As part of its activity, all companies collect data about their customers. This includes identity data, of course, but also data regarding engagement or attitude. This information can be collected by various means, in particular by a call centre or customer services, and used for strategic purposes. Conversational predictive analysis uses the data gathered during interactions with customers to anticipate their future behaviour and improve the quality of the service offered. What are the main advantages of this method, and which sectors use it?
Recording and analysing conversations between a consumer and an agent provides access to key information, in particular on customer intent, thanks to predictive analysis. This is an essential strategic lever for companies and contact centres, giving them a head start in identifying potential customers and their propensity to make a purchase.
Thanks to a better understanding of customer profiles, conversational predictive analysis enables you to optimise your marketing campaigns and implement actions that are fully in line with your objectives. Your prospect/customer conversion rate can also be improved using this technique, as can your customer retention rate.
Conversational predictive analysis helps to define offers that are better adapted to customers and more likely to retain them. It can also be an excellent upselling support, helping to increase sales.
With conversational predictive analysis, your teams have everything they need to adapt to customer demand and be more reactive in solving problems. Clear savings in time and gains in productivity!
Many companies use conversational predictive analysis for the specific needs of their business sector.
Financial organisations have long used this type of tool to ensure customer satisfaction and loyalty. Conversational predictive analysis also enables them to reduce cases of fraud; depending on the terms used, the silences or the hesitations of the person speaking, it is sometimes possible to identify false statements.
Data exploitation has always been at the heart of the insurance sector. This enables customer risks to be more clearly defined, in order to offer more appropriate services and products. Like banks, insurance companies are using conversational predictive analysis to detect and anticipate fraud. It also helps them to become more efficient at handling claims.
Applied to the retail sector, conversational predictive analysis helps to improve the customer experience thanks to a personalised approach based on the data collected. These exchanges also allow a better understanding of the customer’s preferences, in order to adapt offers to their needs at the time.
The telecommunications sector uses conversational predictive analysis for customer loyalty purposes. With optimal timing and a good knowledge of the customer, this marketing method can also be used by the salesperson for an upsell to increase the initial value of the basket.
Conversational predictive analysis offers a considerable asset to boost your sales and increase satisfaction among your customers!
