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With just a few clicks and our brand new connector, you can combine your Google Analytics data effortlessly with other key sources like CRM, ERP, social media metrics, email campaign data, & POS data. Like everything Snowflake, it just works. Derive valuable insights for understanding your customer journey and driving personalisation by building your own enterprise grade models and apps for: 1. Customer 360 2. Multi-touch attribution (MTA) 3. Churn prevention 4. Next best action And if you really want to jazz it up check out our Composable CDP/MarTech partners Hightouch, BluSnow, Census, Segment, Braze, and Simon Data! Want to know more about how Snowflake can help your marketing/retail teams? Follow James W. Warner and Leslie Lorenz for insights or contact your friendly ❄ account team and let us do the heavy lifting for you 💪 https://lnkd.in/gJDWqhzu #MarketingDataCloud #martech #adtech #customer360 #snowflake #mlops #genai #llm 

𝗛𝗼𝘄 𝘁𝗼 𝗖𝗿𝗲𝗮𝘁𝗲 𝗮 𝗦𝗲𝗾𝘂𝗲𝗻𝘁𝗶𝗮𝗹 𝗲𝗖𝗼𝗺𝗺𝗲𝗿𝗰𝗲 𝗙𝘂𝗻𝗻𝗲𝗹 𝗶𝗻 𝗕𝗶𝗴𝗤𝘂𝗲𝗿𝘆 Creating a sequential funnel works like this: users must go through all the steps in a specific order. For example, if someone lands on your site directly on a product page, they won’t be counted because they need to start at step one. This is the hallmark of a closed funnel. Here’s how to do it: 1. Define Your Funnel Steps: In an eCommerce funnel, typical stages include product view, adding to cart, starting checkout, and completing the purchase. It’s crucial that all these steps are mandatory because a sequential funnel requires users to pass through them in order. A closed funnel counts only those who start from the very first step, like viewing a product. This focus helps you concentrate on users who genuinely go through the entire journey. 2. Extract Data: Start by pulling the necessary data from your Google Analytics 4 (#GA4) events table. You’ll need events related to key user actions to track their movement through the funnel. 3. Create Joins: This is where it gets interesting! Combine the data for each step to count how many users make it to each stage. Make sure your joins only include users who completed previous steps in the right order. For example, step two will count only those who viewed a product and added it to the cart; step three will include only those who added an item to the cart and started checkout, and so on. 4. Don’t forget to check event timestamps: you want to ensure that users performed previous actions before moving on to the next steps. It’s also important that all actions happen on the same day to keep your data accurate. 5. Visualize Your Data: Once everything is set, save the results in a new BigQuery table and create visualizations in Looker Studio. And that’s it—your sequential funnel is ready! If you’re interested in diving deeper into attribution and learning how to build funnels effectively for your business, I’m launching a course soon, and there are just three days left for early bird pricing for only $199! Don’t miss out on this opportunity - drop me a message or put "course" into the comment section! More details here - https://lnkd.in/gz8zsjAe

👉 Do you want to understand more about Optimizely Data Platform (ODP) - what it is and what you can use it for? The benefits and how it differs from Google Analytics? Then you should read our ODP expert ✨ Adrian Naderi's blog post. Enjoy! https://bit.ly/3UvlFSW #optimizely #customerdataplatform #CDP #personalization #epinova

💡 Building sequential funnels in BigQuery provides an essential view of the customer journey for eCommerce businesses. Alex Ignatenko's steps show how BigQuery can be used not only to capture each stage but also to ensure users progress through the sequence in the intended order. I especially appreciate the focus on event timestamps and precise joins—two key elements for reliable insights. Having worked with BigQuery, I know how crucial these sequential funnels are for identifying where users drop off, allowing businesses to target the stages that need attention.

New site or a re-platform, you can't overlook well-prepared product data. It'll be critical. But there's a lot that often gets overlooked - or not even considered. What you're risking by not giving your product the attention it deserves are things like: * Product listing content on the website is minimal * Poor organic rankings as there is not enough content for Google * Problems with Google Ads not serving * Terrible click through rates on your ads * Poor conversion rates on your product pages * High bounce / low engagement on product pages * Spending more energy and effort on data feeds in the future that you don't need to These are all things you can minimise with good product data. So, here's 7 things you can invest time in from the get-go: 1. Centralise product data with a PIM if you haven't already to serve as your product master 2. Product data enrichment: with images, titles, descriptions and multi language if that's required 3. Product classifications for pushing data to media platforms/aggregator 4. Missing GTIN; these are necessary for Google or other aggregator sites and without them ads may not serve 5. Product descriptions need to read like an amazing Ad while also appeasing the Google SEO gods 6. Ensure it's exportable so you can create data feeds for multi channel distribution into channels like Google, Meta, Amazon and other marker places 7. Ensure your PIM can integrate with ERP, CRM and any other systems is ready for integration to avoid errors. Product data is like the start of the pipe and if its blocked it'll jam everything else up down the line. Spend time on this before the new site goes live - it'll make life way easier in the future, not matter how big or small you are. #ecommerce #digitalmarketing #b2becommerce

