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With the loss of cookies, iOS updates, ad blockers, and more, attribution has become a mess. Here's a good summary of a few metrics you can look at to help prevent your business from relying on platform data that may not be (note: often isn't) accurate. One of my favorite metrics to consider is MER - Marketing Efficiency Ratio. If your revenue is increasing compared to your marketing spend (without other major overhead changes), then your advertising is working. What metrics do you look at to ensure your efforts are actually driving value?

🚨 Attention, marketers! 🚨 Major changes are afoot! Google's shaking things up on its attribution models. Out with the old – first-click, linear, time decay, and position-based attributions are waving goodbye and last-click and data-driven models are taking the spotlight. 🎯 So, what does this mean? 🤔 Well, it's set to significantly impact how we analyze our customer journeys within Google Ads and Google Analytics, disrupting our reporting landscapes. Want a simple analogy? Think of an attribution model like a football team - every player (or touchpoint) has a unique role, and the goal is... the goal (or conversion). ⚽ Different models give credit to different 'players', changing how we view conversions entirely. There's a catch though, Google’s new favorite, the Data-driven attribution model (DDA), isn’t without its flaws. Yes, it's driven by algorithms, but its contributing factors remain under wraps. Transparency, anyone? 🕵️♀️ But worry not! There are alternatives and strategies to navigating this uncharted territory. Devour all there is to know about Google's attribution model shake-up ➡️ https://lnkd.in/gVBtseDu Remember, change is inevitable, but progress is optional. So let's take a step forward to adapt, understand, and continue producing top-notch content. 🚀 Share your thoughts below - how are you bracing for these changes? #GoogleAds #AttributionModel #PPCMarketing #ChangeIsComing Casey Jones

Copy this exact process that I followed to track every dollar that I spent on Google Ads & Meta. Selecting the right method to track adsvertising process is troublesome. Almost every marketer has faced this isuuse since ages and I was one of them. Here are some of common issues that marketer or agencies face: Attribution Models Confusion: Choosing the right attribution model can be baffling. Each model offers different insights and fits to different needs. Data-Driven Decision Making: This model allocates credit based on actual data, giving you a realistic view of which touchpoints contribute most to your conversion. Complexity in Measurement: Conversion tracking isn’t just about counting clicks. Understanding the path that leads to a sale involves recognizing that earlier touchpoints, although not the last interaction, are crucial in the conversion proces 🔍 Here is the process that i use to choose best atrribution models that can help you to reward the platforms or ads that caused you sales. Evaluate your current attribution model and consider multi-touch attribution to get a fuller picture of your customer's journey and then based on sales data and timing test different attributions. Use tools like Google Analytics' Model Comparison Tool to see how different models impact your ad performance and then select the best model that suits your buyer's journey. Regularly update your tracking tags and ensure they’re implemented correctly across all campaign elements to maintain data integrity. Need help with your advertising? Drop a message and let's scale your business!

Yellowpop's digital game just leveled up with Polar Analytics's tools. We cracked the code on their strategy, and the results? You've got to see this. 🚀 Have insights or feedback? Feel free to connect directly. 📉 001 - Reduced Cost per Purchase Summary: With Polar's server-side tracking, Yellow Pop saw a substantial 36% drop in Cost per Purchase. The strategy's working, and the numbers speak for themselves. 📈 002 - ROAS Enhancement Summary: Achieved an impressive 28% increase in Return On Ad Spend on Meta. This isn't incremental change; it's a transformative boost. 🔗 003 - Improved Match Quality Summary: Solved the Click ID mismatch issue with innovative tracking solutions, leading to a significant improvement in ad performance metrics. 💰 004 - Controlled CPC & CPM Summary: Reduced Cost Per Click by 3% and CPM by 4%. Effective and efficient — that's the goal of any marketing campaign. Ruben G., Co-founder & CEO at Yellow Pop, summarized the experience: "Thanks to Polar, we achieved this without changing our ad spend, which was just amazing." Interested in how this was accomplished? Explore the detailed case study here. These results are just the beginning. Stay tuned for more updates and insights! https://lnkd.in/eYcGmPPA

