One of the most profound movements in marketing over the past five years or so has been the desire to consolidate as much customer information as possible into a single 360-degree customer database — more specifically, a Data Warehouse. If you have every piece (or nearly every piece) of first-party, second-party, and third-party data that you own or have acquired about your customer in one place, you can be even more personalized, responsive, and predictive (i.e. leverage AI models) about how best to serve and communicate to those customers. And customers increasingly expect you to leverage their data in this manner — to deliver a better cross-channel experience that “surprises and delights.” To fail to do so is to risk losing that customer relationship.
In the past, creating an enterprise data warehouse required a significant investment in hardware and software, along with the need to size it correctly. Too large, and you paid for unused capacity. Too small, and you quickly outgrew it.
Enter the modern Cloud Data Warehouse. Providers such as Snowflake, Amazon’s Redshift and Google’s BigQuery are just a few of the most popular modern data warehouse providers that allow you to scale almost infinitely with minimal up-front investment, while leveraging tools such as Fivetran where needed to effortlessly replicate siloed data into a modern, high-performance data warehouse. For marketers, this has become a great opportunity, as described by the head of Marketing Analytics of Square in this article “The Unlikely Marriage of Data Warehousing & Marketing”.
Once the data warehouse is ready, though, many marketers using legacy ESP marketing clouds are still faced with the onerous task of integrating and replicating portions of that data warehouse to the marketing cloud — and paying for it in the form of data storage, latency, and the headcount to support it.
In increasing numbers, sophisticated cross-channel marketers in organizations who have invested in a marketing data warehouse have been looking to solutions like MessageGears as their ESP so as to skip the painful processes described above entirely and instead use their Data Warehouse (whether cloud-based or on-premises) as their ESP database. These “Super Senders” attach the MessageGears Accelerator product directly to the data warehouse as a small-footprint, value-added marketing workbench to create audiences, campaigns and content to send over to the cloud for message rendering, delivery, and analytics.
It’s important for Super Senders to remember that tech should liberate and empower them, not limit them and throw up barriers.
MessageGears Accelerator sits directly on top of the data warehouse, making that the system of record for audiences and personalization data for things like conditional content. Benefits of this approach are numerous – including agility, security, and cost. Brands who have adopted this approach (including Expedia, Chick-fil-A, and Ebates) have seen significant benefits in the areas of improved engagement and ROI — and at a cost that’s significantly less than other ESPs because they don’t have to replicate their customer data into their ESP’s cloud and pay twice for storage.
It’s important for Super Senders to remember that tech should liberate and empower them, not limit them and throw up barriers between their teams and the innovative work they want to do — and, perhaps more importantly, their customers have come to expect from companies of their size. Brands that combine a hybrid platform like the one MessageGears provides with their Customer Data Warehouse are seeing the walls come down between their aspirations and their martech stack, and the results have been a win for Marketing, I.T., and the customers on the other end of the campaigns.