How to Spot Trends in Google Ads Data

Anirban Sen
Dec 3, 2025
19 min read

Relying on outdated Google Ads data can hurt your campaigns. Trend analysis helps you stay ahead by identifying patterns in metrics like CTR, CPC, and conversion rates. For example, while cost per lead rose only 5.13% from 2024 to 2025, recognizing this slower growth compared to 2023-2024's 25% jump can guide smarter budget decisions. Key takeaways:

Trend analysis improves performance: Spot rising audience segments, refresh underperforming ads, and allocate budgets effectively.
Seasonal and cyclical patterns matter: Use historical data to predict demand spikes or slow periods.
Segment your data: Break down performance by device, region, audience, and keyword for deeper insights.
Track key metrics: Focus on CTR, CPC, ROAS, and conversion rate to measure campaign success.
Act on trends: Prioritize impactful changes, test adjustments, and monitor results.

Google Ads Search Trends Insights

Preparing Your Data for Trend Analysis

To uncover meaningful trends in your Google Ads campaigns, you need to start by organizing your data effectively. Raw numbers, on their own, don’t tell the full story. It’s only through structuring, segmenting, and comparing your data that patterns and insights begin to emerge.

Google Ads includes tools designed to help you streamline this process. For instance, the Insights Finder feature allows you to export marketing insights in slides or sheets, making it simple to share data with your team or clients. This is especially helpful when tracking performance over time and needing quick access to historical data.

A great starting point is creating standardized report templates. These templates should include key metrics such as impressions, clicks, CTR, conversions, CPC, and ROAS, and they should be organized by dimensions relevant to your business. For example, if you’re in eCommerce, you might sort data by product category and device type. On the other hand, lead generation companies might focus on audience segments and geographic locations. Keeping your reporting consistent makes it easier to spot changes over time.

Make it a habit to export your data regularly - weekly for active campaigns and monthly for broader strategic reviews. Save these exports in a centralized location with clear naming conventions, such as "GoogleAds_Performance_Jan2025_ByDevice." This ensures that anyone on your team can easily find and reference the data they need. With an organized and regularly updated dataset, you’ll be able to benchmark performance across different time frames more effectively.

Comparing Performance Across Date Ranges

A key part of trend analysis is comparing campaign performance across various time periods. However, not all comparisons are equally useful - choosing the right time frames is critical to distinguish genuine trends from random variations.

Year-over-year (YoY) comparisons are a fundamental tool. For instance, comparing January 2025 to January 2024 accounts for seasonal patterns that might otherwise skew your analysis. This is crucial for businesses with predictable seasonal fluctuations. A 30% jump in conversion rates from December to January might seem impressive until you realize the same pattern occurred the previous year due to post-holiday shopping trends.

Take, for example, a cost-per-lead increase of just 5.13% from 2024 to 2025 (rising from $66.69 to $70.11). While this might seem minor, it’s far less dramatic than the 25% increase seen from 2023 to 2024. Without the YoY context, even small increases could lead to misleading conclusions.

Month-over-month comparisons are ideal for spotting medium-term changes and evaluating the impact of specific optimizations. For instance, if you updated your ad copy in mid-February, comparing February and March performance can help you assess the effectiveness of those changes.

For short-term insights, week-over-week analysis is invaluable. A sudden 40% drop in CTR over a week could indicate intensified competition, technical issues, or landing page problems. During promotional periods, comparing campaign performance against baseline weeks (rather than the week immediately after) can help isolate the true impact of your promotion. For example, evaluating Black Friday campaign results against a typical November week provides a clearer picture than comparing them to the post-sale lull.

When adjusting date ranges in Google Ads, keep in mind that the platform dynamically displays changes in search interest and campaign performance. The maximum value always peaks at 100, but the specific peak date can shift depending on the range you select. This means you need to analyze not only the numerical changes but also when those peaks and valleys occur.

Once you’ve established performance comparisons over time, segmenting your data will help you uncover even deeper insights.

Segmenting Data for Deeper Insights

Looking at aggregate data alone can hide key performance differences. For instance, while a campaign might average a 5% CTR overall, mobile users might be clicking at an 8% rate, while desktop users lag behind at 3%. Segmenting your data is essential to understanding where your campaigns are thriving and where they need improvement.

