GrowthLoop

2025 is coming in hot. 🔥 Is your data strategy ready? We compiled our top 10 resources that will help you have the best data year yet. Catch the list in our latest edition of Looped In. Plus, find out where you can meet the GrowthLoop team (in person!) in January. 👀

Today, let’s bust the “zero-copy” myth and dive into why zero-copy is not enough. Salesforce and others now tout the fact that they offer a zero-copy solution to customers. This definitely represents an improvement to the costly, closed, and cumbersome model many of us have gotten used to. Less data movement is better for security, cost, and efficiency, which is why our platform was built to be zero-copy since we founded GrowthLoop. But Salesforce still misses *the greatest advantage* a data cloud-native solution offers: an open and flexible data model. Most companies have very complicated data, and it can painful and constraining to fit their data into a closed and fixed data model like Salesforce Marketing Cloud’s. Here are some quick examples I’ve personally seen of how complicated targeting can be: ➡️ A baseball club needs to manage complex relationships between individual people, corporate accounts (for corporate packages and events), and brokers. ➡️ A bank needs to be able to differentiate between primary and secondary contacts, parent entities, and “households” in their outreach. ➡️ A B2B advertising company needs to link advertising activity across an agency’s clients and roll-up advertising spend across the subsidiaries of a multi-national conglomerate. None of these naturally fit inside most email or engagement platform audience targeting tools because they reflect the complicated nature of real-world relationships and data, not a standard set of filters. Why don’t existing martech solutions support more nuanced targeting despite its benefits? Because it would mean re-writing the entirety of their application from the ground up. With thousands or hundreds of thousands of customers relying upon their legacy software, that is simply too much of an undertaking.   Instead, I predict they will try to confuse the market with concepts like “zero-copy” to keep attention away from the core issue — their closed and fixed data model. Who is getting it right?  Data cloud-native products built to support an open and flexible data model from the very beginning. Connect with us if you agree. #ZeroCopy #SalesforceMarketingCloud #Composable

Want to build buy-in for your data strategy and the tech that goes with it? This advice from Luke Stenis is pure gold. 🥇 #DataStrategy #composableCDP #DataCloud

Almost every martech platform these days has some kind of AI component. Sure, they help save time or eliminate the more tedious tasks of marketing. But ultimately, they sit on a limited dataset. The #AI can only build and learn from the data it has access to, which, in this case, is the data in your CRM or email platform. Now, imagine what AI could unlock for your #marketing if it sat on top of your organization's Snowflake or Google Cloud #BigQuery — a single source of truth for *all* data, not a portion of it in a martech tool. It could: 🤔 Analyze campaign results in seconds 🤔 Spot trends in customer behavior (churn risk, upsell opportunities) 🤔 Make recommendations for high-performing, more optimized campaigns That's the power of AI on the #DataCloud. Dive into how (and why!) you should apply AI to your data cloud in the latest post from Anthony Rotio. ( 🔗 in comments 👇)

Thanks to the Snowflake team for hosting us at their Boston Seaport office, as we brought regional banking leaders in for a Lunch and Learn event with Traci Michel, PMP of Metro Credit Union. Traci shared her team's journey as they work to move away from a core-centric data management strategy by building a single version of truth in the Snowflake Data Cloud. With its enterprise data in Snowflake, Metro is building a scalable data architecture that brings operational efficiency and repeated utility of its data assets. We will be releasing video excerpts from the event in the coming days, but for now, here are some photos with our panel with Traci, Greg Spencer and Scott Whalen of Passerelle, Eddie Drake of Snowflake and Robert Livada of GrowthLoop.

