Data analytics works in a way that the information about the customer’s use, purchase, experience, etc., is used to understand customer behavior and predict future patterns. Predictive analysis and new technology can anticipate customers’ choices and needs. Data summarizing past events is vital, and companies actively study these data. Companies involved in game and mobile app development use predictive analysis to match up with their competitors and thus improve their customer experience. When the customer-marketer relationship is improved, it helps to boost sales and, at the same time, increases consumer satisfaction. With the pandemic, companies have seen an increase in online shopping, which proves the need to improve the company’s online presence or acknowledge that their platform needs improvement.
Companies, small or large, should invest in predictive analytics. Predictive analytics firms such as https://www.pecan.ai/resource/cx-score-predictive-analytics/ help set up a digital presence for traditional companies and plan to collect and analyze data. Here are the top ways predictive analytics can help with customer experience.
Hyper Personalized Marketing
Knowing what the customer expects, wants, and needs before they say it becomes more accessible as a marketer. That is a feature that forecasts analytics help with. With the data or information collected and analyzed, you can predict a consumer’s behavior by understanding their pattern. This helps you create a personalized collection that makes the experience relevant and engaging.
Virtual Concierge
Just like OTT platforms can provide personalized suggestions about films, series, or documentaries. Similarly, people expect the same experience on other online platforms. Predictive analytics driven by AI help you predict the customer’s future choices based on their previous views, likes, searches, etc. This makes the experience more convenient and enjoyable for the client/customer.
Efficiency
With the use of predictive analytics, the operational efficiency of the company is also significantly improved. It helps you in situations like customer traffic based on previous experiences. These shipping issues may or may not occur, providing the customer with an accurate date of shipping and forecasting demand and inventory. All of these combined improve the internal efficiency of the company.
Churn Reduction
Any company is bound to have some customers that will leave them for their competitors. Forecast analytics helps understand their behavior and what they have not liked about the experience. With this information, an improvement in these specific areas can be made to ensure fewer churn-risk customers. It also helps you pay more attention to these customers in ways or incentives to satisfy them.
Better Pricing Model
With small or traditional companies, the prices are set based on age or gender. With the help of forecast analytics, you can decide the costs based on the customer’s previous choices, needs, frequency of using that product, etc. For example- insurance marketing companies can predict the prices for a customer based on how frequently they drive a car to understand their chances of meeting an accident. This helps the companies to set personalized rates/prices for each individual.
Final Thoughts
Predictive analytics can provide the necessary push your company requires. You can benefit from the promising efforts of forecast analytics and ensure a better customer experience for your clients.