Start with device segmentation. Separate mobile, desktop, and tablet performance to identify areas for optimization. If your mobile CTR is lagging compared to desktop, it might be time to adjust mobile bids or improve your mobile landing page experience. This is particularly important as mobile is expected to account for 66% of total ad spending in search advertising by 2029.

Geographic segmentation can reveal regional differences that aggregate data might obscure. Use Google Ads’ geographic performance reports to analyze metrics like ROAS, CPC, and conversion rates by location - whether that’s country, region, city, or metro area. These reports index performance values, with the top-performing location set at 100, making it easy to see which areas are driving success.

Audience segmentation is another powerful tool. Compare performance across remarketing, in-market, and affinity audiences. While remarketing often delivers high conversion rates, it can also saturate quickly. In-market audiences, on the other hand, may require more detailed analysis to uncover high-performing subcategories.

Creating separate reports for each segment can help you identify patterns over time. For example, lead generation ads might perform best during business hours on desktop, while eCommerce ads excel on mobile devices during the evening. These insights can guide your strategy on when and how to reach your target audience most effectively.

It’s also important to track traditional search campaigns separately from newer formats like Performance Max, Shopping, and YouTube ads, as each has distinct performance characteristics.

Keyword and match type segmentation is critical for refining your targeting strategy. Reviewing your search term report alongside keyword match types can help you see if your keywords are capturing the right intent. For instance, you might notice that certain long-tail keywords are driving higher search volume and conversion rates, signaling growing interest in specific product features or solutions. Grouping keywords into effective and ineffective categories - and monitoring how they perform as competition and customer behavior evolve - can further fine-tune your strategy.

The key to effective segmentation is analyzing multiple dimensions simultaneously. For example, don’t just evaluate device performance on its own. Look at how it interacts with audience type and geographic location. Mobile users in one region might convert well in remarketing campaigns but struggle with cold traffic, while desktop users in another region show the opposite trend.

Google Ads’ Comparison View feature makes it easier to analyze multiple segments side by side, helping you identify trends that might be missed when reviewing data in isolation. Comparing similar ad groups can also highlight differences in CTR, revealing variations in messaging or audience targeting.

Finally, integrating Google Ads data with Google Analytics 4 (GA4) provides a fuller picture of user behavior before and after an ad click. This integration can reveal gaps - such as high CTRs but low on-site engagement - that might prompt you to rework your ad messaging or landing pages.

Monitoring Key Metrics and Patterns

Once your dataset is well-organized, the next step is zeroing in on the metrics that truly influence your campaign's success. A clear focus on these key indicators helps you separate short-term variations from genuine performance trends.

Which Metrics to Track

To effectively analyze trends, start by monitoring the metrics that directly reveal campaign performance.

Impressions are a good starting point, showing how often your ads appear in search results. While impressions alone don't guarantee success, tracking them over time can highlight whether your reach is expanding or shrinking.
Clicks provide a measure of user engagement, but their value becomes clearer when paired with the click-through rate (CTR) - the percentage of impressions that result in clicks. In 2024, the average CTR for Google Ads reached 6.42%, up from 6.11% in 2023. This rise can be attributed to new ad features and the blending of ads with organic listings. CTR benchmarks vary widely by industry; for example, arts and entertainment ads can achieve CTRs of around 13%, while legal services often hover closer to 5%.
Cost per click (CPC), which reflects the average cost of each user interaction, is another critical metric for understanding budget efficiency. In 2024, the average CPC for Google Ads was $4.66, up $0.44 from the previous year. While CPC has been steadily increasing, the growth rate slowed in 2025, with agency-wide CPCs rising less than 5% year-over-year - a sign of a stabilizing ad market.
Conversion rate measures the percentage of clicks that lead to actions like purchases or sign-ups, offering a direct view of campaign effectiveness. In 2024, the average conversion rate was 6.96%, and by 2025, 65% of industries reported improved conversion rates, despite rising costs.
Return on ad spend (ROAS) is a key profitability metric. A rising ROAS indicates that your campaigns are becoming more lucrative, potentially justifying increased investment. Conversely, a declining ROAS signals inefficiencies that may require strategic adjustments.

It's crucial to evaluate how these metrics interact. For instance, a campaign with a slightly higher CPC but significantly better conversion rates might deliver more value than one with a lower CPC but poor conversion performance.

By focusing on these metrics, you can identify patterns that distinguish meaningful trends from everyday fluctuations.

Separating Trends from Temporary Fluctuations

Collecting data is one thing; interpreting it accurately is another. The real challenge lies in distinguishing short-term noise from actionable patterns. For example, a single day of low CTR might stem from a temporary competitor promotion or a technical hiccup. However, a consistent decline over two to three weeks usually signals a deeper issue that warrants investigation.

To navigate this, establish a baseline for your campaigns. Knowing your typical performance range makes it easier to spot significant deviations. For instance, if your CTR typically stays within a predictable range, a prolonged drop outside this range could indicate a problem.

When changes occur, the context matters. A sudden dip in CTR might suggest the need for fresh ad copy, while a gradual decline over weeks could reflect shifts in audience behavior or increased competition. Similarly, if conversion rates drop while CPC rises, it’s a clear sign that something needs attention.

Analyzing performance across different timeframes can also help you identify whether a dip is temporary or part of a larger trend. For example, the deceleration in cost per lead growth - from a 25% increase in 2024 to just 5.13% in 2025 - points to a more stable market. Likewise, the slowdown in CPC inflation, from double-digit growth to under 5% year-over-year, suggests a shift in competitive dynamics that could shape your long-term strategy.

Different campaign types often exhibit unique trends. For instance, Demand Gen campaigns saw a 26% year-over-year increase in conversions per dollar spent, with investments in these campaigns more than doubling in Q2 2025 compared to the previous year. Evaluating each campaign type separately can provide a clearer picture of overall performance.

Keeping detailed historical records is one of the best ways to separate meaningful trends from background noise. With months of data, you can better understand your campaigns' natural rhythms and pinpoint when a change in metrics reflects a real shift rather than normal variability. Use these insights to guide your next steps and refine your strategy for continued success.

Identifying Seasonal and Cyclical Patterns

Analyzing structured data is a great starting point, but spotting seasonal trends takes your campaign planning to the next level. By recognizing predictable performance shifts - like holiday shopping booms, tax season spikes, or back-to-school surges - you can fine-tune your budgets and strategies. Some patterns are obvious, while others are tied to specific business cycles or industry events. Understanding these trends allows you to seize opportunities and steer clear of avoidable downturns. Historical data becomes your guide for forecasting and preparing for what’s ahead.

Using Past Data to Predict Seasonal Trends

Seasonal planning begins with a deep dive into 12-24 months of historical campaign data. This timeframe helps you distinguish recurring seasonal trends from one-off anomalies. Look at changes in conversion rates, CPC, CTR, and ROAS over time to identify consistent patterns.

For example, compare performance during the same months across different years - January 2024 versus January 2025. This isolates seasonal factors from other variables that may influence results. If ROAS consistently spikes in certain months, you’ve likely uncovered a seasonal trend.

Different business types exhibit distinct seasonal behaviors. eCommerce businesses often see sales soar during Black Friday, Cyber Monday, and the December holidays. Meanwhile, lead generation businesses may peak during fiscal quarters or busy periods unique to their industry, such as tax preparation services in March or HVAC companies during summer and fall.

The data also highlights key differences between B2B and B2C campaigns. For instance, in Q2 2025, B2B campaigns showed stronger performance overall, while B2C campaigns remained flat compared to the previous year and even dipped slightly from Q1. Recognizing these nuances is crucial for tailoring forecasts to your business model.

When analyzing historical data, segment it by geography, device type, and audience. Seasonal patterns can vary widely across regions, devices, and demographics. For example, holiday shopping might peak earlier in one area, or mobile users might behave differently than desktop users. Breaking down your data in this way uncovers opportunities to optimize for each segment during high-demand periods.

Document your findings in a spreadsheet or dashboard. Record which months consistently deliver higher conversion rates, when CPCs tend to spike due to increased competition, and which audience segments respond best during specific seasons. This reference becomes a valuable resource for planning future campaigns and setting realistic expectations. With these insights, you’ll be better equipped to adapt to seasonal changes and maximize performance.

Adapting Campaigns for Seasonal Changes

Once you’ve identified seasonal trends, the next step is to adjust your campaigns to make the most of peak periods while staying steady during slower times. This involves refining budgets, bids, creative assets, and targeting strategies.

During peak seasons, increase your budgets to capture the surge in demand. For example, if your conversion volume typically doubles in November, consider boosting your budget by 50-75% to account for both higher traffic and increased CPCs due to competition. Interestingly, agency-wide CPCs rose by less than 5% year-over-year in Q2 2025, marking a second quarter of stable growth. This makes seasonal budget planning more predictable.

