Conversion Path Analysis

🔍 𝐏𝐚𝐭𝐡 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: 𝐔𝐧𝐜𝐨𝐯𝐞𝐫𝐢𝐧𝐠 𝐊𝐞𝐲 𝐔𝐬𝐞𝐫 𝐏𝐚𝐭𝐡𝐬 𝐰𝐢𝐭𝐡 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐐𝐮𝐞𝐫𝐢𝐞𝐬 𝐢𝐧 𝐁𝐢𝐠𝐐𝐮𝐞𝐫𝐲 As Digital Marketers and Analysts, understanding user interactions on your website or app is essential for optimizing the customer journey and boosting conversions. Path Analysis helps visualize user movement, revealing friction points and opportunities to enhance the experience. With sequence queries in BigQuery, you can analyze user paths to uncover bottlenecks and make data-driven decisions for conversion path optimization. By understanding which paths lead to conversions and which paths lead to drop-offs, you can: ✔️ 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗛𝗶𝗴𝗵-𝗖𝗼𝗻𝘃𝗲𝗿𝘁𝗶𝗻𝗴 𝗣𝗮𝘁𝗵𝘀: Discover the sequences that most often lead to a successful conversion. ✔️ 𝗦𝗽𝗼𝘁 𝗕𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸𝘀: Identify stages where users drop off frequently, indicating friction or confusion in the flow. ✔️ 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗣𝗮𝘁𝗵𝘀: By analyzing these paths, you can optimize the user experience, making it easier for users to complete their desired actions. 🧠 𝗛𝗼𝘄 𝗦𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝗤𝘂𝗲𝗿𝗶𝗲𝘀 𝗛𝗲𝗹𝗽 With SQL sequence queries in BigQuery, you can analyze users' paths through events and stages in a more granular way. This enables you to pinpoint the exact series of interactions that occur before conversion (or drop-off). 📊 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: 𝗨𝘀𝗶𝗻𝗴 𝗦𝗤𝗟 𝗳𝗼𝗿 𝗦𝗲𝗾𝘂𝗲𝗻𝗰𝗲 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗶𝗻 𝗕𝗶𝗴𝗤𝘂𝗲𝗿𝘆 Let’s say you want to uncover the most common paths that lead users to a purchase. You would first define a set of key events, such as: ▻ 𝗽𝗿𝗼𝗱𝘂𝗰𝘁_𝘃𝗶𝗲𝘄 ▻ 𝗮𝗱𝗱_𝘁𝗼_𝗰𝗮𝗿𝘁 ▻ 𝗰𝗵𝗲𝗰𝗸𝗼𝘂𝘁_𝘀𝘁𝗮𝗿𝘁 ▻ 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲 By using sequence queries, you can track how users transition from one event to another, and identify the most common paths to conversion. 🔑 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗨𝗻𝗰𝗼𝘃𝗲𝗿 💡𝗕𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸𝘀: If many users drop off after add_to_cart or at checkout_start, this may indicate friction points. 💡𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻-𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱 𝗣𝗮𝘁𝗵𝘀: Identifying sequences that lead to a purchase consistently can help you optimize your site by promoting those actions or simplifying user flows. 💡𝗨𝘀𝗲𝗿 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: By grouping users by device, region, or behavior type, you can discover path variations that can be tailored for different segments. 🎯 𝗧𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Once you know your users' most common paths and where they tend to get stuck, you can act on this data: ✔️ Refine User Journey ✔️ A/B Testing ✔️ Personalization 🏆 𝗣𝗮𝘁𝗵 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 = 𝗛𝗶𝗴𝗵𝗲𝗿 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝘀 Have you used path analysis in your projects? Share your thoughts in the comments! #DataAnalytics #BigQuery #SQL #PathAnalysis #CustomerJourney #ConversionOptimization #DataDriven #DigitalTransformation #MarketingStrategy

💪 I just spent 10 hours writing a new article for the Simmer blog, and it was worth every minute. Path analysis in #GA4 is powerful in theory… but almost unusable in practice. So I rebuilt the user journeys of Google’s Merchandise Store using #R and #BigQuery. In the article, I walk through the full process step by step, and introduce a new approach that combines path analysis + funnel analysis to surface insights GA4 can’t show you. Most importantly, I focus on the business impact, not just pretty charts. Here are the questions we answer: 1. Where do users drop off most frequently? 2. What are the most common entry points? 3. Which landing pages behave like “dead ends”? 4. How far do users typically progress through the purchase funnel? 5. How do promotion views affect conversions? 6. What happens after users sign in? If you work in digital analytics, UX, ecommerce, or CRO, this is for you, and the full R code is included. Link to the article in the comments. #Rstats #DigitalAnalytics #DataScience #Ecommerce #UX #MarketingAnalytics

