The majority of agencies today struggle with scaling their ad operations in the face of compounding complexities and customer demands. If you’re like most agencies, you’ve got different teams working with different tools and manually pulling in disparate data sets to make decisions.
“Even when your teams, strategies, and data are under the same roof, alignment is often missing,” said Eric Mayhew, Fluency CPO and co-founder, on an AW360 podcast about creating a data-powered advertising strategy. “When there’s no alignment, one part of the funnel can fail to support the next.”
These efficiency challenges stem from data challenges. Advertisers have been using data to drive decisions, optimizations, and campaign strategies for years. But if you want to start integrating automation and AI into your advertising, you need a data-powered approach.
Data-powered advertising means your data is complete, unified, and ready to work across every platform, channel, and AI tool you use to build campaigns. Misaligned data puts your agency at risk of overspending, not hitting customer goals, or simply failing to resonate with target audiences.
So how can we address this? Start by conducting a systematic evaluation of your advertising operations from the ground up. Understanding the intersection of data, strategies, processes, and tools is crucial to understanding what opportunities exist.
The following four-step framework can help you prepare your advertising data for AI workflows, automation, and future-proofed performance. By taking these steps, you can build an action plan to evolve your agency from being merely “data-informed” to being truly data-powered, while enjoying massive efficiency and performance gains.
1. Organize and audit all your advertising data sources
Start by taking inventory of the data you have to build your ads. Making a list of your different data sources makes it easier to see what makes your data sets unique—and, therefore, valuable—to the strategies your agency develops.
Some examples of first-party data sets include:
- Account-level data in your CRM
- Loyalty program data
- Web or app traffic
- Local store data
- Creative assets
- Inventory data
- Creative and campaign assets
- Purchase history
- Brand requirements
- Scheduling or appointment availability
- Review or testimonials
- Regional data
- Referral data
Primary data sets are reliable, targeted, and provide you with deep customer insights. You can use this valuable data to build highly personalized and effective campaigns.
You should also make a list of any third-party data sets you use (or want to use):
- Publisher data
- Local event calendars
- Weather
- Audience data
- Geolocation data
Data organization is the cornerstone of data-powered advertising. Each data point must be accessible for multiple workflows and available to everyone at your agency via a centralized location.
Once you know what data is available to you, look at how your agency collects these different data sources. For example, are you accessing publisher data through an API or logging into each system separately? Do your customers give you access to their CRM or do they send spreadsheets?
You should also note how these data sets are formatted or structured. You’ll need a way to normalize all your data moving forward, but for now, just evaluate the different formats you’re working with.
Knowing where your data lives, in what format, and how you access it is important as you evaluate solutions for data consolidation. You’ll need to ensure any vetted tools can access and synchronize data from all your different systems and sources.
This can also help you see where your data sets may be incomplete. Ask yourself whether your data includes all necessary touch points. For instance, are there clear gaps in audience information or missing variables that limit customization? Clean, comprehensive data ensures your advertising efforts are both actionable and scalable.
Ultimately, organizing and auditing your data allows you to identify patterns that make your ad strategies more impactful. Structured, well-integrated data is at the heart of moving your agency from data-informed to data-powered.
2. Optimize agency workflows: identify and eliminate inefficiencies
It’s important to take an honest look at your process inefficiencies to fully understand where your team is spending (and wasting) their time and energy every day. Building a flowchart of your end-to-end campaign execution is the first step in establishing automation-ready workflows.
Map it out: build a flowchart of your campaign launch playbook
After drawing your campaign launch flowchart, determine which campaign execution and management processes take up the most time for your teams. For instance, how long does it take to manually input campaign specs for launch? Can teams build month-end customer reports in 30 minutes or do they need multiple hours? Identifying these workflow bottlenecks can help you understand where technology can take over low-value tasks so your team can focus on high-value tasks.
(Want to see how your AdOps workflows compare to industry averages? Take our 30-second AdOps scorecard assessment.)
Pinpoint manual-process-heavy workflows and unclear protocols
Next, look at where your teams are making tradeoffs. Maybe they sacrifice targeting precision to get a campaign out the door faster. They may skip creative approval steps when refreshing hundreds of ad assets if there are too many checkpoints for launch. Understanding where teams compromise quality for quantity indicates that process improvements are needed.
