How to Achieve Reliable Customer Data

How to Achieve Reliable Customer Data

How to Achieve Reliable Customer Data
Reliable customer data is crucial for the success of any business. It lets you communicate with your customers effectively, informing you which products, offers, services, and messages they’d be most interested in at any given time, and which communication channels they’d likely prefer.

You can see information about previous interactions customers have had with your company, and make sure that you have things like correct affiliations and spelling of their names – all of which can lead to a better customer experience and prevent loss of business due to simple mistakes.

But attaining reliable customer data is often an ongoing challenge. Just look at a typical omnichannel customer journey today – customers may visit your website looking for a product. They may use a mobile application to order it, and if there’s an issue or they need help, they may contact a call center.

They may also go to the store to return or exchange the product. Meanwhile, they subscribe to marketing emails for coupons and deals and follow the company on social media. This is how customers do business today — they pick the channel and the time of interaction most convenient to them.

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Capturing all this information and supporting these complex omnichannel journeys requires systems to maintain and share customer interactions, transactions, and profile information. But disconnected systems and channels make it challenging to create a single source of reliable customer information, so data often remains siloed.

Point-to-point system integrations are expensive to build and maintain. In these scenarios, sales, marketing and support teams have little confidence in the quality of their customer data, often questioning if it’s up-to-date and clean. Unreliable data leads to uninformed and inconsistent communications with customers, and, in turn, poor customer experience and loss of business.

What’s needed is for organizations to be able to bring customer data from all internal and external sources together into a single source of truth — information that includes demographics, multichannel interactions and transactions, social media feeds, and third-party data subscriptions.

Data from various sources needs to be matched and merged using various rule sets and machine learning algorithms to create a single “golden record” for each customer. Modern data management solutions are helping answer this need, and enabling all business users within an organization to access and contribute to a standard customer profile.

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