Best Practices

Drive effective E-Commerce ad targeting with rETL | Census

Ross Katz
Ross Katz August 24, 2022

Ross is the Principal and Data Science Lead at CorrDyn, a data-driven technology consulting company. At CorrDyn, Ross oversees projects that leverage data to deliver value to clients across industries, including E-Commerce, EdTech, BioTech, Finance, and SaaS. Prior to joining CorrDyn, Ross received his Master's Degree in Information and Data Science from UC Berkeley and occupied various analytical leadership roles along the way.

For E-Commerce leaders looking for opportunities to grow and become more profitable, developing a reliable analytics engine that consistently generates insights about your customers, products, supply chain, and fulfillment operations is critical to your success. 

Over the past five years, cloud data warehouses (like BigQuery, Snowflake, Redshift, and Synapse) have become the central hub for various software-as-a-service (SaaS) tools and in-house operational systems to come together and deliver those critical data insights. 🤝 Data extraction tools such as Fivetran cohesively streamline the process of bringing this data together, while data warehouses provide the computational horsepower and flexibility to deliver the answers E-Commerce companies need to identify problems, remove bottlenecks, and build their businesses. 💪

But the data warehouse cannot be a “be-all end-all” in itself. Actually generating value from data requires four elements:

💯 The right data

⏰ At the right time

📍 In the right location

✅ To take action

It’s easier than ever to ensure data warehouses have the right data at the right time, but getting that data in the right location to take action remains problematic. That’s where reverse ETL (rETL)  comes in.

So, how can data and operational teams leverage rETL to put together the second half of the value chain for your E-Commerce business? Read on. 👇 

Passing conversion tracking to advertising platforms

Starting at the top of the funnel, app tracking transparency and similar browser ecosystem changes have added noise to every company’s ability to track potential buyers through their website traffic.

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In particular, attribution of conversions to specific marketing activities has become less reliable, especially through in-browser cookie tracking, making marketing optimization even more difficult than usual. As the ad ecosystem searches for better solutions to the problem of missing attribution, you can take advantage of advertising platforms by leveraging your customer data to guide advertisers toward better ad targeting and spending.

The platforms you already utilize for advertising, including Google, Facebook, Snapchat, TikTok, Criteo, Pinterest, and Twitter, can all deliver better return-on-ad-spend with improved visibility into your website’s conversions. 🔍👀

Reverse ETL empowers business teams and analytics users as they manage the process of pushing data to advertisers. So, when you pair rETL with your data warehouse for conversion tracking, you: 

  • Put the ownership of your conversion data in the hands of the people who know your customer best, giving marketers and data teams the power to be creative and drive performance. 🚀
  • Remove barriers to website updates that come with your housing conversion tracking codes. Your marketers and data teams can iterate on what works, so changes to your conversion-tracking ecosystem don’t require expensive developer time (since you most likely have these conversions living in your data warehouse already!) 🚧❌
  • Expand and refine your definition of what “counts” as conversion, allowing advertisers to see offline conversions, products added to the cart, conversations with your sales team, or whatever constitutes a meaningful milestone in the customer journey for your business. If certain products are returned to the warehouse frequently, you can delay reporting and adjust your conversions for whether or not someone returned the product. You are not confined to when, where, and how someone clicks on your website. 🔓

Nurturing potential and existing customers with targeted outreach

Now that you’re generating high-quality traffic and using discounts to gather email addresses, you want to customize the messaging to resonate with each audience and (re-)convert them. This is applicable in two different contexts:

  • Targeted paid advertising – Reverse ETL enables optimized digital campaigns for your user base by syncing to ad tools’ customer lists. This works double duty: It gets rid of manual CSV uploads and enables you to run targeted ads for users that might have abandoned their cart, haven’t returned to place an order, or made an account and never added anything to their cart. 🛒
  • Marketing automation system – This is only as intelligent as the data housed within it. Moving data from your touchpoint on your website and SaaS providers into your data warehouse only gets you halfway there. By incorporating information about customer search terms and product page visits into systems like Marketo and Hubspot, you can enable your email marketing team to deliver the specific promotions that lead to sales. 🤑 For example, you can send relevant, personalized notifications to users in the hours that they have previously interacted with your platform. Because email marketing data is your own, you can feed what you learn from these messages into your top-of-funnel systems as described above.

Guiding sales, customer support, and customer success operations

Once potential or existing customers visit your website and research your products, they may need that extra nudge from a one-on-one connection to get them to make the first purchase or to resolve an obstacle that's currently preventing them from repeat purchasing. ✉️ Putting the customer profile, order & return history, and recent site interactions at your team’s fingertips can help them to prioritize interactions and deliver the experience that wins a long-term customer relationship with higher lifetime value. 

Keeping customers apprised of their orders

Your company can improve the customer experience by creating better app integrations between fulfillment operations and customer notifications. Suppose fulfillment information is already in the data warehouse via your ERP system, Shopify Fulfillment, or direct integrations with fulfillment vendors. In that case, your company can provide updates to customers based on your vendor information, and rETL can push relevant fulfillment information into your email automation providers, such as Sendgrid, Sailthru, and Mailchimp.

Regardless of where you drive value using your data, you want your operational leaders to own operational processes with a single source of truth. When you implement rETL into your modern data stack, you put those processes in the hands of the people who know the customer best and understand how the customer journey should work, not just how it does work. 

And in E-Commerce, it pays to be nimble. When you leverage your data warehouse with a tool like Census, you operationalize your analytics and turn the flexibility of your analytics system into the flexibility of your business as a whole.

If you want additional data expertise to drive value from your data, CorrDyn acts as your extended data team, helping you to connect all the pieces of the E-Commerce data value chain, from data acquisition 👉 analysis and modeling 👉 action.

✨ Want to get started using rETL to drive more effective ad targeting? Book a demo with a Census product specialist. 

✨ Want help connecting the pieces in your E-Commerce data value chain? Get in touch with a CorrDyn expert.

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For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps: