How Predictive Analytics Improves Customer Experience

Customer experiences can determine if businesses will succeed or fail. In striving to provide successful experiences, businesses tend to focus on the importance of collecting data.But, brands who want to increase customer loyalty as a result of great experiences need to leverage analytics to engage with their customers better.

Predictive analytics helps decision makers see historical patterns and make predictions about future behavior for specific individuals. By taking customer data that is held internally and adding what people have said and done, companies can map out what customers are likely to do next.

Customer experience is a major revenue driver

While collecting data is important, the real challenge lies in aggregating the right data and then using the insights in a timely fashion to improve customer experiences and bottom-line results.

Analytics are fueling how businesses understand and value the customer experience, across the entire lifecycle and through every channel. Through research, strategy, insights – and basically putting the customer first – customer experience is one of the primary differentiators that businesses can somewhat control. Brands that provide compelling customer experiences outperform their competition.

Staying ahead of the curve

Instead of looking at the past and reacting to issues as they arise, predictive analytics uses all of the data available to predict how consumers are likely to respond. Analytics should never be a reactive practice. Rather, organizations should be proactive and use predictive analytics to identify opportunities and challenges before they arrive. Predictive analytics helps you learn more about customer behaviors and their subsequent experiences (i.e. allow you to better anticipate customer issues and provide resolution as quickly as possible). When issues arise, service representatives need the information and ability to resolve the problems.

Where to begin

Like every new initiative, the best place to start any predictive analytics program is to take the time to define objectives. What are the goals? What data will you need? Does the strategy fall in line with the overall company vision?

To set the stage for successfully implementing predictive models across an organization, it’s also critically important to involve all relevant stakeholders early. It is important to build buy-in and collaboration, as well as determine whether existing resources will suffice or if there is a need to build new systems. By laying this foundation, executives have a clearer path for putting data-driven models to work.

Going to the next level

Traditionally, segmentation has been used to divide customers into groups based on certain demographics, attitudes, or buying behaviors to target them with specific messaging that will resonate. Utilizing predictive analytics, previously hidden patterns in the data help organizations generate more in-depth customer segments. The resulting segmentation is more precise and nuanced, and is ultimately based on the increased likelihood that a consumer will respond positively by accepting the offer. As customers receive more relevant offers it results in a more profitable relationship for the company.

Advanced segmentation strategies help identify niches based on consumer behavior and as a result can significantly boost marketing effectiveness. Companies that deploy these techniques will accelerate past the rest of the pack in developing and deepening customer relationships.

Beyond segmentation, there are several other ways that predictive analytics can positively impact success. Advanced customer experience analytics techniques can help companies leverage data for more profitable outcomes across the organization, including:

  • Identifying strategies to reduce attrition
  • Targeting improvements at key touch points to accelerate issue resolution
  • Increasing cross-sell rates with sophisticated customer segmentation
  • Boosting the value of your Voice of the Customer program.

Whatever the objectives, predictive analytics can help companies transform customer data into valuable insights that benefit both customers and the business.

Analytics are playing a more critical role

Analytics has become a crucial piece of the customer experience puzzle. Without analytics, organizations would be paralyzed from the copious amounts of data collected on a daily basis. Companies must first assess their competencies in using data and perhaps consider bringing in a professional with advanced analytics expertise to help develop more actionable insights. Using data science and predictive analytics, these analysts can help organizations synthesize data sources across multiple channels to better target the right customer with the right offer at the right time.

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