Why your SEO traffic is not converting (and how to fix it) You’re ranking on page 1. Traffic is increasing. But conversions? Flatlined. This is the silent killer of SEO success. Rankings without conversions create false confidence. Here is what is actually happening: You optimized for search engines, not search intent. The disconnect shows up in three places: 1. Intent Mismatch → Your content ranks for “best project management tools” → The page pushes your product immediately → The searcher wanted comparison. You gave them a pitch. Fix: Match content format to intent stage. → Informational queries need guides, not landing pages → Commercial queries need comparisons that include your solution → Transactional queries can handle direct product pages 2. Expectation Gap → Your title promises a “complete guide” → The page delivers a surface-level overview → The visitor leaves in 12 seconds You will see this in high bounce rate, low scroll depth, and no assisted conversions. Fix: Deliver on the promise made in the title and meta. → If you say “complete,” make it comprehensive → If you say “2026,” keep the data current → If you say “step-by-step,” show real steps 3. Conversion Path Chaos → You rank an informational blog post → The only CTA is “Book a Demo” → That is a 10-step commitment for someone still learning Fix: Align conversion paths with awareness level. → Top-of-funnel content: newsletter, free guide, tool → Middle-funnel content: case study, comparison, calculator → Bottom-funnel content: demo, trial, consultation The pattern shows up everywhere across SaaS and content-heavy businesses. Teams optimize content to rank. Then apply the same conversion goal to every page. Someone searching “what is content marketing” is not ready to buy enterprise software. They may download a beginner’s checklist. That is how you bridge the gap. SEO traffic already carries intent signals. The query tells you where the user is in the journey. Match the conversion ask to that moment. Not every page needs to sell. Some pages build trust. Some educate. Some nurture. Conversion happens across multiple touchpoints. Stop treating every ranking page like a landing page. Start building conversion paths that respect the journey. That is how traffic becomes revenue. What is your biggest conversion challenge with SEO traffic? ♻️ Repost if this clicked for you. P.S. If you want a clear view of where your content leaks conversions, DM me.

Your customers are ignoring your navigation. The data proves it. Watch any college campus. Perfect sidewalks everywhere. Yet worn dirt paths cut straight across the grass. Urban planners call these "desire paths." They show where people actually go... versus where we tell them to go. Your website has the same problem. You designed a logical flow: homepage to category to product to checkout. Your customers want something different. They're searching instead of browsing. Jumping straight to reviews. Bypassing your carefully crafted funnel. These digital desire paths reveal the truth. Your customers know what they want. And, your navigation is in their way. At The Good, we've tracked these patterns for 16+ years. The data is consistent. Visitors who find their desired path convert more often. Those forced through predetermined funnels abandon at higher rates. Smart companies don't fight desire paths. They pave them. Amazon put search at the center. Conversion rates jumped. Zappos made returns prominent. Sales increased. Netflix killed categories for personalized rows. Engagement soared. Your analytics already show these paths: ↳ Heat maps reveal where users actually click ↳ Session recordings show their real journey ↳ Search logs expose what they can't find The paths exist. You just need to look. Then pave them before your competitors do.

