Data Maturity Roadmap: Reaching the Pinnacle of Data Maturity

If you’ve made it this far into the Data Maturity Roadmap (Start with Tier 1, Tier 2, or Tier 3 if you like), you’re hopefully thinking about how these steps could make your path easier. You see where your organization stands in relation to Anna, and you’re thinking about what challenges you might face when trying to implement similar solutions with your team.

But maybe you’re also wondering how much of this is theoretical, as opposed to being tested in the real world. It all sounds good, but is this just a way for MessageGears to steer you in the direction we want you to go? Has any of this actually been put into practice with enterprise organizations that walked this path before you?

It’s fair to ask those sorts of questions, so here’s a “cheat sheet”: real examples of our customers who have been in your shoes and put in the work to take true ownership of their customer data. Here’s where the Data Maturity Roadmap really comes to life, and the specific steps they took along that journey.

Tools can’t keep up with their modern data warehouse

When a Top-10 big-box retailer came to MessageGears, they faced a familiar challenge. They’d invested in Google BigQuery as their modern data warehouse because they understood how important customer data was to their marketing strategy. But what they found once they got it in place was that their marketing tools — Salesforce Marketing Cloud for their ESP and HCL Unica for marketing automation — couldn’t connect to or keep up with BigQuery.

It was taking them 7+ days to get a personalized offer into Salesforce for sending, and it took 24+ hours to send a single abandoned-cart email, resulting in countless revenue in lost sales and poor customer experiences. They were running nightly syncs from BigQuery to a database Unica actually supported in order to put it to use, and they had to send data to Salesforce a week ahead of time for QA and templating. Today, though, they’re in a far better place. Here’s what their path looked like:

• Added MessageGears Segment to their martech stack, allowing them to replace Unica by directly segmenting data within BigQuery, and then uploading audiences to Salesforce Marketing Cloud in <1 hour for live email
• Began using MessageGears Engage as a live data store for their website to draw real-time pricing and inventory data from via API call >1,000 times per second, ensuring customers see the most up-to-date deals when they log on
• Started using MessageGears Message for a limited number of email campaigns, allowing them to see the potential of pulling their data in live and launching those campaigns faster than on Salesforce – seeing a higher engagement rate and ROI from messages using live data
• As they saw the potential for MessageGears Message, they began migrating more of their email campaigns over from Salesforce, owning more of the process on their end and becoming more nimble with changes where needed
• Results: Campaign deployment 24 times faster, and 15% higher engagement rates

Campaign deployment 24 times faster, and 15% higher engagement rates

The CDP just doesn’t work

A major digital hospitality leader was struggling with many marketing cloud solutions — an ESP, CDP, and a data management consultancy to manage the data going back and forth. They had begun consolidating their data in Snowflake, but nothing seemed to be working as they expected. Their ESP, Cheetah Digital, couldn’t connect to Snowflake, which is a common issue we see across most ESPs.

And, importantly, the CDP they were paying a significant amount of money to (SimonData) wasn’t doing much of anything for them. Many promises were made during the sales process, but it turned out that none of the connections worked. There was a tremendous amount of frustration on their marketing team, and they didn’t know if there was a better solution out there. We started them on the road to data maturity, and it looked like this:

• Connected MessageGears Message to their Snowflake environment through the native API connection, allowing them to start using the live data in Snowflake for the first time
• Discovered MessageGears Segment and quickly realized that it provided virtually all the advantages of SimonData but without any of the drawbacks related to connectivity and data friction; this allowed them to sunset SimonData and use MessageGears Segment as their CDP, saving money while improving performance
• Opened up audience activation on Facebook and Google Ads via MessageGears Segment’s audience-building tools and direct data access
• Enabled cross-channel communications on email and push notifications with MessageGears Message, ramping up their ability to send highly personalized emails at the massive scale they needed
• Results: Total Customer Lifetime Value rose 15%; Operational spend on marketing software dropped 20%

Total Customer Lifetime Value rose 15%; Operational spend on marketing software dropped 20%

It’s a matter of trust

A major publishing company had its own set of data issues, with copies of their customer data being shipped off to various messaging providers. This meant that different vendors were copying the data at different times, leading to inconsistent or incomplete feeds, and a situation where different departments within the company had disparate sets of data they preferred.

When no one fully trusted the data they — or anyone else at the organization — was using, it created all sorts of silos that led to customer interactions that were sloppy at best and downright confusing at worst. They needed to find a way to bring all that data together, but they didn’t know where to begin. The Data Maturity Roadmap was a good place to start, though. Here’s how they did it:

• Upgraded their internal data warehouse using Amazon RDS, giving them total control over data in and out of their system; this was a positive first step, and what they needed next was to find a solution that could help them take full advantage of their new setup
• Began installing MessageGears on top of their database to enable them to have a full 360-degree view of their customer by connecting directly to their data and giving them access to it all, live and in real time
• Ran through the transition process extremely quickly, with the entire migration taking less than five weeks from ink on paper to being fully onboarded and sending campaigns; because they had assembled all their data together with Amazon RDS, template design and audience creation was a breeze
• Results: 6-month net engagement across their audience base is above 90%; email read and click rates up 15% from before the switch

6-month net engagement across their audience base is above 90%; email read and click rates up 15% from before the switch