact matches) and inferred data (which relies on analysis of various data points for identity assumption) is also crucial for evaluating your data's quality.
Once you know what you’re working with—and you’ve structured your data so it’s easier to scale—you’re ready to start extracting your data’s value.
2. Enhance your data value through clean room partnerships
With your data clean and usable, it’s time to start exploring the unique value your data brings to the table. Data clean rooms are a great place to start.
Data clean rooms are secure environments where data from different sources can be combined and analyzed without direct sharing. Data is shared in a clean room in such a way that enables collaborative analysis while maintaining privacy.
Using clean rooms can also help you enhance the depth and breadth of your data without jeopardizing its proprietary (and therefore differentiating) value. This is why clean rooms are a highly efficient way to extract meaningful insights from your data without diluting its uniqueness.
Collaborating with other parties within clean rooms can help you better understand and define what’s working with your advertising campaigns. For example, let’s say you look at your data and find a user that converted on mobile. How can you figure out what finally got them to convert when mobile is a black box? Clean rooms can help.
“Clean rooms can help you define what’s working and what’s not,” said Taren King, Director of Product for Intuit SMB Media Labs in an AW360 podcast episode on data-powered advertising strategies. “By collaborating with different entities, you can get it to do a determination. You are building your first-party data but by collaboration with another source.”
By pinpointing the most valuable elements of your data, you can more easily segment your audiences and drive better results.
3. Build modular audience segments for rapid activation
With your data structured correctly, the quickest way to activate audience data is using the “LEGO brick” segmentation strategy.
The “LEGO brick” strategy involves dividing your consumer data into super specific and modular segments (just like LEGO bricks). Each brick represents specific user behaviors or qualifiers, such as demographics, behavior, past purchases, or geography.
Once segmented, you can use these bricks to build highly nuanced audience groups for finely tuned targeting.
For example, you can use your segmentation bricks to build targeted campaigns that are as generalized as promoting cold-weather running gear to prospects in the northern part of the United States. However, your targeting can also be as nuanced as serving trail running shoe ads to users who live in rural areas and visit hiking trails or road running shoes to users in urban areas who have previously purchased reflective gear.
Granular data segmentation enhances targeting and ensures that audiences receive the most relevant information. You can take multiple “bricks” and combine them to build hyper-relevant audience segments. After all, the better you can target a user’s interests, the more likely they are to convert.
Key operational challenges in activating audience data
Good news: with these three stages complete, your data is set up so you can easily segment audiences and build custom, strategic campaigns.
But how can you possibly create all the necessary assets, write dozens (or hundreds) of different ad copy sets, and then build campaigns for so many unique audience segments? Activating audience data at scale using manual methods and workflows is a behemoth of a task—and cannot be done without automation.
Activating audience data at scale with automation and AI
By implementing automation, you can stop wasting time on repetitive, low-value activities. Instead, you can focus your time and energy on strategic objectives and run multichannel campaigns directly from the structured data and segmentation plan outlined above.
Here are four key areas where automation excels and a brief example of what this looks like in practice:
- Campaign management: Automatically pull in audience segmentation “blocks” and key messages to build and launch personalized ads at scale.
- Budget optimization: Instantly reallocate budgets across channels or campaigns based on real-time performance.
- Reporting: Mine performance data for key findings and generate reports instantly.
- Data orchestration: Streamline the process of ingesting, updating, and applying key audience insights across every platform, channel, campaign, or ad
Automation not only saves you time when building and executing localized campaigns at scale, but it also reduces the human margin of error. Working directly from your data sources ensures that everything is accurate and up-to-date. Plus, you can even build in a checks-and-balances system to ensure that anything going out the door meets third-party regulatory requirements or brand standards.
In short, automation you to scale how quickly you can execute operational tasks (like building nuanced ad copy for every audience segment) without exponentially scaling headcount or labor costs.
Thriving in a cookie-less future with first-party data activation
While Google's reversal on third-party cookies might seem like a reprieve, the reality is clear: first-party data activation isn't just a backup plan. It should be your agency's strategic imperative.
To fully integrate first-party data into your ad strategies at scale, your agency needs:
- Well-structured data that showcases your (or your customers’) unique value
- Efficient processes that eliminate manual roadblocks
- Automation solutions that scale your operations without sacrificing personalization or compliance
Start by auditing your current data assets and operational workflows using this short playbook framework. This will help you identify where you're losing time, where your data needs cleanup, and which processes are optimal for automation. Remember: your first-party data is your competitive advantage. The more efficiently you can activate it across channels and campaigns, the more value you can deliver to your clients.
The agencies that will thrive in this new era aren't the ones with the most data. They're the ones that can activate data most effectively. By combining strategic data segmentation with automation tools that eliminate operational complexity, you can deliver the personalized, local targeting that clients demand while maintaining operational efficiency as your client base grows.
Oh, and if you want to learn more about how you can build an all-encompassing advertising strategy focused around your data sets, take a listen to the AW360 podcast episode where King and I share how your agency can build a data-powered advertising strategy and lessen your reliance on third-party cookies.