Leverage automated bidding strategies like Target ROAS or Maximize Conversions to dynamically adjust bids during high-demand periods. However, keep an eye on these tools, as they can sometimes overcompensate when competition heats up.

Consider running dedicated seasonal campaigns. This allows you to test seasonal ad copy, landing pages, and promotions without interfering with your evergreen campaigns. For eCommerce, this might mean launching holiday gift guide campaigns. For lead generation, create campaigns that address time-sensitive needs, such as tax prep services in March.

Demand Gen campaigns have proven particularly effective for seasonal marketing, with a 26% year-over-year increase in conversions per dollar spent. These campaigns, which perform well on platforms like YouTube, Shorts, and Discover, are ideal for showcasing visually engaging content that captures seasonal interest.

Prepare your creative assets and landing pages well in advance - ideally 4-6 weeks before peak periods. Review past successes to guide your updates. Refresh landing pages with seasonal messaging, adjust product recommendations, and ensure your website can handle increased traffic. Don’t overlook page load speeds; slow-loading pages during high-traffic times can severely impact conversions.

For keyword strategy, consider testing broad match keywords during peak seasons. Broad match keywords are now outperforming exact match in non-brand search campaigns, driving higher average order values. This approach can help you capture search variations that more restrictive match types might miss.

During slower seasons, scale back budgets without shutting down campaigns entirely. Maintaining a baseline budget helps preserve your Quality Score and market position. Focus on evergreen campaigns that deliver steady performance year-round, and use this time to test and optimize. Experiment with new keywords, ad copy, and landing page designs that you can scale during busier times. Lower your bids by 20-30% to reduce costs while staying visible. Monitor impression share to ensure your adjustments don’t hurt your competitiveness.

Slow periods also offer opportunities to analyze competitor activity using Auction Insights reports. Understanding how competitors adapt during these times can reveal gaps in the market or strategies you can capitalize on.

Track conversion rates alongside CPC trends throughout the year. With 65% of industries seeing improved conversion rates in 2025, maintaining strong performance during high-cost, high-competition seasons is critical. Focus on spending efficiently, not just increasing volume.

Finally, set up a consistent review schedule for seasonal performance. Use custom dashboards to monitor CTR, conversion rate, and impression share daily during peak periods. Create alerts for significant deviations from historical averages - like a 20% increase in CTR compared to the same period last year. These alerts help you spot emerging trends early and adjust quickly.

Applying Trend Insights to Your Campaigns

Once your data is neatly organized and key metrics are tracked, the next step is turning those insights into actionable improvements for your campaigns. Spotting trends is just the start - the real value comes from applying those trends to refine and enhance your strategies. This involves prioritizing which trends need immediate attention, testing changes systematically, and building a repeatable process that keeps your campaigns running at their best. Without structure, trend analysis risks becoming just another data exercise that doesn’t translate into better performance.

Deciding Which Trends Need Immediate Action

Not every trend demands an immediate reaction. The challenge lies in distinguishing between urgent issues and patterns that can be observed over time. For example, a sudden 30% drop in CTR for a top-performing ad group is a red flag that needs quick action, while a gradual 5% decline might just reflect normal market fluctuations.

Start by evaluating the financial impact of the trend. For instance, a 10% improvement in ROAS (Return on Ad Spend) on a $10,000/month campaign means an extra $1,000 in revenue - clearly worth prioritizing over smaller campaigns showing similar percentage changes.

Next, consider statistical significance. A one- or two-day fluctuation often doesn’t mean much, but consistent changes over two to four weeks usually signal a real trend. Tools like Google Ads’ comparison view can help you analyze historical data to see if current performance deviates from the norm.

Business impact also plays a role. If your highest-revenue campaign shows a declining conversion rate, that’s a top priority. On the other hand, a similar trend in a smaller test campaign may not require immediate action.

Don’t forget to factor in competitive dynamics. For example, if your CTR drops but your impression share remains steady, competitors might have upped their game with better ads. In this case, a creative refresh could be the solution. Use the Auction Insights report to compare metrics like overlap rate and outranking rate. If your CTR is down but your outranking rate hasn’t changed, the problem might lie in your ad copy or landing page relevance rather than external competition.

