How to analyze your paid ad performance across multiple channels

Paid advertising often feels like a juggling act. You're managing campaigns across Google Ads, Meta Ads, LinkedIn, and more—each with its own metrics, dashboards, and quirks.

At the same time, you're expected to track conversions accurately, optimize budget allocation, and make strategic decisions quickly. It's no surprise that many marketers are feeling the strain. According to the 2025 Marketing Data Report, 56% of marketers say they don't have enough time to analyze their data thoroughly.

If you're constantly toggling between spreadsheets and ad dashboards trying to get a clear picture, this guide is for you.

Key metrics for analyzing ad performance

Before diving into advanced metrics, it's important to focus on the fundamentals. These core performance indicators help you evaluate whether your ad campaigns are on track—and where to adjust.

Impressions and engagement rate

Impressions reflect how many times your ads are shown. High impressions suggest strong visibility, but that alone doesn't guarantee effectiveness.

Engagement rate typically includes actions such as likes, shares, or comments, depending on the platform, and signals how actively your audience interacts with your ads.

How to track it: Most ad platforms provide native engagement metrics, but comparing performance across channels requires a consolidated view. Use a reporting tool to bring data from all your channels (e.g., Google Ads, Meta Ads, LinkedIn) into one dashboard.

This allows you to spot discrepancies, such as low engagement on one platform, and refine creative or messaging accordingly.

Click-through rate (CTR) and conversion rate

Click-through rate measures how often users click on your ad after seeing it. A high CTR signals that your creative and message are resonating with the right audience.

Conversion rate tracks the percentage of users who take a desired action after clicking—whether it's a purchase, sign-up, or form submission. That formula is: 

Neither metric is inherently more important. It depends on your campaign goals and funnel stage:

• Top-of-funnel campaigns may focus on impressions and engagement.
• Mid-funnel efforts rely on CTR to show ad relevance.
• Bottom-funnel campaigns prioritize conversion rates.

How to track it: Most platforms report these metrics natively, but consistency is key. Define what counts as a conversion, then apply that definition across platforms like Google Ads, Meta, and LinkedIn.

Use a centralized reporting dashboard to standardize and quickly spot trends. For instance, if one channel delivers strong CTRs but low conversions, it may indicate a disconnect between your ad and landing page experience.

Return on ad spend (ROAS)

Return on ad spend measures the revenue generated for every dollar spent on advertising. It's one of the most direct indicators of campaign efficiency.

A higher ROAS typically means that your campaigns are more cost-effective. That said, focusing on quality over quantity to boost ROAS helps avoid wasting money on ineffective campaigns. 

It's always tempting to just add more budget, but that doesn't guarantee real performance gains. Instead, focus on understanding your audience, refining your ICP, and removing low-value clicks using exclusion lists. Ad spend should always bring in qualified leads—otherwise, you're paying for traffic that won't convert.

How to track it: To calculate ROAS accurately, connect ad spend from each platform (e.g., Google Ads, Meta Ads) with attributed revenue, often captured in a CRM or ecommerce system. Because conversions may happen outside your ad platform, integrating these tools is essential.

Automating these data connections through your ad revenue-tracking system allows you to view ROAS by channel in one place. This visibility makes it easier to shift budget toward the highest-performing sources without guesswork.

Ad quality score

Ad quality score—used by platforms like Google Ads—measures how relevant and useful your ad is to users. It influences your ad rank and cost-per-click (CPC), making it an important lever for efficiency.

Quality Score is calculated based on the combined performance of three components:

• Expected CTR: The likelihood of your ad being clicked.
• Ad Relevance: How well your ad matches user intent.
• Landing Page Experience: The quality and relevance of the destination page.

A high quality score can improve placement and reduce costs, but the goal isn't just a better score—it's better performance. Compare your quality metrics to campaign goals and not just industry averages to stay focused on what matters most.

How to track it: While “Quality Score” is a Google-specific term, other platforms offer similar metrics.

For example:

• Meta Ads uses Relevance Diagnostics.
• LinkedIn Ads provides a Quality Score and Relevance Score.

Unifying these metrics under a single “Ad Quality” category in your reporting tool lets you identify creative or targeting issues across platforms. If you see a drop in Google's Quality Score and Meta's Relevance Score at the same time, it may signal a broader messaging or audience alignment issue that's worth revisiting.

