Making Informed Decisions With Ecommerce Performance Reports

Do you use key data to make strategic decisions? Ask yourself these 5 questions. In my 6+ years of experience, I've helped e-commerce brands become more data-driven and better manage their finances. Through all my projects, similar patterns emerged. Those patterns led to the birth of the "Optimizator" framework. For simplicity, it can be reduced to 5 main questions (in order): 1. Do you trust your numbers? 2. Do you understand your numbers? 3. Do you test your numbers? 4. Do you action your numbers? 5. Do you monitor your numbers? Every question directly influences the next one. Every next question renders the previous one useful. They are all interdependent. Here's what each of them means: TRUSTING NUMBERS Trust = ensuring accuracy, relevancy, and timeliness If your numbers lack all, you can't trust them. Without trust, your understanding of the numbers will suffer. SOLUTION: Implement proper accounting and data management procedures. UNDERSTANDING NUMBERS Understanding = looking underneath the surface If you don't utilize and optimize systems to help interpret your numbers, you will be stuck with surface-level insights. Without understanding, your testing and action will suffer. SOLUTION: Implement a proper "system stack" that delivers deep insights on demand. TESTING NUMBERS Testing = evaluating probable outcomes If you don't test your numbers in various cases, you expose yourself to downside risk. Without testing, your action will suffer. There are no certainties - only probabilities. SOLUTION: Implement financial modeling, forecasting, and scenario analysis to evaluate the range of values for a target variable. ACTIONING NUMBERS Action = laying a roadmap for execution If you don't act on the numbers and data, you risk acting irrationally and underutilizing your main asset - data. Without action, your monitoring will suffer. SOLUTION: Implement frameworks to act on critical insights. MONITORING NUMBERS Monitor = evaluating the rate of change If you don't track the outcomes of your decisions, you won't maximize the ROI of your actions. Without monitoring, all previous efforts are rendered useless. SOLUTION: Implement reporting that paints the "before and after" picture. --- Don't overcomplicate finance management. Answer the 5 questions above to know which area is currently lacking. P.S. if you don't know how to approach those 5 questions, DM me and I will help you assess your current state. #ecommerce #finance

Here's the exact framework we use to scale top e-commerce brands with data-driven creative strategy. (And why it works every time) This framework will help you analyze your creative metrics from a behavioral standpoint and turn them into insights that scale profitability. Step 1: Shift From Guesswork to Data-Driven Decisions Make your ad decisions based on behavioral insights, not assumptions. Here’s how: Primary Metrics (Performance): These tell you IF your creative works—think purchases, CPA, and spend. Secondary Metrics (Storytelling): These explain WHY your creative= works—look at things like Scroll Stop Rate, Hold Rate, and Outbound CTR. Most brands stop at CPA and purchases—but without knowing why an ad works, you can’t repeat success. Step 2: Focus on Creative Optimization Stop tweaking creatives based on random guesses. Instead, create a Creative Optimization Feedback Loop that feeds data back into your creative process. This will help you: Replicate Winning Elements: Identify which creative elements work and use them across campaigns. Cut Waste: Invest more in creatives that drive the best results and avoid wasting budget on underperformers. Improve with Precision: Use insights from secondary metrics like Scroll Stop Rate and Hold Rate to refine weak spots in your creatives. Step 3: Break Down Your Metrics to Understand Consumer Behavior Primary Metrics (Performance): They tell you how much you’re spending vs. what you’re earning. But secondary metrics show the why. For example, low Hold Rates signal that your ad loses attention fast. Is your pacing off? Are the visuals weak? Step 4: Leverage Age, Gender, and Placement Breakdowns Discover Hidden Opportunities: Break down performance by age and gender to see which segments are truly engaging. Personalize Your Approach: Adjust messaging and visuals based on these insights to make your creatives resonate more with the right audience. Optimize for Specific Segments: Not all audiences respond the same way—ensure your creative is tailored to your highest-performing segments. Step 5: The Power of Tracking Key Metrics: Scroll Stop Rate (How well your ad grabs attention) Hold Rate (How well your ad keeps the audience’s attention) Outbound CTR (How many click through to your landing page) By focusing on metrics that matter, you’ll quickly spot issues before they impact your budget. Final Thoughts: Systematic Analysis > Guesswork. Data-driven creative wins. The best brands don't rely on gut feelings—they analyze, iterate, and scale. Here’s your action plan: 1. Set up dashboards to monitor both performance and behavioural metrics. 2. Regularly track and review creative performance. 3. Use this data to refine, test, and improve. 4. Scale with a creative library of proven success. ------ 👉 What’s the biggest challenge you face when analyzing creative performance?

Making Smart Data-Driven Decisions, Faster At Amazon, we pride ourselves on being data-driven while maintaining a bias for action. As leaders, we're accountable for making sound decisions quickly. These dual imperatives—being right and moving fast—create a healthy tension that drives our business forward. Here's a common scenario: You're reviewing two options where A (new feature) shows 93.2432% on a business metric and B (the current feature) shows 92.7835%. The decision seems clear—go with A and move forward quickly, right? Not so fast. You always have to look beyond averages. Digging deeper you can find that these precise-looking numbers come from just 69/74 and 90/97 observations. When properly represented with confidence intervals: - 93.2% ± 8.1% (n=74) - 92.8% ± 6.9% (n=97) The reality? These options perform essentially the same. The apparent difference is statistical noise, not a true business advantage. This matters because false precision leads to: 1. Wasted resources chasing illusory improvements 2. Slowed innovation as teams fixate on insignificant differences 3. Lost credibility when "improvements" fail to materialize at scale To justify reporting 93.2432% (four decimal places), you'd need approximately 100 million observations! For context: - 1 decimal place: ~1,000 samples - 2 decimal places: ~100,000 samples - 3 decimal places: ~10 million samples - 4 decimal places: ~100 million samples In my experience, the highest-performing teams understand data limitations. They dive deep into the numbers, insist on proper statistical rigor, and still maintain a bias for action by: 1. Including sample sizes with every metric 2. Showing confidence intervals alongside point estimates 3. Making decisions appropriate to their certainty level When confidence intervals overlap, effective leaders either: - Declare the options equivalent and move forward - Quickly gather more data if the decision is critical - Look beyond primary metrics for differentiation True data-driven decision making isn't about precision—it's about understanding what your data can actually support while maintaining velocity. How does your organization handle uncertainty in metrics while still moving quickly? What practices have you found most effective?

🔍 Amazon PPC isn't just about launching campaigns, it's about knowing when to spend and when to hold back. By leveraging time-based heatmaps, I recently analyzed ad performance across days and hourly windows. Instead of treating the entire day as one block, I broke it down by the hour, and the results were eye-opening. 🚀 Here’s what optimizing around peak conversion hours unlocked: Ad Spend: $26,088.10 → $23,503.14 Sales Revenue: $126,537.78 → $174,617.37 Total Orders: 437 → 816 ACoS: 20.65% → 13.46% Yes, less spending, more sales, and nearly double the orders. All by adjusting bids and budgets to match when customers are converting. This isn’t just a report, it’s a decision-making tool. You gain visibility into when to scale, when to pause, and where your ROI is strongest. No guesswork. Just data-backed decisions. If you're managing Amazon ads and not factoring in day + time analytics, you’re likely leaving efficiency (and profit) on the table. 📩 Curious what a heatmap would look like for your account? Feel free to DM, always open to audit and share insights that drive results. #AmazonPPC #EcommerceStrategy #AdOptimization #PerformanceMarketing #ACoS #AmazonFBA #PPCInsights #AmazonSellers #DigitalMarketing