Most consumers seeing your ads with "up to X off" get disappointed once they click on your ad. And that is costly for your company. They expect something better than what you deliver in most cases. In my head, I'm (wrongly) assuming that there are a lot of interesting products with 50% off. In reality, only a tiny amount of products, that no one typically wants to buy, are 50% off. Your sale ads with "up to 70% off" might have a great Click Through Rate. But on average, we see that the traffic from ads with "up to x off" have a 39% lower Conversion Rate on your site. Consumers don't want to feel manipulated. And when I talk with people about eCommerce, this is probably THE tactic that feels the most like manipulation. If you want great traffic, you need to align expectations better in your ads. Not manipulating people with high expectations just for them to figure out how lousy the offer is in reality. For the nerds: Data is based upon 10.6B impressions and 91.6k pieces of content, from September 2021 -> January 2023. Meta platforms only. Across all countries and industries. Campaign Objective is Conversions only. Ads are filtered down to ads mentioning sales or discounts. Confect algorithms are used to scan the text in the content and find words in the image/ video related to "up to x off". Numbers are looking at correlation only, not causation. Remember to check your own data: numbers for different brands, industries, and contexts will vary. Ideally, A/B test it. Oh, btw: You can check your own data with Confect :)

In today's digital landscape, optimizing performance tracking is not just a choice, but a necessity. Whether you're a marketer, developer, or an entrepreneur, adopting analytics will be essential for an uphill climb for your organization: The benefits of using GA4 with server-side tracking include: • Faster Page Loads: Server-side tagging reduces the load on browsers, ensuring quicker page loads. • Seamless User Experience: No more data collection interruptions. Users enjoy a smoother journey on your website. • Sharper Ad Targeting: Get ready to witness enhanced ad targeting and personalized experiences that make a lasting impact. Google Tag Manager steps into the limelight, simplifying the entire tag management and deployment process. It’s the glue that holds this seamless integration together. This guide arms you with troubleshooting insights, saving you time and frustration. Remember, data fuels decisions. Don't miss out on this empowering resource that uncovers how to unleash Google Analytics’ true potential through server-side tagging. Dive into the details here 👇 https://lnkd.in/gVJYSx6b #GoogleAnalytics #ServerSideTagging #DataAnalytics #DigitalMarketing #WebsiteOptimization 

Conversion value is how you hack Meta and Google. I’d say the majority of hack strategies on paid channels are BS. The algo’s are smart and if you have an intermediate to advanced knowledge of channel optimization you know all the tips and tricks. The hack now is making your user experience better and your data smarter. At some point I’ll do a user experience post, but honestly I see those everywhere. Ok the strategy. Right now the majority of e-comm companies are using conversion value to run tROAS campaigns with variable products and optimize for the highest absolute value. Update that revenue number to a contribution margin number and now your ROAS is a profitable revenue metric inclusive of costs. That’s level 1. Now let’s say you’re running a lead acquisition strategy. All leads aren’t created equal so don’t count a lead as 1. Let’s use zip for example lead submit with zip 00001 = $1 and zip 00002 = $100. Where do you think the the algo is gonna optimize? This is more effective than targeting individual zips with different CAC goals cause the algo has higher CPMs for targeting. The moral of the story use conversion value. Your data is your edge. Use it wisely.