You improved your website speed. Pages now load in seconds. But sales? Still flat. Here’s the truth → Website speed doesn’t automatically mean conversions. It only gives you potential. What you do next decides if speed turns into sales. When your site loads faster, users stay longer — but that extra attention must lead somewhere. Speed opens the door. Strategy gets them to buy. Here’s what actually drives sales after a speed boost → ↳ Analyze post-speed user behavior through GA4 or Hotjar to understand new visitor patterns. ↳ Rebuild your hero section for instant clarity and emotional connection — fast attention needs fast persuasion. ↳ Simplify your conversion path; a fast page with a complex funnel still loses sales. ↳ Use the improved load time to enhance mobile UX — speed + ease = trust. ↳ Reorder elements for visual hierarchy; fast-loading CTAs must now capture intent. ↳ Reoptimize product pages and pricing visibility; faster discovery equals faster decision-making. ↳ Leverage behavioral personalization to show relevant offers dynamically. ↳ Retest ad landing pages — ensure ad promise and landing content are aligned. ↳ Maintain Core Web Vitals monthly; consistency sustains credibility. Your speed upgrade gave you performance. Now, refine the experience. Because in 2025, conversions aren’t driven by design or load time alone — they’re driven by perception, flow, and buyer logic. Fast websites create opportunities. Optimized experiences create customers. When your speed and strategy work together, every click has value, and every second counts. If your site loads fast but sales aren’t increasing, it’s time to audit your post-speed journey. You’ve fixed the performance — now fix the persuasion. Save this post as your post-optimization checklist. Comment “SALES GROWTH” if you’d like the framework I use to scale conversions after speed upgrades. Follow Dinesh Kumar for weekly frameworks on SEO, Websites, and Digital Ads designed to turn speed, traffic, and clicks into measurable profit. P.S. If your website loads quickly but still isn’t converting — let’s connect. I help businesses transform fast websites into conversion-driven profit machines through strategic SEO, high-performing design, and optimized ad systems. #WebsiteOptimization #SEO #ConversionRateOptimization #DigitalMarketing #WebDesign #CoreWebVitals #LeadGeneration #EcommerceSEO #PageSpeed #OnlineSales #DigitalAds #MarketingStrategy #DineshKumar

The new Path to Conversion by campaign groups in Amazon Marketing Cloud is becoming one of the most valuable tools for post event analysis and future planning. Until recently, interpreting the path to conversion signals was largely done at the account level. Anyone aiming to break performance down by campaign groups, product categories, or portfolio structures had to rely on custom queries, specialist assistance, and a considerable amount of manual interpretation. Now that AMC is integrated directly into the Ads Console, the barrier to entry has dropped significantly. Advertisers can explore the customer journey from first touch to final interaction using filters that focus on exactly the campaigns they want to analyse. The result is a clearer picture of how shoppers actually move through the funnel. This is especially valuable for brands that manage multiple categories or product lines. Each category tends to behave differently, and the new report makes that visible. A Sponsored Brands strategy that drives meaningful lift for one SKU might drain budget for another. DSP remarketing can be a conversion driver for some products, and almost irrelevant for others. The Path to Conversion by campaign groups report highlights these contrasts and provides evidence you can use to reshape strategy rather than relying on assumptions. Running this analysis regularly is useful, but it becomes indispensable around major retail moments. When you combine customer journey insights with deal performance, you can clearly see which levers accelerated discovery, which touchpoints genuinely influenced buying decisions, and where incremental investment is likely to pay off in the next event. 👉 If you want to check it out, open your Advertising Console, go to Measurement and Reporting, select Amazon Marketing Cloud, choose your instance, open Use Cases, and select Path to conversion by campaign groups. Allocate budget smartly across the entire Amazon Ads ecosystem! #AmazonAds #Advertising #Ad