In addition to process inefficiencies, consider if your agency’s wider protocols are clear, communicated, and agreed upon across the org. Any process or procedure that pulls your team away from priorities or high-value tasks should be scrutinized.
The goal of this step isn’t to draw attention to your agency’s process inefficiencies. Instead, it’s an exploration of efficiency opportunities. Your goal is to identify where data, automation, and other technologies can have the biggest impact on productivity throughout your organization—not just at the tactical level.
3. Break down tool silos: evaluate platforms, tools, and systems for interoperability
After auditing your data and processes, it’s time to look at the daily platforms, tools, and systems your teams use to do their work. Understanding how these tools share data and work together (or don't) can inform what needs to change in order build AI-ready data workflows. There are two key areas to focus on when evaluating your internal systems and platforms: technical debt and ad execution systems.
Technical debt includes outdated systems or tools that, while functioning, may be burdening your team with inefficiencies. Process inefficiencies, data silos, and misaligned workflows all stem from tools that aren’t interoperable. Your systems must be in order before you can bring in technical infrastructure to support data-powered advertising. In short, technical debt perpetuates the disconnected data issues that cost your team both time and money.
As you build this list, pay specific attention to ad execution tools. Are these tools interoperable? For example, do they enable seamless cross-channel execution, real-time insights, and easy multi-channel reporting?
AdTech bloat can be a real problem for your agency. Maybe your agency set out to be tech-enabled many years ago, but now you’re working with a conglomerate of specialized platforms that don’t talk to each other and are inhibiting multi-channel scale.
Trading in single-purpose legacy tools for interoperable advertising systems is a big leap—and not one that should be taken lightly. If you’re still on the fence, consider this: siloed tools may be really good at doing one thing, but there’s a high likelihood that those benefits are restricted to just one aspect of your overall strategy.
If your goal is to make your AdOps faster, scalable, and more strategic, you’ll need to leap at some point.
4. Build an AI governance strategy for secure, scalable AdOps
If you don’t have a formal policy on AI usage, including AI security protocols and governance, you absolutely must get one in place. If you’re still evaluating AI tools for advertising operations, look for a responsible, forward-thinking partner who can help your teams reap the benefits of using AI without compromising client data privacy or security.
According to a 2024 survey from Basis Technologies, 83% of marketers and advertisers use ChatGPT (and over 70% of respondents use generative AI tools at least once a week.) Since AI tools like ChatGPT are free, your teams may use them even if your agency doesn’t have a paid license. That’s why it’s important to ask your teams what AI tools they use and how they use them, even if your agency hasn’t officially approved any AI tools.
Once you know what AI tools are used, focus on practical applications. AI can improve a wide range of AdOps tasks, from automating bid adjustments using real-time data to optimizing creative assets. AI can also analyze audience behavior, predict campaign outcomes, and recommend additional keywords (or negative keywords) in real time based on what’s working and what’s not.
AI isn’t going away. In fact, its usage is projected to increase in the advertising sector. A whopping 90% of respondents in a Basis Technologies survey said they “believe AI will radically transform digital advertising within 3-5 years.” Establishing strong AI governance for your AdOps ensures your agency has the technological foundation to compete in a crowded market.
Watch now: data-powered advertising strategies in action
Curious about what data-powered advertising looks like? Heather Chevalley, AVP of Growth and Fluency, highlights how advertising workflows and outcomes completely change when data powers your digital advertising in this short video.
Transition from data-driven to data-powered advertising
Becoming a data-powered advertising agency doesn’t happen by accident. It’s the result of deliberate evaluation, thoughtful changes, and buy-in from your teams. If you want to build data workflows that are AI-ready, you need to start with a solid assessment of how things operate today.
Building your agency’s action plan using these four steps will lay the foundation for high-impact, scalable ad campaigns with less wasted effort. Evaluate your data opportunities, audit how current tools help (or hurt) your strategic goals, and build a plan that's purpose-built for technologies like AI and automation. These steps can ensure that your advertising operations and campaigns are ready to ride the next wave of AdOps efficiency.
Remember, the key to growth isn’t just about tools and technology; it’s about ensuring everyone at your agency works together toward a unified goal. The insights and strategies you implement today will shape the future of your agency’s long-term success.
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