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Real-Time Data Improving Customer Service

Renee Johnson
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The ability to collect and respond to real-time data about customers is increasingly separating winners from losers. Success requires analyzing, collecting, and acting on client data. You can collect massive amounts of real-time data but can you act on it quickly?

You can be ready to act on data using decision management and other technology-based solutions. However, these solutions are meaningless without the right real-time data. If you want to offer outstanding customer experiences that increase revenue and build loyalty, real-time data is your best friend.

These practical tips will help new and established businesses adopt a real-time data strategy, particularly in marketing and customer support.

 

1. Collect and Analyze Real-time Client Data

Real-time is vital, but it’s not the only factor. You have a lot of data to work with when you know what a consumer is doing today. However, it’s also important to know what they did yesterday or the day before.

That’s why it’s critical to get data from multiple sources about your customers.

 

2. Look Beyond the Client

Real-time data about customers and other areas of corporate operations provide context for business choices.

A good example comes from Dickey’s Barbecue Pit. Their real-time data showed lower-than-expected sales and a glut of ribs at one site. In response, they sent offers for a ribs special to customers nearby and it worked out well for both parties.

This emphasizes the need for a customer data platform that can integrate with other business systems. In addition, it should be able to examine real-time customer data alongside real-time data from other areas.

 

3. Make Mobile and Social the Focal Points

Nothing surpasses mobile and social data sources for knowing what clients are doing in real-time. Using that data is like personally following clients around to find out where they are and what they want.

Revive Vending, a chain of self-serve coffee shops, employs IBM Watson Analytics to monitor consumer tweets for purchase intent. This allows them to make judgments about product inventory and promotions. These are based on what consumers are thinking and doing right now, rather than what they’ve done in the past.

 

4. Take Action Right Away

Collecting real-time data on your customers and your firm from many sources is only the first step. You must also be able to assess and act in real-time. According to recent research, 75% of customers who contact a firm via social media expect a response within an hour.

While it may sound quick, in the world of marketing and customer service, an hour seems like a long time. Therefore, taking advantage of today’s marketing and customer service opportunities requires quick thinking and acting.

 

5. Let Big Data Help You Predict Your Client’s Next Step

When developing a real-time consumer data strategy, it’s necessary to look beyond. That is, you should consider using predictive analytics to not only grasp the moment but also foresee the next one. With big data, you can do this even before your customers do.

According to the trend, people will soon expect businesses to anticipate their future needs. One factor affecting this is the evolution of self-learning marketing technology. As it implies, this technology learns from its actions, becoming smarter and better at predicting and making decisions over time.

 

Conclusions

For some businesses, big data is more like “big overwhelming data.” Pulling out the important or useful data from all the information can be extremely daunting. For some, this influx of data from all directions is like trying to get a drink from a fire hydrant.

Many companies are coping with this dilemma by creating big data policies. These policies determine which data is captured and therefore analyzed. They also determine which data is not useful enough to retain.

Many businesses have chosen not to gather some data today, sometimes because they have no adequate place to store it. However, more often it’s that nobody can identify a clear value for the data. This shows a greater demand for people with the education and expertise to help businesses use real-time data effectively.

 

Image Credit: Yan Krukov; Pexels; Thank you!

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