To help you get started, here's a Google Ads Historical Quality Score Reporting template we made.

Cost per impression/click/action (CPI, CPC, CPA)

These cost-based metrics help you assess the efficiency of your campaigns, depending on your specific goals and funnel stage:

• CPI (Cost per Impression): Useful for brand awareness and reach-focused campaigns.
• CPC (Cost per Click): Ideal for mid-funnel efforts focused on driving traffic.
• CPA (Cost per Action): Best for measuring final conversions like purchases or form submissions. Formula:

Choose the right cost metric based on what you want the campaign to achieve. Awareness campaigns prioritize CPI, traffic campaigns focus on CPC, and performance or sales campaigns hinge on CPA.

How to track it: Each ad platform reports cost data differently—Google Ads might show CPC, while Meta reports cost per link click. Standardizing your cost metrics in a centralized dashboard helps you compare performance across funnel stages and platforms.

To go deeper, group metrics by funnel stage (e.g., top-of-funnel = CPI, mid = CPC, bottom = CPA). This structure gives you a clear view of which channels are delivering the most efficient results at each step of the journey.

Advanced PPC metrics for deeper insights

Foundational metrics tell you what's happening, but advanced indicators help explain why. These deeper metrics provide context, uncover long-term trends, and support more strategic data-driven decision-making.

Tip: As your paid ad strategy expands, consider tracking performance marketing analytics metrics and other important PPC metrics for a richer understanding of your advertising impact.

Lifetime value (LTV)

Lifetime Value estimates how much revenue a customer generates over the course of their relationship with your business. It helps you understand whether your acquisition efforts are profitable in the long run.

LTV isn't just a finance metric—it's a strategic lens. If you're acquiring low-cost leads that never convert beyond one transaction, your campaigns may appear successful on the surface, but underdeliver over time.

How to track it: Accurately calculating LTV across ad platforms requires stitching together data from multiple sources—typically your ad accounts and CRM or ecommerce platform.

Start by aligning on a consistent definition (e.g., 12-month revenue per customer), then tag customers with their acquisition source using standardized UTM parameters or platform IDs. This allows you to compare long-term value by channel and invest more confidently in the ones delivering sustained revenue, not just short-term wins.

Customer acquisition cost (CAC)

Customer Acquisition Cost measures how much it costs to acquire a new customer, including both advertising spend and related sales and marketing expenses.

CAC = Total sales & marketing costs / Number of new customers

Tracking CAC alongside LTV helps ensure you're not overpaying for growth. If CAC exceeds LTV, your campaigns may be driving short-term conversions at the expense of long-term sustainability.

In some cases, it's useful to calculate Marketing CAC separately—isolating ad spend from broader overhead—to better understand how your media budget contributes to pipeline and revenue.

How to track it: Accurate CAC tracking requires aligning spend data from your ad platforms with customer acquisition numbers from your CRM or sales system.

If you run campaigns across the funnel, attribute spend accordingly—top-of-funnel ads shouldn't carry the same weight as conversion-focused efforts. A unified dashboard that combines channel spend and customer counts gives you a clear view of which campaigns are acquiring customers efficiently—and which are burning budget without results.

Share of voice (SOV)

Share of Voice (SOV) measures how visible your brand is compared to competitors within a specific channel, market, or keyword set. It's a reliable signal of brand presence and competitive pressure. Here's how to calculate it:

A rising SOV indicates growing awareness and mindshare. It also helps you assess how aggressively your competitors are advertising—and whether you need to adjust your strategy to stay competitive.

How to track it: SOV tracking varies by channel.

• Paid search: Use tools that measure impression share or competitor ad visibility.
• Social media: Monitor share of mentions, ad frequency, and engagement compared to peers.
• Display and video: Track estimated reach and frequency within your audience segments.

Bringing this data into a centralized reporting tool helps you spot gaps—for example, high visibility on Google Ads but limited presence on LinkedIn. This perspective ensures you're not overinvesting in one channel while missing opportunities in another.

Attribution window

An attribution window defines how long a conversion is credited to that ad after an interaction (like a click or view). There's no formula here; it's a predefined timeframe, like “7-day click” or “1-day view.”

Tip: Pick one attribution model and stick to it for consistency. First-click, last-click, or time decay are all valid, but if you change your model frequently or mix them up, you cannot compare apples to apples. This uniform approach also matters for your marketing attribution across different campaigns.

