Customer success is a concept which refers to attaining solid retention and growth through a system which is customer centered. According to Hubspot, a leading company in the space, ignoring customers as a way to grow your business is a mistake. This is why the main goal is to successfully build strong long-term relationships with the clients and therefore increase the overall customer lifetime value (CLTV) while empowering customers and customer success managers.
Performance measurements are necessary to evaluate the success and efficiency of any type of activities conducted by a company.
This is where Key Performance Indicators are vital, even though one must consider that KPIs importance varies across sectors, organizations and business models. Statistical knowledge and a deep understanding of the sector is necessary to make the right predictions on KPIs, draw the right conclusions and implement a new strategy.
What KPIs does AI affect?
When it comes to Customer Service, many are the KPIs that support teams keep under control to monitor their ability to provide outstanding experiences to their customers.
Artificial Intelligence can impact many of them, but the most affected are:
- Average Response Time
- Average Handling Time
- Customer Satisfaction.
Let’s have a look more in detail at each of the 4 KPIs mentioned.
Average Response Time is the amount of time it takes on average to respond to a requested inquiry. ART is usually affected by the number of tickets submitted, the average think time and the dimension of the network.
One way Artificial Intelligence can impact ART is by automating email or chat replies in real time.
It is nowadays possible to train an AI model on your historical data, so it can understand the meaning of an incoming customer request and respond automatically based on how human agents have replied to similar tickets in the past.
This can cut the ART down to mere milliseconds, both when it comes to emails and chats.
Average Handling Time is commonly used in call centers to identify the total amount of time spent talking, plus the after-call tasks performed by agents including the duration of hold up, all divided by the number of total calls.
According to Zendesk, AHT differs depending on a company’s approach to the customer experience and the product they sell. In addition, companies should understand that a low AHT is not necessarily indicative of an efficient call center. The time should not be high, however, customers’ issues should be addressed with the right amount of help, even if in some occasions, it might raise AHT a bit.
AI helps in reducing AHT thanks to the ability to identify call-types and redirect customers to the right agent or to the possibility to replace manual canned replies selection processes by giving intelligent suggestions to the agents.
These intelligent suggestions free up agents from simple, redundant macro search and application. Companies can reduce AHT by 30% using AI-powered automated suggestion replies.
Productivity AI can help in increasing productivity while at the same time improving the rate of customer satisfaction and all that with fewer expenses. As mentioned above, the ability of AI to suggest relevant macros reduces the time taken to resolve the issues.
CSAT stands for “Customer Satisfaction” and it is measured using a scale from 1-5 where 1 is considered as very unsatisfied and 5 very satisfied. An average is computed and the CSAT score can be presented in a percentage scale with 100% standing for complete satisfaction and 0% standing for dissatisfaction.
As a consequence of improving Average Response Time, Handling Time and Productivity through AI, CSAT is also improved.
AI is already changing the way of how companies address Customer Service, there is no doubt about it.
AI has the ability to generate a huge competitive advantage: it is cheaper, more accessible and thanks to its algorithms, which are always improving, it gives relevant inputs that positively affect Customer Service KPIs.
At the same time, AI allows to process a large amount of data through machine learning algorithms This helps to discover and define new patterns and trends difficult to see with a “naked eye”, allowing customer support leaders to increase team productivity and deliver better customer experiences.
Without a doubt, AI is changing how companies provide CS and deliver CX, and the business KPIs for support departments already is, and will definitely be, positively affected by the rise of AI.