When juggling multiple trends, create a ranking system that considers financial impact, urgency, ease of implementation, and confidence in the solution. Start with quick wins - those that require minimal effort but deliver meaningful results. For instance, pausing underperforming keywords or tweaking bids can often yield immediate benefits. Larger trends, like the need for new creative assets or landing page overhauls, will take more time but may still be worth the investment.

Look for dependencies between trends as well. For example, if both CTR is declining and CPC is rising, improving ad relevance (which affects CTR) might also help reduce costs.

Testing and Measuring Campaign Changes

To ensure your adjustments improve performance, take a hypothesis-driven approach to testing. Start by defining a clear hypothesis based on your observations. For instance: “A 15% drop in mobile CTR over the past month suggests our mobile ad copy needs updating.”

Isolate the variable you want to test by creating a separate ad group or campaign variant. This might involve updating headlines, adjusting bids, or refining targeting. Run your test for a statistically significant period - usually two to four weeks with sufficient traffic - and keep a control group unchanged for comparison.

Track the metrics that matter most to your hypothesis. For ad copy changes, focus on CTR and conversion rates. For bid adjustments, monitor CPC and ROAS. Keep a detailed log of test specifics, including dates, changes made, and any observations. After the test concludes, use Google Ads’ comparison tools to evaluate whether your changes delivered measurable improvements.

ROAS is often the most critical metric, as it reflects the actual profit generated by your ads. An increase in ROAS shows that your trend-based changes are driving real business value. Similarly, a higher conversion rate indicates that your adjustments are attracting more qualified traffic, while keeping an eye on cost-per-conversion ensures efficiency.

For eCommerce campaigns, it’s also helpful to track metrics like revenue per click and average order value. For lead generation efforts, prioritize lead quality scores and cost-per-qualified-lead instead of just raw conversion numbers.

Segment your analysis by device type, geography, and audience group to confirm that improvements benefit your most valuable customers. Integrating Google Analytics 4 can provide deeper insights into post-click behavior, such as bounce rate and time-on-page, which reveal how well your landing pages align with your ad messaging.

Only scale successful tests to broader campaigns after confirming statistical significance and a positive ROI. For example, testing broad match keywords might lead to higher average order values in non-brand search campaigns. However, always verify that these results hold true for your business before rolling out changes widely.

If you haven’t already, consider experimenting with Demand Gen campaigns. These campaigns have shown a 26% year-over-year increase in conversions per dollar spent. They are especially effective for businesses looking to maximize ROI. Use performance insights from non-search channels like Meta and connected TV to create eye-catching, high-quality assets.

Once a test proves successful, integrate the improvements into your ongoing analysis and optimization process.

Building a Consistent Trend Analysis Process

A regular trend analysis routine helps you stay ahead of performance dips and seize new opportunities. Weekly reviews should focus on high-level metrics. For example, scan your top campaigns for notable shifts in CTR, conversion rate, or ROAS - anything deviating by more than 10–15% from the previous week. Set up automated alerts in Google Ads to catch unusual changes without constant manual monitoring.

Every two weeks, dive deeper. Segment your data by device, geography, audience type, and keyword performance to identify specific areas needing attention. Review search term reports to find negative keywords and highlight top-performing ones that deserve additional budget.

Monthly, conduct a comprehensive analysis. Compare campaigns and ad groups, assess seasonal trends, and analyze the competitive landscape using Auction Insights reports. Keep a trend analysis log to document metrics that changed, possible causes, and actions taken - this will help identify long-term patterns.

Quarterly reviews are an opportunity to evaluate whether your trend-based changes have delivered the expected results. They also help you prepare for seasonal adjustments. For example, 87% of industries saw increased CPC in 2025, while 65% experienced better conversion rates. Knowing how your performance aligns with these broader trends ensures your campaigns stay competitive.

Standardize your reporting process with templates that include dashboards for key metrics, segmentation breakdowns, and sections for trend observations and action plans. Assign ownership and use tools like Google Ads’ Insights Finder to stay on top of trends.

Leverage first-party data strategies, such as Customer Match and GA4 audiences, to refine targeting and maintain a competitive edge. With the average CPC for Google Ads rising to $4.66 in 2024, efficiency has never been more critical.

Incorporate AI-driven tools for real-time optimization. Features like smart bidding can adjust campaigns automatically based on performance data, responding faster than manual changes - especially during high-traffic periods.

Finally, build incrementality testing into your strategy to measure the true impact of your Google Ads spend. This helps distinguish between conversions that would have happened anyway and those directly driven by your ads. Enhanced conversions and GA4 user-provided data can also improve attribution and measurement.