How to track it: Most advertising platforms or analytics solutions have their own default attribution window (e.g., seven-day click, one-day view). To track conversions accurately across multiple channels, decide on a standard attribution window that aligns with your sales cycle and apply it consistently.

For instance, if you choose a 30-day window for high-value B2B leads, configure that setting in your CRM and analytics tools to capture all conversions appropriately.

Tools and strategies for practical campaign analysis

Cross-channel campaign analysis requires more than raw data—it takes the right tools and a clear process. Whether you're a solo marketer or part of a larger team, success depends on how well your systems work together.

Look for reporting tools that:

• Integrate easily with your existing ad platforms, CRM, and analytics stack.
• Centralize data to create a single source of truth.
• Support flexible dashboards for daily monitoring and executive reporting.

Consider how they integrate with your current setup when selecting or switching between tools. Robust marketing reporting software can aggregate data from multiple advertising platforms, centralize it, and help you build consistent reporting dashboards.

If you need more detailed insights, these dashboards can feed into a data warehouse for advanced analytics.

For a practical view on extracting insights from cross-platform campaigns, check out our guide on extracting insights from your paid campaigns.

Attribution models and optimization techniques

Marketing attribution helps you decide how to credit each marketing channel or touchpoint in the customer journey. Common models include:

• Last-click: The final channel gets 100% of the credit before conversion.
• First-click: The first channel that brought users to your site gets 100% of the credit.
• Linear attribution: Credit is equally distributed across all touchpoints in a customer's journey, providing a more holistic view of the conversion path.
• Time-decay: Credit is weighted toward interactions that are closer to the conversion.
• Position-based (U-shaped): A larger share of credit is given to the first and last interactions, splitting the remainder among the middle touchpoints.
• Data-driven: Offering a sophisticated understanding of cross-channel contribution, these models dynamically consider factors such as channel interactions, timing, and customer behavior.

For instance, in Google Analytics 4 (GA4), typical paths using last-click attribution might look like this:

• Display → Social → Paid Search → Organic Search → 100% credit to organic search
• Display → Social → Paid Search → Email → 100% credit to email
• Display → Social → Paid Search → Direct → 100% credit to paid search
• Direct → 100% credit to direct traffic

Each model tells a different story. Some highlight early awareness, while others prioritize closing channels. What matters most is choosing a model that aligns with your goals—and sticking to it. Switching attribution models mid-campaign makes performance data unreliable.

How to apply it: Consistency is key. Define your model at the outset, document it, and use it across tools. This gives your team a stable foundation for optimization and goal tracking.

Budget allocation strategies and real-time data monitoring

Splitting your budget across platforms isn't just about cost—it's about return. Some channels may drive volume, others deliver higher-quality leads. Understanding that tradeoff is essential.

For example, channels like LinkedIn Ads often carry a higher cost per click but can deliver more specialized leads if you're a B2B company. Meanwhile, platforms like Meta Ads might yield more conversions, but with broader targeting.

Instead of defaulting to the cheapest option, focus on the channels that deliver qualified leads and long-term value.

How to stay agile: Real-time monitoring helps you respond quickly when performance shifts. Set up alerts for significant drops in CTR, CPC, or conversion rate—so you can pause underperforming campaigns, adjust targeting, or test new creatives without delay.

Keeping a close eye on your ad spend is also made easier with systems for automating ad spend tracking and budget pacing, so you don't have to jump between platforms continuously.

Tip: Align your budget strategy to your ideal customer profile (ICP). The most efficient spend is the one that reaches the right audience at the right moment.

Get this Ad campaign budget pacing template for Google Sheets >>

Unlocking the full potential of paid ad analysis

Analyzing paid ad performance goes beyond tracking a handful of metrics. It's about adopting a well-rounded view of your entire funnel, from initial impressions to final revenue.

By focusing on the right KPIs, you'll make data-driven decisions that propel you toward higher returns and better audience engagement.

When you're ready to go beyond basic data collection, consider a Marketing Intelligence Platform like Supermetrics. It connects your marketing data from ad platforms, CRMs, web analytics, and BI tools so you can uncover insights faster, build smarter reports, and make more informed decisions. No more patchwork spreadsheets or manual updates. Just a clear view of what's working and where to optimize.