Content analytics of calls is one of the largest untapped data resources globally. It is a treasure chest on which companies sit without realizing its value.
At the same time, the wave of digitalization has swept across all industries, bringing with it new contact channels. The new channels were supposed to redirect customers to self-service channels and reduce the number of contacts, especially for calls, but what happened? Call volumes have dropped marginally and new channels have increased contact volumes tremendously.
Corporate management typically has three areas of interest:
The content analytics of calls has a direct link to each of the three points. That is why I call this area a treasure chest. The investment for the opening of this chest is repaid in a few months. This article presents these three areas through concrete examples.
Currently, the most common use cases for utilizing calls in business are listening to recordings related to service and product development, coaching, or dispute resolution. Concerning the settlement of disputes, the truth is found out very quickly and the benefits are immediate. For coaching purposes, on the other hand, a light sample of the agent's practices is obtained. For developing processes, products, or services it is not possible to obtain a representative sample by listening to the calls. When done manually, there is always a time-consuming and expensive process ahead, which is also impossible in larger companies.
"We have a mandatory call categorization before customer information can be closed." This is a common practice in call centers and at its best, it gives a top-level direction on what things make people call customer service.
However, this information does not provide an answer to the question of why this topic is increasing call volumes. In our experience, we can state that one of the most common call category is “someone else”. This gives the agent a quick way to move forward in their work towards their daily call goal.
Utilizing the technology, quick wins can be sought by automating the existing classification process. Automation speeds up customer service work and the accumulated time savings can be easily calculated as monetary value. At this point, it’s a good idea to stop and ask three questions; which businesses utilize classification information, in what roles is this information needed, and why?
So, does automating the current call categorization process provide significant value and competitive advantage to the business?
Our experience shows that significant value arises from identifying all topics that appear in calls in real-time. When the contents of the calls are clear in addition to the development of operations, we´re also able to cover the topics that burden customer service. We better understand why customers call to us and how we can influence it.
In best cases, our customers have been able to significantly reduce call volumes and this change has been permanent.
The task of the customer journey is to describe the customer's entire purchasing process from identifying the need for the purchase and the subsequent activities. The customer path includes all contact points where the customer is in some way in contact with the company. The customer journey thus brings with it the context behind the calls to be analyzed.
However, the customer journey cannot be made visible based on the content of the calls alone. This requires carrying call-related background information with the call information (metadata). Metadata most commonly contains the following information:
The above serve as examples and are therefore not an exhaustive list. Metadata and their meanings in business vary according to the company's operations. As operations evolve, metadata also lives with this change.
The combination of metadata and themes identified from the calls creates a view of the weaknesses of the customer journey. Where on the customer journey do customers drop out and on the other hand, what topics directly affect the churn? In predicting the churn, the topics of the analyzed calls can be brought back to the CRM system, for example.
Measures taken in the field of product and service development are reflected in real-time in the contents of customer calls, this immediate feedback enhances development work and focuses on the right place on the customer journey. A concrete example of this was provided by Stockmann, which utilizes Aiwo.
Sara Toivakainen, Stockmann's Director of Customer and Employee Experience Development, says the following about the cooperation:
Our team was able to react quickly and extend the reservation time. Very soon right after the change, they were able to see from Aiwo that our customer experience was improving in real-time. We didn’t get the feedback regarding the reservation time anymore. That was very impressive! We noticed the issue from Aiwo, we were able to react and take action right away. And after this, we could say that it had an impact.
As services and products meet customers' needs in the right service channels, the average purchase per customer starts to develop in a positive direction.
By cutting call volumes, significant savings can be achieved quickly. If cutting call volumes and directing customers to self-service channels were easy, it would have been done ten years ago. Companies have been chronically pained due to a lack of understanding because there has been no visibility into the content of the calls. However, technological developments have taken great strides and made possible the creation of the Aiwo service, for example. In addition to the Nordic countries, Aiwo is currently helping companies globally, all the way to Australia.
Failure demand and its understanding come to the fore when it comes to influencing call volumes. According to Professor John Seddon, who introduced the concept of failure demand 30 years ago, failure demand is always a signal of inefficiency. It is not uncommon for up to 80% of demand from service organizations to be failure demand. Failure demand is also a sign that current customer satisfaction measurements are often misleading.
Failure demand arises when a customer receives the wrong service, no service at all, or only partial service. Failure to serve the customer will cause the customer to come back with additional requirements. The customer is dissatisfied, the organization is overwhelmed, employees get tired and costs go up.
The content analytics of calls creates a mandatory basis for effectively modeling the share of failure demand burdening the company in the total call volume. When a company identifies the topics and themes that drive failure demand to customer service, it creates the ability to take development measures that can easily have a saving effect of millions of dollars in large companies.