𝗛𝗶𝗴𝗵 𝗧𝗿𝗮𝗳𝗳𝗶𝗰, 𝗟𝗼𝘄 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝘀? 𝗛𝗲𝗿𝗲’𝘀 𝗮 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗧𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗪𝗼𝗿𝗸𝘀 We see this all the time, companies generating 20K+ monthly sessions but not seeing a proportional impact on pipeline or revenue. If this sounds familiar, here’s a simple framework we use to identify what’s working, what’s not, and what to do next. It’s not about guesswork, it’s about categorizing your pages by potential and acting accordingly. 𝗦𝘁𝗲𝗽 1: 𝗗𝗼𝘄𝗻𝗹𝗼𝗮𝗱 𝗮𝗹𝗹 𝘆𝗼𝘂𝗿 𝘄𝗲𝗯 𝗽𝗮𝗴𝗲𝘀 Pull data from GA4, CRM, or your marketing automation platform, whatever gives you page-level traffic and conversion metrics. 𝗦𝘁𝗲𝗽 2: 𝗖𝗮𝘁𝗲𝗴𝗼𝗿𝗶𝘇𝗲 𝗲𝘃𝗲𝗿𝘆 𝗽𝗮𝗴𝗲 𝗯𝗮𝘀𝗲𝗱 𝗼𝗻 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 𝗮𝗻𝗱 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝘀 Once you have the data, sort your pages into these buckets: - 𝗛𝗶𝗴𝗵 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 & 𝗟𝗼𝘄 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 (𝗛𝗧 & 𝗟𝗖): These pages are pulling in visitors but failing to convert. CRO is your top priority here. SEO has done its job, now it’s about improving the on-page experience, messaging, and CTAs. - 𝗛𝗶𝗴𝗵 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 & 𝗭𝗲𝗿𝗼 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 (𝗛𝗧 & 0𝗖): These pages are your red flags. If you’re getting thousands of visits with zero impact on pipeline, it’s time to reassess the purpose of the page. Again, CRO is your main lever. - 𝗟𝗼𝘄 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 & 𝗟𝗼𝘄 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 (𝗟𝗧 & 𝗟𝗖): These pages need a full reset. Look at intent, content quality, SEO optimization, and conversion paths. Treat these as experiments to improve both discoverability and user flow. - 𝗟𝗼𝘄 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 & 𝗭𝗲𝗿𝗼 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 (𝗟𝗧 & 0𝗖): These are typically pages without clear value. Decide if they’re worth fixing. If yes, apply both SEO and CRO effort. If not, consider deindexing or repurposing. - 𝗟𝗼𝘄 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 & 𝗛𝗶𝗴𝗵 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 (𝗟𝗧 & 𝗛𝗖): These are your silent winners. They may not get a ton of visits, but they convert well. Double down on SEO to bring in more of the right audience. These are high-leverage opportunities. 𝗦𝘁𝗲𝗽 3: 𝗠𝗮𝗽 𝘁𝗵𝗲𝘀𝗲 𝗽𝗮𝗴𝗲𝘀 𝗯𝘆 𝗳𝘂𝗻𝗻𝗲𝗹 𝘀𝘁𝗮𝗴𝗲: 𝗧𝗢𝗙𝗨, 𝗠𝗢𝗙𝗨, 𝗕𝗢𝗙𝗨 You’ll often find your high-potential pages in the BOFU category. Start there. They’re closest to conversion and the most aligned with business outcomes. Here’s what we’ve learned after running this framework across multiple high-traffic B2B SaaS websites: - Treat each page as its own product. What works for one won’t work for another. - Think intent-first. Understand what your user is trying to achieve when they land on the page. - Optimize for clarity. 𝗧𝗿𝗮𝗳𝗳𝗶𝗰 𝗶𝘀 𝗴𝗲𝘁𝘁𝗶𝗻𝗴 𝗵𝗮𝗿𝗱𝗲𝗿 𝘁𝗼 𝗲𝗮𝗿𝗻. 𝗠𝗮𝗸𝗲 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗼𝗳 𝗲𝘃𝗲𝗿𝘆 𝘃𝗶𝘀𝗶𝘁. This exercise is where we usually start when onboarding clients with significant traffic but unclear ROI. It consistently reveals untapped opportunities, and gives the team clarity on where to invest next. TripleDart #seo #saasseo

❓Do you know your website’s top conversion paths, for your most important conversion type? I think every dealer would agree, the very-best-top-quality-we-want conversion type is: Lead forms What am I looking at in this screenshot? This is a Google Analytics 4 (GA4) Attribution Paths report I started tinkering with at a hotel waiting for a 20-group meeting. You can run this same report, just match my settings in the attached screenshot. 💡I didn’t realize you could filter this report to show just one conversion metric, so I did that. I built a report that answers the question: I wonder which conversion path, or shopping journey delivers the most lead forms on my website? And that is what the attached screenshot is showing you. The asc_form_submission events (following Automotive Standards Council guidelines), is one powerful and comprehensive event that tracks (or should track) ALL lead forms - not just website forms, but also leads from chat widgets, digital retailing tools, trade-in calculators, and other third-party integrations. For this dealership, three primary traffic sources are driving form submissions: -       Branded searches including Google Business Profile clicks -       Vehicle Listing Ads (part of Performance Max campaigns, hard to effectively measure, see my other posts!) -       Deeplinks from automotive marketplaces like Cars.com and AutoTrader What you cannot see below the screenshot, is the hundreds of additional longer tail conversion paths. I’m also not showing the assisted conversions on this same report, though often it is not as helpful. Of course understanding these paths helps you allocate marketing budgets more effectively, and reward channels that are driving your best conversions. 🎥 Subscribe to our Google Analytics 4 YouTube channel to stay updated on more GA4 best practices for automotive dealers. We're building a comprehensive library of training content to help dealerships navigate the transition to GA4, a link to subscribe is in comments. Follow George Nenni for more #automotive #automotivemarketing #automotiveindustry #googleanalytics4 #GA4tips and strategies to help your dealership!

