Acxiom Powers its
Real-time Transformation from Data Provider to Customer Intelligence Leader with MongoDB

INDUSTRIES

Martech / Adtech
Consumer Services
Corporate Services

PRODUCTS

MongoDB Atlas
MongoDB Realm
MongoDB Charts
MongoDB Atlas Data Lake

INITIATIVE / USE CASES

Cloud Data Strategy
Analytics
Security & Compliance
Single View

CUSTOMER SINCE

2017
INTRODUCTION

Using data to build a leader in the martech space

Over the decades, Acxiom has been a leader in the ethical use of all things data, providing access to vast amounts of data and data management capabilities for Fortune 500 enterprises to help them better engage with their audiences. Over the last few years as part of the Interpublic Group of Companies (IPG) acquisition in 2018, Acxiom has taken a highly proactive approach to expanding its data-driven capabilities with new cloud innovations, bringing martech and adtech together to power more effective marketing decisioning, activation, and measurement.

Today, Acxiom is a customer intelligence company that provides data-driven solutions to enable the world’s best marketers to better understand their customers, to create better experiences and business growth. IPG leverages Acxiom’s foundational data and identity capabilities, including its expertise in privacy, across its media agencies such as Mediabrands, which includes UM (Universal McCann) and Initiative. IPG is also leveraging Acxiom to build new data-powered products to serve a wider range of companies by helping them make the best use of all their data assets and connecting the end-to-end marketing ecosystem.

Acxiom has been a valued MongoDB customer since 2017. The companies’ first projects together centered on using MongoDB Atlas and MongoDB Stitch (now rebranded as part of MongoDB Realm) to provide Acxiom and its customers with access to all relevant data powering real-time decisioning and data management capabilities for Acxiom clients. As Acxiom continues to innovate and provide a more holistic set of solutions and capabilities across a connected martech and adtech ecosystem, this has resulted in the expansion of the partnership with enhanced requirements and opportunities to jointly address the growing needs of brands. One example of this is the new MongoDB Charts dashboarding feature that enables user data visualization across a host of connected data sources.

THE CHALLENGE

Find better ways to provide data-driven solutions to brands, and support real-time decisioning

Finding better and more efficient ways to provide data-driven solutions to brands is an ongoing focus area for Acxiom:

Real-time Decisioning:

A key area of focus for Acxiom is continually enabling brands to optimize their experience on the Acxiom platform across a host of use case-specific customer data platform use cases. “On behalf of our clients, it is imperative our teams can visualize select data in Acxiom’s event-driven data environment to monitor the flow of customer requests for data, and to identify any that exceed a predefined threshold within two seconds of latency to enable real-time decisioning,” said Scott Jones, an Acxiom Fellow. The prior processes relied on a more cumbersome approach that limited real-time decisioning capabilities for the end client.

Data Integration:

Another way Acxiom helps customers is by enabling them to collect, cleanse, and connect their data to various martech solutions such as Adobe, Salesforce, and Unica to launch and manage campaigns. Acxiom is a market leader when it comes to bringing data together, then cleansing, stitching, and orchestrating it to enable brands to execute campaigns across connected customer intelligence.

Acxiom Data Trends & Insights:

Acxiom itself is focused on analyzing trends and insights across its own proprietary third-party data offerings. This requires the ability to look across all of its connected data to identify new data type opportunities that may have emerged, and new data product opportunities for Acxiom to deliver the most unique and relevant data available for brands.

THE SOLUTION

Leverage MongoDB’s Cloud data platform to build a real-time decisioning solution

“We chose MongoDB as our metadata store because we wanted to go away from relational. This simplified our metadata completely. When we store a layout of a file, it’s one document. It’s not five or seven intersection tables. This has made our administration a lot simpler, so we can focus more on the business logic,” said Jones.

“We chose MongoDB as our metadata store because we wanted to go away from relational. This has made our administration a lot simpler, so we can focus more on the business logic.”

Scott Jones, Acxiom Fellow, Acxiom

Acxiom’s real-time decisioning system leverages Realm for the API and Atlas to store documents with integration to their existing authentication and PII engine. “By using MongoDB to productize some of our key capabilities, we have now reduced our time to deploy new customers from two months to less than 20 minutes to have the base solution up and running. The only thing left after deployment would be to implement any customer custom exit points,” said Jones. This has provided improved latency and throughput for the applications. It is also easy to install custom validation as a function per client and yet work off a single codebase for the overall application. Webhooks offer the API front end that activates Realm functions which then perform the work of retrieving or inserting documents.
“By using MongoDB to productize some of our key capabilities, we have now reduced our time to deploy new customers from two months to less than 20 minutes to have the base solution up and running.”

