By now, consumers are well aware of the potential for how brands can use customer data to communicate with them in a more personalized way. Every day, in their inboxes and on their phones, they bear witness to both the best and worst examples of brands trying to bring more relevance to their cross-channel marketing. And each time they receive a brand message that utilizes their data in a clever, positive, and responsible manner, it raises their expectations for future brand communications.
Marketers whose success depends on access to accurate, robust customer data have understood for a while now the importance of having that data consolidated into one centralized point of storage. But that value isn’t always easy to quantify and put into numbers that the average marketer can fully understand.
In our latest webinar, Aron Clymer (Founder & CEO, Data Clymer) shared the work his company did with Major League Baseball’s San Francisco Giants, utilizing the capabilities of modern data platform Snowflake to give their Marketing and Sales teams the ability to use it in ways they never could before — and with impressive results to go along with it.
The MessageGears marketing console is an enterprise Java application that connects directly to Customer data sources to allow our users to segment users and personalize messages. Traditionally, we have leveraged JDBC (Java Database Connectivity) drivers to standardize connectivity to dozens of traditional and modern databases, which work well across nearly any standard data source and give us the flexibility to connect to dozens of customer data stores.
Today, however, MessageGears now fully integrates with the Google BigQuery API to support faster and more efficient data transfer to power our Segment, Message, and Engage products.
For Super Senders that have considered moving to a modern data infrastructure, the biggest hurdle is often the bottom line for basically every business: cost. No matter how much benefit the Marketing team sees from having better data access, if it can’t be directly tied to revenue and a tangible ROI, it’s liable to be passed over for more pressing needs.
Because we’re believers in the immense power of a modern data infrastructure to revolutionize the way marketers use their data, though, we decided to partner up with MarTech Review and LumenData to do a close examination of the costs and savings associated with this sort of investment in order to develop a research-based ROI model so that companies can go into the decision-making process more confidently because they have better information.
Our exclusive new research into the enterprise marketing experience with modern data warehouses (MDWs) uncovered lots of interesting information about how those relationships are working from the marketing side. While the general tenor was quite positive, we received a wide variety of responses to our questions, as one would expect.
But the most consistent, resounding response came to our question about benefits to working with an MDW. No matter the size of the organization or their responses to other questions, enterprise marketers overwhelmingly said that they saw the benefits from having their data in an MDW.
For enterprise marketers, the dream when it comes to cross-channel marketing is to be able to easily access and utilize the data they have to deliver campaigns that feel personalized to the individual customer. But what’s been clear for some time is that’s a dream that’s rarely realized, with data hard to get out of various sources and nearly impossible to reliably get up to the ESP’s marketing cloud in order to build out those targeted campaigns. Response time lags, data feeds break, security is questionable, and everything’s often just generally a mess.
If this sounds familiar to you, you’ll want to watch for our upcoming research report, examining our Q4 survey in which we examined marketers’ experience with modern data warehouses, looking at the challenges and benefits they’ve encountered from their investment in consolidation and access for their customer data with a modern data warehouse.