Did you know that artificial intelligence can bring countless benefits to your customer service channels?
And we are not talking about case studies far removed from the reality of most companies, but tools that optimize the customer experience and help your business grow in a scalable way adapted to the constantly evolving world.
What is artificial intelligence (AI) in customer service?
Chatbots are the most common example of artificial intelligence in customer service. Other examples are automations and self-service services, such as virtual assistants with different learning capabilities, including natural language processing.
Basically, those are processes and tools that make the day-to-day life of professionals easier, increase ROI, while raising customer satisfaction. It uses technologies such as machine learning to optimize services and operations with little or no human interference.
There are many ways to apply it, but in general, solutions are able to respond to customer questions and occurrences in an agile manner and participate in sales strategies. One of the applications of this technology is a voicebot that goes beyond answering frequently asked questions (FAQ), providing self-service to customers.
That means: instead of guiding the consumer "type x to talk to y", it can process the person's natural language, understand the problem and offer a solution. All without the customer having to navigate through complex menus, go through contact centre staff members and, best of all, the tool learns independently with each call.
How artificial intelligence (AI) can streamline customer service:
When well developed and implemented, artificial intelligence can streamline customer service through the following benefits:
As we have exemplified in our blog, an omnichannel strategy implies that your company is where the customer is and that customer services are the same, regardless of the channel. At this point, integrating apps and platforms comes into play to make customer support work like an orchestra.
- Queue coordination and management: customer requests from all channels unified in order to establish priorities and enable staff to plan their time.
- Contact history: the customer service agent can see past interactions with each customer in seconds. That allow opportunities for loyalty, retention, up-selling and cross-selling.
2. Process automation
What if your voicebot could proactively make calls to provide the best post-purchase support and even run an onboarding process on its own? Automating processes helps you save time and money, as well as being able to participate in sales processes.
In some cases the contact happens reactively. When that happens, the service agent already receives the reason why the problem occured even before talking to the consumer. Using a platform for process automation avoids repetition and makes your team better trained to respond to market demands.
3. Decrease or even the end of waiting time
Adopting a conversational answering solution promotes the resolution of incidences 24 hours a day with no waiting time for service. The AI handles low and medium complexity calls. While high complexity calls can go to the dedicated service team to solve specific problems, make new sales or even avoid losing customers.
According to a Gartner article, one company reported that its bots responded to customer requests in estimated 5 seconds, while traditional services took 51 seconds on average.
4. Integrated data processing and analysis
Every customer contact generates data. AI-powered engines can collect and structure this data, creating dashboards and reports for identifying improvement points and opportunities.
You can generate exact metrics such as number of outbound calls, percentage of cases successfully resolved, successful cross-selling and upselling opportunities, customer satisfaction and even return on investment.
5. Constant Learning and Evolution
It is no accident that the technology is called artificial intelligence. Just like humans, solutions that use machine learning have a certain independence of learning. To explain further, this type of solution works from a neural network, which we call deep learning.
With several layers, this network simulates the behaviour of the human brain to learn from large amounts of data. This way, in customer service-oriented applications, it is possible to improve the automations performed, through the performance of analytical tasks, without any human intervention.
User Cases - Omilia, AI applied to large-scale financial and telecom customers
One of the largest financial institutions in Portugal has a virtual assistant that answers over 4 million calls per year from over 2.2 million customers. Omilia was developed and implemented in the company in just 12 weeks. Today she serves all IVR channels and all segments of Caixa Geral de Depósitos' private customers.
The results are thriving: the retention rate increased by 20% in the last quarter of 2021 alone, while negative feedback was reduced to less than 1%.
A telecom company Kcell has gone ahead of the curve by betting on a virtual assistant so developed in 2017. Omilia was applied to answer call centre calls, and chatbots were developed for text-based services. The technology recognises more than 100 categories and sub-categories of requests and provides end-to-end self-service.
There are many ways to use artificial intelligence to improve customer service for your business.
GrupoGBI offers voicebots and chatbots solutions that, when implemented, can improve your company's processes and deliver many advantages to the customer. As a result, your client will be satisfied with your service. The chances of customer loyalty are very high!