Scott Jones, Acxiom Fellow, Acxiom

To achieve its objective of delivering a great customer experience and the use cases above, Acxiom is using Charts to build dashboards visualizing data in the event-driven environment. In a recent project, Jones specifically monitors a brand’s data insights report and consumer opt-out requests to readily troubleshoot requests that are being slowed by data latency. As shown in Figure 1, the dashboard displays three groups of charts showing how many customer requests have been made over the preceding six hours, day, and week.

Figure 1: Acxiom customer requests dashboard using MongoDB Charts

“The most important figures I’m monitoring are the visualizations in each group showing any requests that have taken more than two seconds to execute. When a request exceeds that two-second threshold, I can now click into a performance debugging dashboard in Charts to learn more about the request, such as the source, and can quickly troubleshoot the request to provide the desired sub-two-second execution time going forward. This is a big improvement to the process in place prior to the adoption of the Charts tool,” said Jones.

Jones has provided a MongoDB Charts dashboard to Acxiom’s Vice President of Engineering that shows error data from Acxiom’s core data management intelligence engine, as shown in Figure 2. Connected to the dashboard are Git repository pulls and Jira check-ins so the VP can see at a glance how often errors are occurring and how quickly they are being resolved. Visualizing errors and error handling data allows the VP to quickly track and in a sense, to gamify developer performance by having users and teams compete to see who is performing the most check-ins and reviews, who can generate the least amount of errors, and who can resolve errors the fastest.

Figure 2: MongoDB Charts dashboard Acxiom uses to quickly visualize performance

“One of the benefits of using Charts is that rather than sending data to an external analytics and visualization tool, MongoDB Charts is generating those things directly from the database,” said Jones. In addition to Acxiom’s work with MongoDB Charts, which is primarily to drive internal operational intelligence, it also integrates and uses BI tools such as Tableau and Looker for some client-facing reports.

“To address customers’ needs for accessing specific portions of the data, and to make the freshest offer data available to them when they need it, we used MongoDB Realm and MongoDB Atlas to create a cloud solution that enables customers to request data from the enterprise data warehouse Acxiom is managing on their behalf,” said Jones. “This allows us to enrich that data in real time with updated offer information.
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Lastly, Acxiom utilizes Atlas Data Lake paired with Charts to better understand the cost of its cloud infrastructure. It ingests AWS billing data exported into AWS S3 and uses Data Lake as the query engine to run aggregations, persisting the results to an Atlas Cluster. “We use Atlas Data Lake to bring all of our AWS usage data into one place for internal business owners,” said Jones. “We’re able to aggregate data in S3, write it to an Atlas cluster and visualize it using Charts. This gives us a full view into our usage across six different AWS master accounts without complex data transformation.”
THE RESULTS

Operational excellence, expanded self-serve, and freedom to focus on
business value

Acxiom can now better understand operational performance with much less effort. Jones no longer has to manually create weekly or monthly reports to isolate data latency areas that require troubleshooting, which has made this process easier. “With the MongoDB cloud data platform, whether it’s Atlas, Realm, Charts, or Data Lake, you don’t have to think about it,” said Jones. “Just use it and go on with your day. Click and it’s done.”
“With the MongoDB cloud data platform, whether it’s Atlas, Realm, Data Lake, or Charts, you don’t have to think about it. Click and it’s done.”

Scott Jones, Acxiom Fellow, Acxiom

Jones added, “We’ve cut the time to develop an API for our customers in half, and our teams now have more time to solve business problems for our clients versus focusing on the management or operational overhead. Combining MongoDB Atlas, Data Lake, Realm, and Charts has become a key part of our cutting-edge cloud architecture, helping us design, build, and manage omnichannel solutions that power exceptional customer experiences.” Jones said Acxiom is also achieving better alignment between its data technologies and its business-side stakeholders, helping the business side be more in-the-know and self-sufficient, and less dependent on manually pulled reports. “My monthly process to produce the information is simpler. So, a lot less time for me and self-serve convenience for the business. I don’t have to worry about who is in a spreadsheet. I can just share a dashboard link.”

“Combining MongoDB Atlas, Data Lake, Realm, and Charts has become a key part of our cutting-edge cloud architecture, helping us design, build, and manage omnichannel solutions that power
exceptional customer experiences.”

Scott Jones, Acxiom Fellow, Acxiom

As noted at the outset, Acxiom is serving as the customer intelligence foundation for brands and supports IPG agencies to provide connected martech and adtech data-driven media solutions. Its partnership with MongoDB supports Acxiom in delivering these solutions. As an example of better alignment and collaboration between the data management and privacy teams, Jones said, “When new files come in with attributes we haven’t seen before and have yet to be classified, we’re now able to quickly share this data with the privacy team so it can determine whether the data is PII (personally identifiable information). This helps Acxiom ensure our clients are always privacy-compliant.”
“When new files come in with attributes we haven’t seen before and have yet to be classified, we’re now able to quickly share this data with the privacy team so it can determine whether the data is PII (personally identifiable information) This helps Acxiom ensure
our clients are always privacy-compliant.”

Scott Jones, Acxiom Fellow

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