Understanding your customers when there’s only a handful isn’t too difficult. But as your company grows and the number of customers expands rapidly, it can be overwhelming to keep up with the change. Who are your customers? What do they want? How can you provide the best customer experience to give you a competitive advantage? Those questions can all be answered with data analytics.
Brands today have huge amounts of data on their customers. When it comes to customer experience, data analytics can be broken down into three key areas: descriptive analytics, prescriptive analytics and predictive analytics. Knowing what answers you want from the data can help you use it in the most effective and strategic way possible.
If you want to know what happened, use descriptive analytics. Until recently, this is how most companies used data—to see what had happened in the past. Using analytics, descriptive data can paint the picture of the past. Descriptive analytics can be customized to fit any time frame or set of customers. If you want to know what has happened in the last 30 days or year with only a certain demographic of customers, descriptive analytics can get you accurate answers.
In customer experience, descriptive analytics can be used to track things like total tickets and resolutions. They can be especially helpful in tracking trends to help plan for the future. If the number of customer calls increased greatly around the holidays or when a new product launched, you can plan for increased call volume around those events in the future. Descriptive analytics can also help provide a better understanding of customers by tracking their shopping and contacting preferences.
One of the newest types of data analytics is prescriptive analytics, which takes descriptive data and uses it to make recommendations for future actions and improvements. Prescriptive analytics give advice on potential outcomes and recommend what will happen if those outcomes are reached. By pinpointing the best outcomes and making recommendations, companies can focus on delivering an amazing customer experience. Prescriptive analytics help companies make decisions that reflect customers’ needs and changing trends.
Some credit card and insurance companies use prescriptive analytics to analyze past factors like purchase history and credit score, to predict how a customer will behave in the future and what actions the company can take. Prescriptive analytics are action-based and help keep the company ahead of trends to make smart, future-focused decisions.
Like the name implies, predictive analytics look at what could happen in the future. With the help of AI, predictive analytics have not only been growing in recent years but also becoming more accurate. Algorithms can sort through massive amounts of data to create forecasts on anything ranging from when a customer will need a new product to what services will be the most popular to how to staff a contact center. Predictive analytics can even pinpoint factors for dissatisfied customers so that brands can address the issues before the customers abandon ship. Predictive analytics aren’t guaranteed; after all, nothing can accurately predict the future all the time. However, they can help forecast and give companies things to look and plan for in the future.
Most modern companies use some form of predictive analytics. Data can show what clothing items have been purchased in the past and predict which items customers will want to purchase in the future. Similarly, data that shows when a customer bought a car can predict when they will want to make an upgrade. Although predictive and prescriptive analytics are similar, predictive analytics anticipate customers’ needs, and prescriptive analytics help give brands action items to improve.
Descriptive, predictive and prescriptive analytics all work together to create a high-quality customer experience. When used strategically, all types of data analytics can save time and money while helping brands create more customized experiences. Understanding past actions increases a brand’s knowledge of its customers, while predicting what will happen in the future and recommending potential action items can help create a more personalized customer experience. To build a future-proof customer experience, rely on all three types of data analytics.