Artificial intelligence has quickly become a competitive advantage for marketers. But adopting AI tools alone doesn’t guarantee results. The true differentiator lies in the quality of the data that powers those systems.

First-party data information collected directly from your customers has always been valuable. In today’s AI-first landscape, it has become essential. With the right data foundation, businesses can unlock predictive insights and tailored strategies that directly improve ROI. Yet, to fully realize this potential, organizations must overcome the long-standing issue of siloed and underutilized data.

Defining Data Strength

Many companies possess large volumes of customer data but struggle to apply it effectively because it lives in disconnected systems. Data strength is the concept of unifying and enriching these assets, creating a single, accurate view of the customer.

Strong data reveals two things:

• Where to invest: Which data sources and signals provide the most value.

• How ready you are: Your ability to connect disparate systems and activate them through AI.

When businesses achieve data strength, they enable AI to operate with a complete picture, leading to smarter decisions and stronger returns.

Four Ways Leading Advertisers Build Data Strength

1. Securely connect all your data sources

The first step to building data strength is eliminating silos. Data scattered across sales, website analytics, CRM systems, and advertising platforms prevents AI from seeing the full picture. Centralizing these sources into one ecosystem ensures consistency and accuracy.

Platforms like Google Data Manager simplify this process by offering direct integrations with major systems and APIs. Advertisers can streamline the movement of information, reduce troubleshooting, and improve reliability. Another advantage is the ability to convert third-party tags into first-party ones. For example, solutions such as Google Tag Gateway allow advertisers to capture stronger, privacy-safe signals without having to retag entire websites. In fact, this type of setup can result in an average 11% lift in usable marketing signals.

2. Focus on improving data quality and variety

Once your data pipelines are connected, the next priority is ensuring that the signals being captured are rich and reliable. AI systems thrive on diverse, high-quality inputs, which enable them to deliver more accurate recommendations and insights.

Top advertisers expand their signal mix by incorporating:

• Advertising signals: Campaign-level interactions such as impressions, clicks, and engagement trends. These reveal how audiences respond to specific creative or placements.
  

• Customer signals: First-party details that people choose to share, like email addresses or phone numbers. These identifiers help map customer behavior across multiple devices.
  

• Transactional signals: Purchase values, order histories, and other key actions that help assess the real impact of campaigns. They also prevent duplicate conversion counting.
  

• Behavioral signals: On-site activities such as browsing, content engagement, or product interactions. These insights deepen understanding of the customer journey.

3. Activate your data through AI platforms

With high-quality, connected data in place, the next step is activation. This is where data strength translates into tangible business value. AI-driven advertising platforms, such as Google Ads, can use your signals as inputs to power advanced optimization.

Key applications include:

• Audience creation and expansion: Identifying your highest-value audience segments and building similar (lookalike) groups to expand reach.
  

• AI-powered bidding: Leveraging real-time data to automatically adjust bids for maximum impact, uncovering opportunities that human optimization might miss.
  

• In-channel optimization: Using advanced attribution to understand what actions or touchpoints truly drive sales within each channel. This allows for precise allocation of the budget.

4. Demonstrate ROI with modern measurement

The final step is proving the value your data delivers. Relying solely on outdated last-click attribution no longer provides the full picture. To understand the true impact of your advertising, businesses must adopt more advanced measurement practices.

Some of the most effective include:

• Cross-channel attribution: Goes beyond clicks to evaluate how different touchpoints—search, display, social, email—work together in driving conversions.
  

• Incrementality testing: Uses controlled experiments (such as geo-based or conversion lift tests) to determine whether ads directly caused an outcome rather than simply appearing in the customer journey.
  

• Marketing mix modeling (MMM): Applies statistical analysis to correlate marketing spend with sales, helping businesses optimize budget allocation across channels and assess the overall contribution of each media type.

These modern measurement techniques provide a holistic view of advertising effectiveness, allowing marketers to demonstrate clear ROI and make smarter investment decisions.

From Stronger Data to Improved ROI

In today’s AI-driven marketing landscape, building data strength is no longer optional—it’s essential. Strong first-party data empowers businesses to deepen customer relationships, optimize campaigns with precision, and maximize the lifetime value of their audiences.

AI fueled by robust, connected signals can transform bidding strategies, increase efficiency, and ensure that budgets are deployed where they matter most. For forward-looking leaders, strengthening data is not just about improving current performance; it is about laying the groundwork for long-term, AI-powered growth.

Organizations that prioritize this today will be the ones positioned to thrive tomorrow.