Keep an eye on industry benchmarks to set realistic expectations. For instance, arts and entertainment ads achieve the highest CTR at 13%, while legal services average only 5%. Understanding where your performance stands relative to these benchmarks helps you identify real opportunities for improvement.

Conclusion: Using Trends to Improve Campaign Performance

Spotting trends in your Google Ads data isn't just about crunching numbers - it's about uncovering the next steps to elevate your campaigns. The secret lies in consistently monitoring these trends and acting on the insights they reveal.

By sticking to a structured trend analysis routine, you can uncover actionable insights at different intervals. Weekly reviews help you catch and address immediate issues before they drain your budget. Monthly deep dives uncover patterns that guide strategic adjustments, while quarterly assessments prepare you for seasonal changes and shifts in the competitive landscape. This steady rhythm ensures your campaigns stay adaptable without overreacting to short-term fluctuations, complementing the detailed analysis methods discussed earlier.

The trick is to distinguish between everyday fluctuations and real shifts in performance. A one-day slump in metrics? Likely not a big deal. But when you see consistent changes over two to four weeks - like a declining click-through rate (CTR) on mobile, rising cost-per-click (CPC) in specific regions, or better performance from broad match keywords - that’s when it’s time to act. These patterns provide a solid foundation for meaningful optimizations.

For the best results, combine insights from multiple data sources. This broader perspective minimizes the risk of misinterpretation and leads to smarter decisions that enhance campaign performance.

Regularly monitoring trends, as outlined above, is key to maintaining a strong return on investment (ROI), even as competition heats up. Advertisers who embrace first-party data, value-based tracking, and AI-driven tools are pulling ahead of the pack. On the other hand, relying on gut instincts or sporadic checks can leave you lagging behind.

To turn your trend analysis into a competitive edge, document the trends you identify, prioritize them based on their potential impact, and test solutions. Track your results to build a knowledge base that fuels future success. This systematic approach transforms data into a powerful tool for improving campaign performance and making every advertising dollar count.

Need help refining your trend analysis or optimizing your campaigns? Check out Senwired for expert guidance tailored to your needs.

FAQs

How can I use past data to predict seasonal trends in my Google Ads campaigns?

To get a handle on seasonal trends in your Google Ads campaigns, start by digging into historical performance data from the same seasons or holidays in past years. Focus on key metrics like click-through rates (CTR), conversion rates, and

cost-per-click (CPC) to uncover patterns.

Look for consistent peaks or drops in performance and connect them to external factors like major holidays, weather changes, or events specific to your industry. Tools like Google Ads' reporting features or custom dashboards can make it easier to spot these trends and see how they play out visually.

Once you’ve identified the patterns, use that insight to tweak your bids, budgets, and ad creatives. This way, you can make the most of high-traffic periods and avoid overspending during slower times.

What are the best ways to segment Google Ads data for better insights into campaign performance?

Segmenting your Google Ads data is a smart way to uncover patterns and boost your campaign's performance. By organizing your data into categories like device type, geographic location, and

time of day, you can spot trends that matter. For instance, you might find that mobile devices bring in the most conversions or that certain regions deliver better ROI.

You can also dive deeper by looking at audience demographics - such as age, gender, and interests - or by examining ad performance metrics like click-through and conversion rates. Let’s say you analyze performance by age group and discover that a specific demographic engages more with a particular ad creative. That’s valuable information you can use to fine-tune your strategy. Regularly reviewing these segments allows you to make smarter, data-driven tweaks to your campaigns, helping you maximize results while cutting down on wasted ad spend.

How can I identify which trends in my Google Ads data need immediate attention versus those I can track over time?

To spot trends in your Google Ads data that demand quick action, keep a close eye on key performance indicators (KPIs) like click-through rate (CTR), conversion rate,

cost per conversion, and return on ad spend (ROAS). If you notice sudden, sharp changes in these numbers, it’s a clear sign that adjustments may be needed. This could mean pausing ads that aren’t performing well or shifting your budget toward campaigns that are delivering better results.

For trends that evolve over time, focus on gradual changes in audience behavior, seasonal patterns, or overall performance shifts. These can inform your long-term strategy, like updating ad creatives or experimenting with new targeting methods. By regularly reviewing your data, you can stay ahead of the curve and make smarter decisions to improve your campaign outcomes.