Know Your Customers, Drive Your Growth

Trusted Records Help a Global Money Transfer and Financial Services Company Deliver Better Customer Experiences to Improve the Bottom Line.

Picture this: You’re on a global money transfer and financial services company’s website trying to send money and are having trouble with the transaction. You head to the site’s chat function and get help from the support agent who not only solves the problem, but also offers a discount on the money transfer fee since you’re a high-value customer.

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Providing this level of service requires knowing your customers and the full history between them and an organization. And obtaining these complete customer views and making sure different systems’ records are “talking” to each other was made possible by Tamr.

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Why knowing 90% of your customers isn’t enough

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To better serve their customers, this global money transfer and financial services company was transitioning from a retail-first organization to a digital-first one. As part of this transformation, the financial services company began integrating records from online and retail channels to form 360-degree customer views. 

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But when hundreds of millions of people have used the provider’s services to send and receive money over the years via three different channels (retail stores, website, and mobile app), data volume, variety, and quality issues made obtaining those single customer views challenging.

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“You may have five profiles but you are the same person. And I should be able to give you the same service whether you’re using the mobile app, the retail channel, or the website. We wanted to bring all of that information together and offer a great omni-channel engagement,” the company’s chief data architect said. But without accurate customer data, providing an elevated level of service “was absolutely impossible.”

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However, the company did have some insight into their customers. They used a 10-year-old rules-based master data management (MDM) tool that cleaned most of the customer data. However, that wasn’t enough to impact the bottom line.

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“You make a real difference in that final 10% to 20% zone. That’s when you can reduce fraud or increase revenue. Our product has remained the same so to have a business result, we had to look at how much money we could make from those customers or how much risk we could reduce,” said the chief data architect.

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Conventional rules-based systems can be effective on a small scale, relying on human-built rules logic to generate master records. However, rules quickly fall apart when tasked with connecting large amounts of highly variable data at scale, especially when dealing with millions of customer records from a multitude of sources.

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“To master 200 million records using the traditional way of writing rules, we’d be doing it for 10 years and probably still wouldn’t be able to do it,” commented the chief data architect.

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Adopting a modern approach to MDM

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To adopt a modern approach to MDM, the money transfer and financial services company deployed Tamr. With Tamr’s next-generation solution, AI and machine learning handle a majority of the manual data preparation work. Humans are kept in the loop to provide feedback and manual curation for edge cases when needed. 

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“The way mastering is done, our data analysts and data scientists were blown away by it. Most of their time was spent writing rules. And here they were building experiences for our customers while bringing Tamr along that journey to build the heart of our data foundation,” said the company’s chief data architect. 

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The company also used Tamr to enrich records with external data to standardize mailing address formats, validate phone numbers, and check that email addresses have valid domains. Combining data enrichment with customer mastering means that not only are data sources automatically cleaned, they are also enhanced with valuable commercial information while avoiding the extremely time-consuming and manual work that goes into incorporating external data.

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Each customer record was also assigned a Tamr ID, a persistent identifier that serves as a reference to an entity across multiple data sources assigned by Tamr. The customer records created by Tamr were loaded into the Snowflake Data Cloud, which provided the company with a single source of truth to power both analytical and operational applications.

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Delivering better customer experiences for bottom-line growth

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One front-end system that leveraged the Tamr ID was used by the support agents who fielded questions submitted via the chat function on the company’s website. The Tamr ID provided the agents with the customer’s full transaction history. Since people sometimes have multiple accounts, viewing only one of them wouldn’t show if a person was a top customer.

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The company also used records mastered by Tamr as part of an initiative focused on communicating with customers using Salesforce Marketing Cloud. A feature of this marketing automation platform is the ability to send messages by text and email as well as in the company’s mobile app. Successfully reaching a customer with the right message on the right channel requires accurate email addresses and phone numbers, which Tamr provided. 

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With Tamr, the company also increased customer matches from their retail and online databases by 3 to 5%. The business impact of this modest increase was quite substantial given the size of the customer base. As a result, the company was able to spend less on marketing by not reaching out to the same person over and over again. This adjustment made a very big difference to the company’s top-line revenue and bottom-line results.