Want to know an underrated ingredient in data transformation? Empathy. Data is information — it’s clicks, transactions, and demographics. But behind every single customer data point is a real person. So each time you send a campaign, don’t just think about potential revenue — think about the human who will get the message. 💡Use your data to talk *with* them instead of *at* them. After you ask AI to help you build an audience, think about the actual people in that audience. 🎨Let unified data paint a picture of who they are, what they want, and how you can help. Don’t forget internal empathy, either. Approach data transformation based on how it will affect the other teams around you. Consider how the data team’s life will get easier if they don’t have to field cross-functional requests or how marketing can be more creative with self-service data access. 🤝Empower teams with data to make everyone’s lives better. When you start by thinking about the person behind the data, your data becomes your most powerful tool for reaching and helping them effectively. #DataStrategy #DataCloud #composableCDP

GrowthLoop now integrates with DV360! Take your audience activation to the next level by exporting segments directly from GrowthLoop to Google’s ad ecosystem. Launch campaigns across Gmail, YouTube, display, connected TV, and more — all while saving time, improving targeting, and staying compliant. Trusted by leading brands like Allegro, GrowthLoop makes it easy to connect your first-party data to the channels that matter most. Swipe through to see how #DV360 and GrowthLoop can simplify your workflows and deliver better results. #GoogleAds #DigitalMarketing

The holidays are like the Super Bowl for retailers. And the competition is fierce. Changing customer expectations and shifts in data collection have made it harder than ever for marketers to succeed in a crowded retail space. That’s why I collaborated with Jason Downie, U.S. CEO of Making Science, on these data-driven strategies retailers can use to maximize their earnings this season (and future-proof their marketing). Check out our tips, or catch the link to the full Total Retail article in the comments below.  1️⃣ Put first-party data first With third-party cookies on the decline, prioritizing first-party data is more important than ever. Loyalty programs and mobile apps are great tools for building comprehensive customer profiles (with consent!) and enabling deeper personalization. 2️⃣ Leverage #GenerativeAI Retailers like Walmart are finding tangible ways to leverage generative #AI to improve customer and employee experiences. For example, their “adaptive retail” program harnesses data and large language models to improve their product catalog. This improves customers’ ability to find what they’re looking for. 3️⃣ Predict inventory and pricing needs AI-powered predictive analytics can help forecast demand, align inventory and delivery, and fine-tune pricing strategies in real time. This approach avoids stockouts and rushed pricing changes while improving margins. 4️⃣ Adjust campaigns in real time Holiday campaigns need to adapt quickly. Real-time data helps refine ad spend and messaging on the fly, ensuring campaigns align with customer trends. A centralized #DataCloud paired with AI makes this easier than ever. 5️⃣ Unify cross-channel data Siloed data hurts customer experience. By integrating data across in-store, online, and mobile channels, retailers can deliver a seamless journey and consistent messaging that keeps customers coming back. The future of #retail is data-driven and AI-powered. Those who embrace it now will be better positioned to meet rising expectations and build lasting loyalty—not just this season but all year long.

We can't wait to join the biggest event in tech innovation — that's right, we're headed to CES 2025! 🚀 If you're scaling your #AI strategy or looking to optimize your #DataCloud investment, keep an eye out for our team! Mary Kheedo, Jace Dicker, Ash Giles, and Kyle Martinowich will be on the ground in Vegas and ready to answer questions like: 👉 How can I maximize my data cloud investment? 👉 What’s the next step in building a future-ready AI strategy? 👉 How can I drive personalization at scale? Secure time on our calendar with the 🔗 in the comments below. 👇 🫡 See you in a couple of weeks! #CES2025 #CES

We’ve all heard it before: Those who don’t learn from history are doomed to repeat it — and that couldn’t be more true in marketing. Teams lose key insights when campaign results are forgotten or people move on. That’s learning loss — and it happens all the time. But what if your #AI acted like a team historian, remembering every campaign, every test, and every result? Instead of relying on memory or digging through old reports, AI steps in to retain and build on past successes, so you’re not stuck repeating the same mistakes. With unified-loop marketing, AI learns with you, using past campaigns to continuously improve results, ensuring you’re always building on what worked before. It’s like having a team member that never forgets. How are you tackling learning loss in your marketing team? #MarTech #ComposableCDP