Attribution modeling isn’t dead… it's just changed a lot in the last few years. Google Analytics offers a few attribution models that your brand should be using depending on what your goals are. I’ve previously discussed the Data Driven Attribution model and will discuss another one today… Google Analytics 4 Paid and Organic Last Click attribution model, simplifies the attribution process by attributing 100% of the conversion value to the last channel the customer interacted with before converting. I normally never recommend only using a last click attribution model and believe a mixed model is best for seeing the entire picture on which touchpoints are in a customer’s journey, however there are times when a last touch attribution model can be beneficial. Additionally, due to its simple nature, it can be a great starting place for brands who are in their infancy with understanding their data. Last touch attribution is also helpful if you want to know which of your marketing channels and touchpoints have the most influence in the final stage of the buyer's journey. Here's your TLDR on how it works: A customer's journey can be through various channels: display ads, social media, paid search, and organic search. Under the Paid and Organic Last Click model, all the conversion value goes to the last touchpoint the customer engaged with. It's a straightforward way of crediting the source that directly led to the conversion. This model streamlines the attribution process, making it easier to track and measure the effectiveness of your marketing channels. It provides clarity and simplifies decision-making by giving full credit to the final interaction. While it may not capture the entire customer journey, it offers valuable insights into the channels driving your conversions. It's worth noting that Paid and Organic Last Click is also known as Last Non-Direct Click – two names for the same attribution model. The key takeaway here is that it's a user-friendly model and easily understandable for brands just starting out with tracking and trying to understand their marketing data.  #LastClick #Attribution #GA4 #googleanalytics #attributionmodels

Hey, exciting news! Meta just rolled out an awesome update to their ads! 🎉 If you're running a shop on Meta and Instagram and you're using Google Analytics 4, you're in for a treat. Now, you can easily keep track of all the purchases people make from your shop using Google Analytics. 🛍️ Here's the scoop broken down into simple steps: Step 1: Before anything else, make sure you've got a shop set up on Facebook and Instagram. Your very own virtual store! Step 2: If you're running ads to bring more shoppers to your store and you want to know how well those ads are doing, Google Analytics can help. But here's the trick: make sure that when people click on your ads, they land in your shop. Step 3: Let's get the ball rolling with a few things: Grab a special code called a tag from Google Analytics. This code is like a secret helper that keeps track of what's happening in your shop. Craft a unique tag for your shop within Google Analytics. Think of this like putting on a pair of special glasses that show you all the action in your shop. Link this nifty Google Analytics tag to your shop on Meta and Instagram. It's like connecting your favorite video game to the controller for seamless play. Step 4: Remember to sprinkle in some special words (known as UTM parameters) to the links people click on. This helps Google Analytics figure out where people are coming from. Think of it like giving a map details about your journey to find hidden treasure. By following these steps, you'll have the power of Google Analytics at your fingertips. You'll know exactly how many folks are shopping in your Facebook and Instagram store. Plus, you can even figure out which ads are hitting the bullseye! 🎯 How cool is that?

📣 Google's Ad Auction Changes: Search Ads Price Increases Again 💸 Attention, advertisers! With Google's recent tweaks increasing ad prices again by up to 10% for search queries it's another clear reminder to all ➡ Relying solely on third-party data isn't enough as platforms will always push for their profitability and not yours. 📈 Why First-Party Data Matters: 1️⃣ Direct Customer Insights: Collecting data directly from your audience (e.g., email sign-ups, website interactions, purchase history) gives you unfiltered insights and creates opportunities. 2️⃣ Higher Accuracy: First-party data is more accurate and relevant, leading to better targeting and ROI. Building Your First-Party Data Arsenal: 🔹 Leverage Google Ads & Meta short term: Use lead generation campaigns to encourage sign-ups, surveys, or content downloads. 🔹 Engage & Retain: Offer value in exchange for data. Think webinars, exclusive deals, or e-books, community building efforets, etc.. 🔹Optimize Landing Pages: As always, ensure they're user-friendly, optimised, and have clear CTAs. The Payoff? By building a robust first-party data ecosystem, you can: ✅ Tailor your marketing strategies more effectively. ✅ Reduce dependency on rising ad costs. ✅ Foster direct relationships with your audience. Remember, while Google Ads & Meta Ads are powerful tools, it's how you use them that counts the most. By focusing on first-party data now, you're setting yourself up for more sustainable, cost-effective campaigns in the future and less dependancy on ad auction prices. 🎯 How are you leveraging first-party data in your strategy? Let's share and learn together! Drop your insights below. 👇🚀