Until recently, the analysis of the Customer and the Employee Experience was a laborious, costly and time-consuming process.
Today, through software equipped with artificial intelligence, especially those integrated with machine learning and deep learning technologies, companies can make decisions in a more targeted and fast way, with great benefits in managing the customer’s and employees’ experience and returning to business.
We talk about this with Federico Selle, Medallia’s senior solutions consultant, who provides the Medallia Experience Cloud solution, which shows us the four areas where artificial intelligence plays a key role in customer experience.
Feedback management, especially unstructured
All marketing professionals know that the relationship between the company and the customer is increasingly touching points of contact, generating a vast amount of data to be managed: artificial intelligence is crucial to analyze them effectively and in real time.
Moreover, today, a growing number of customers express their opinions through surveys, social networks and other forms of reviews.
These feedbacks, says Selle, are in written form, that is not structured and therefore impossible to analyse in a simple and scalable way, especially if the volumes are high.
On the contrary, thanks to artificial intelligence, techniques of text analysis and machine learning apply that categorize all these comments efficiently, grouping them together by topics and related sentiment.
Qualitative analysis therefore becomes quantitative, with the possibility of assigning metrics to qualitative data to understand the impact on the satisfaction of a set of comments related to a given topic. But also to combine this data with operational or financial information, to identify patterns and trends, risks and opportunities.
Artificial intelligence combined with machine learning can also predict future outcomes, starting from the processing of historical data and algorithms until the probability of certain results happening is calculated.
The objective, according to Selle, is not to stop at the analysis of the present reality, but to provide a picture of what could happen in the future.
Using predictive analysis software based on artificial intelligence allows you to know, for example, which customers will be most loyal to the brand and who will instead spread negative opinions.
This will allow preventive corrective actions to be put in place by reducing the criticalities and dissatisfaction (and therefore the rate of abandonment) or by strengthening the phases of the journey that contribute to loyalty the customer.
Analysis of customer sentiment
For companies it is increasingly strategic to know how customers make purchase decisions, what and how they finalise their purchase journey, but also what services, situations or proposals create greater satisfaction and which generate friction or even dissatisfaction.
Analyzing customer sentiment is very important because brands can understand what emotions drive certain reactions. In this direction artificial intelligence is becoming a key technology because it can distinguish Â more and more precisely between disappointment and frustration, approval and enthusiasm and allow brands to understand when and how customers express each other
In fact, it is possible to analyze the tone of voice, the facial expressions, from which comes detailed information on how they feel and, again, react more focused in building a more lasting relationship with them.
Priority for actions
Customers indicate what is positive and negative about their experiences with companies through hundreds of feedback, both direct and indirect, but leave valuable signals in all journalies or interactions with the brand.
Thanks to artificial intelligence all these inputs can be detected automatically to generate insight, which are distributed to all business levels according to a hierarchy of priorities for the person receiving them.
Federico Selle is thanks to the use of advanced customer experience management platforms that companies can obtain useful indications to know the actions with the greatest impact and consequently decide which areas to intervene immediately, and concentrate the majority of