🔔 𝐍𝐞𝐰 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐀𝐥𝐞𝐫𝐭: Amazon Ads 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 𝐏𝐚𝐭𝐡 𝐑𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠 Amazon’s new Conversion Path Reporting is a game-changer for brands aiming to fine-tune their advertising strategies. Here's what it brings to the table and why you should care: 𝗪𝗵𝗮𝘁 𝗜𝘀 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻 𝗣𝗮𝘁𝗵 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴? A feature that lets you visualize 30-day customer paths to conversion, providing unparalleled insights into ad product combinations driving sales. 𝙆𝙚𝙮 𝙁𝙚𝙖𝙩𝙪𝙧𝙚𝙨 𝙏𝙝𝙖𝙩 𝙎𝙚𝙩 𝙄𝙩 𝘼𝙥𝙖𝙧𝙩: 1️⃣ Ad Mix Analysis: Reveals which ad products and formats (like Sponsored Products, Display Ads, or Streaming TV) convert best. Identifies the cross-channel combinations moving customers through your funnel. 2️⃣ Comprehensive Reporting: Tracks touchpoints across Amazon DSP, Sponsored Ads, and more. This includes NTB (New-to-Brand) purchases and highlights growth opportunities. 3️⃣ Actionable Insights: Pinpoints optimization opportunities in near real-time. Helps balance brand-building ads with performance-driven campaigns for better ROI. 4️⃣ Media Impact Demonstration: Quantifies the full effect of your media mix to validate strategies and budget allocation. 𝙃𝙤𝙬 𝙄𝙩 𝘽𝙚𝙣𝙚𝙛𝙞𝙩𝙨 𝙔𝙤𝙪𝙧 𝙎𝙩𝙧𝙖𝙩𝙚𝙜𝙮: ✅ Faster Decision-Making: Real-time insights mean you can pivot campaigns to focus on high-performing paths without delay. ✅ Clearer Attribution: No more guesswork—understand which touchpoints contribute most to conversions. ✅ Increased Efficiency: Double down on ad formats delivering the best NTB purchases or conversion rates. ✅ Scalable Insights: Reporting is brand-level, spanning multiple advertising accounts—ideal for agencies managing complex campaigns. 𝙃𝙤𝙬 𝙩𝙤 𝘼𝙘𝙘𝙚𝙨𝙨 𝘾𝙤𝙣𝙫𝙚𝙧𝙨𝙞𝙤𝙣 𝙋𝙖𝙩𝙝 𝙄𝙣𝙨𝙞𝙜𝙝𝙩𝙨 📍 Navigate to your Campaign Manager in the Ads Console. 📍 Top conversion paths appear on insight cards—your Top 5 are displayed. 📍 Want granular details? Download reports from Measurement & Reporting. 𝙋𝙧𝙤 𝙏𝙞𝙥 𝙛𝙤𝙧 𝘼𝙙𝙫𝙚𝙧𝙩𝙞𝙨𝙚𝙧𝙨: 🔑 Use this tool to test cross-channel combinations—e.g., pair Amazon DSP video ads with Sponsored Display for full-funnel coverage. 🔑 Focus on NTB sales metrics to identify the channels driving first-time buyers. The beta phase might limit availability, but if you’re eligible, this feature is necessary for refining your Amazon Ads strategy. Stay ahead of the curve by leveraging data-backed optimizations to drive conversions like never before! What’s your take—have you started using Conversion Path Reporting? Share your insights below! #amazonppc #amazonadvertising #amazonselling

Amazon Ads Manager is hiding your full-funnel impact. Let’s fix that. You’ll make misinformed decisions if you keep: ❌ Looking at last-click attribution and ignoring assisted sales ❌ Pausing ads that seem unprofitable but actually help in conversions. ❌ Relying on Amazon’s default reports without digging deeper Here’s how this report works: Amazon’s Conversion Paths report reveals how your ads work together, allowing you to make smarter decisions rather than just cut costs. ✅Reveal the full chain of ads that contribute to the purchase process. ✅Optimise acquisition strategies by utilizing the data of new-to-brand sales. ✅Allocate resources to the paths driving the highest returns, focusing on multi-touch attribution. ➡️ Swipe to see how top brands are using this to scale profitably.