What a week for Customer Data Platforms. With Q4 upon us, several of the CDPs we work most closely with have made significant announcements. There are 4 big things I’d like to highlight among the CDP providers we work closely with: 1) CDP World was the best in person martech conference I’ve attended in some time. With great partners like Treasure Data, MetaRouter, and a host of clients and former clients, this event rocked. Congrats to Treasure Data on this touchstone event.   The conversation focused heavily on AI – with interesting demos of LLM powered marketing automation and insights. 2) Lytics has announced its xCDP positioning. Lytics is bucking the CDP Institute's categorization of CDPs and saying there are two types of CDPs…data CDPs and experience CDPs. With its robust integrations to common CMS providers such as #WordPress and #Drupal, Lytics has lowered the barrier to rapid time to value for a new constituent in the CDP Center of Excellence – front end engineers and web developers. Of course, the data still needs expertise like Actable can provide, but activations on the website are even more seamless.   3) BlueConic. Long a holdout in the composable approach, BlueConic announced its foray into the hybrid game of traditional CDPs with composable capabilities on the #Snowflake platform. 4) Simon Data also recently announced new capabilities to extend the reach of addressable audiences to The Trade Desk. Simon clients have additional optionality for addressing audiences on an additional scale ad platform. Each have said that the CDP category is both real-time and composable depending of course on your use cases – with the ability to support all of them. It will be interesting to see how composable players respond, as they have dependencies on the cloud data warehouse. Yet, for brands with well-organized data, careful governance, and/or stringent data privacy requirements, the composable CDP space remains attractive for ease of implementation and data privacy. With all the innovation in the customer data space, I'm excited for what's ahead for the CDP category.

 Is your CDP a Swiss Army Knife or a Spork? CDPs promise a unified customer view, but with so many flavors, are you getting the right tool for the job? Greg Krehbiel's latest article for MarTech breaks down the 4 main types of CDPs: 1️⃣ Data 2️⃣ Analytics 3️⃣ Campaign 4️⃣ Delivery. Discover which one helps YOU: 🍝 Untangle your spaghetti junction of customer data 🔦 Craft laser-focused marketing campaigns ❔ Finally understand your audience (and stop guessing!) 🎚 Level up your marketing tech stack! Read more: https://lnkd.in/eN7nxAXc #marketing #martech #cdp #customerdata #cx #customerexperience

Did you know that Optimizely Data Platform (ODP) is Optimizely’s take on a Customer Data Platform (CDP)? If you’re familiar with CDPs, you know how valuable they are for centralizing customer data and boosting engagement strategies. With ODP’s user-friendly interface and robust tools, managing customer data has never been easier. In my blog post, I break down what ODP is, how it works, and why it might be the right fit for your business.

‘Despite the predicted growth in CDPs, enthusiasm for implementing is contradictory’ 🛒 ⬇️ With third party cookies on the move; businesses are looking to CDPs to help them increase the first-party data they hold and engage in privacy-compliant practices like sharing through data clean rooms. My career comes from a CRM and Direct Mail background and it’s always surprised how little some in businesses initially know about their customer database by lenses such as lifecycle. Even basic RFM segmentation to build strategy and retention rates by segment and LTV. - In my experience the issue with CDPs adoption will once again be less to do with cost and more to do with not knowing how to properly resource and use them once purchased. (A problem throughout all Martech that btw, white elephants firms then resent because they didn’t also get a pilot for the plane) - Key though is to work with your CDP provider to build customer analytics models people understand to make strategic designs with regards to growth that the top of the business understand and align on. (It’s in the CDPs best interest to provide such support) - Whilst equally (and this is vital) putting the platform in the hands of marketers to tactically execute, creating segments, exporting into platforms (not just email, but ad platforms, and the website itself for CRO), so as to be testing and learning. CDPs are a brilliant development for businesses if used correctly, and this article encouragingly also notes that when ‘it comes to generative AI, CDPs are still in the early stages of exploring how it can enhance their offerings. Based on our discussions with vendors, we expect to see much more innovation in this arena in the coming years.’ - Martech - Pamela Parker - April 12, 2024 #cdp #marketing #ecommerce #analytics #crm

Today the market is flooded with ESPs, CEPs, CDPs, etc. and every platform touts the ability to transform data with “real-time” campaigns. All this cross-talk makes it incredibly confusing to know which direction is the right one to take when you’re evaluating your martech stack. Let's clear that up.