Customer journey in the contact center: the importance of predictive analytics. One of the most important challenges that any contact center company faces has to do with the relationship with customers throughout the entire purchase process (or Customer Journey).
Throughout this process, users make decisions and modify their purchase decision. And this is something that must be taken into account by contact center agents, not only at the time of getting in touch: the information and the data set must be previously collected and analyzed in order to precisely know their needs and anticipate their purchase decision.
In the midst of the digital age, with the large volume of data coming from so many sources and through so many contact points and formats, delving into it and turning it into information that can be used to benefit the customer experience is essential. And this is where predictive analysis comes into play. What is it and how does it impact the Customer Journey? Keep reading!
Customer journey: what is predictive analytics?
As its name suggests, is the analysis of data to make predictions. Predictive algorithms allow you to accurately predict events before they happen. But this prediction does not happen by chance, it is based on the analysis of historical data and current data, thus managing to identify behavior patterns.
To be carried out, different techniques are used in data analysis, such as:
- Machine learning: thanks to it, call center companies can identify new areas of interest in real time. For example, in channels such as social media.
- Data mining: Refers to the process by which the analysis of a large volume of data and patterns of the buyer persona (or user persona) is carried out.
Customer Journey: how does a good predictive model help in the user experience?
Predictive analytics in a contact center is very important. Mainly, because it is a very powerful tool to identify and retain potential customers. In addition, it allows agents to anticipate situations in which users are likely to lose interest in a company’s product or service and become lost customers.
A good predictive analytics, therefore, helps contact center agents to react quickly to possible changes in user interests in the different phases of the customer journey.
Customer Journey: how to collect information with predictive analytics?
In the midst of the digital age, technology and new digital tools become essential in the day-to-day life of agents. To give an example, the integration of a chatbot in contact center software allows quick and automatic responses to user questions and requests.
Although it is true that predictive analytics is a relatively new “tool” in the sector, more and more companies are betting on it for, for example, sales campaigns.
Some of the most effective ways to collect information for this predictive analysis are:
- CRM (Customer Relationship Management): Integrating a CRM into contact center software has many advantages. This system allows knowing and recording user information and establishing specific criteria based on data to interact with them. In this way we manage to increase the chances of closing the sale or solving problems with greater agility.
- KPIs (metrics): their analysis allows a contact center to know which touch points generate more or less performance throughout the customer journey, allowing them to promote those channels that generate more performance (email, social media, incoming calls, etc.) .
Discover our software EVOLUTION, for exceptional customer service
A contact center software such as EVOLUTION from ICR Evolution helps your company analyze the consumer experience and establish a mapped customer journey. In this way it is possible to understand, at all times, how consumers think on each of the touch points.
