CX leaders are embracing more powerful AI solutions which, for the first time, provide them with real-time visibility and understanding of the complete customer experience and voice of the customer.
For consumers, AI is ubiquitous. AI has become such an integrated part of the customer experience that we’ve stopped noticing that it’s even there. We rarely think twice before placing an order through Alexa or raise an eyebrow when we’re served a product recommendation that’s eerily relevant to our exact needs.
It stands to reason that AI is just as widespread in the CX departments of the businesses providing these experiences. Indeed, more than two-thirds (68%) of CX leaders are using one or more AI capabilities in their work. Yet 78% still aren’t satisfied with their ability to use data when managing customer interactions. There’s a clear gap in digitalisation plans. CX teams have been slow to leverage the latest AI tools for CX analysis and improvement.
The truth is, the use of AI in customer experience remains in its infancy. Yet the leading enterprises - those that want to provide the best, most personalised and responsive experiences - are taking the initiative and achieving some impressive results. Among the most digitally mature CX leaders, AI is expected to be the biggest investment for CX improvement, with a quarter (23%) placing it in their top five tech investments.
Here are three of the most important AI solutions helping CX leaders to understand and improve the customer experience.
Conversational Analytics and Communications Mining
Personalised recommendations, predictive offers and suggestions, tailoring the buying journey for the individual customer - these all depend on customer intelligence, knowledge of their motivators, preferences and behaviours. AI systems have been critical in collecting and analysing all this information in an efficient way. They’ve undoubtedly contributed to more relevant and satisfying customer experiences.
However, how are CX leaders building on this base? How are they improving customer experiences to deliver the most competitive offering? This has proven more difficult as CX teams brush up against the limits of customer intelligence.
To provide the best experiences, you need to understand the customer experience in its totality. But this hasn’t been possible with traditional analysis tools. Manual collection and analysis of customer feedback isn’t scalable. Sentiment analysis tools rely on broad brush keyword matching and can’t scale across most communications channels. They fail to achieve full coverage over the customer experience, and their accuracy can’t be counted on.
That’s why conversational analytics and Communications Mining have been a real gamechanger. Leveraging powerful AI and natural language processing (NLP), Communications Mining can extract the most important information from masses of communications data - at speed and scale, regardless of channel (whether that’s email, chats or even calls). You can see the drivers of customer demand and purchase decisions, identify the most costly customer issues. You can accurately measure the performance of promotions and, in their own words, assess how customers are responding to them.
Most importantly, conversational analytics gives you the quantity and quality of data needed to build business cases and improvement initiatives with confidence.
FARFETCH’s Voice of the Customer (VoC) team has used Communications Mining to gain full visibility into the VoC and customer experience. This has enabled them to make CX ‘real’ for the C-Suite, linking it directly with the company’s performance and revenue.
Find out more about the FARFETCH CX success story.
Chatbots and Conversational AI
Chatbots, also known as conversational AI, are a category of products used to deflect simple requests and workflows from customer service teams. They can automate simple workflows, such as answering frequently asked questions and processing basic requests like password changes.
The use of these tools has become increasingly pervasive in customer service. Whenever a customer wants to contact a brand, their first port of call - willingly or not - will probably be a chatbot. Customers have become accustomed to talking to them over the phone or chatting with them on the web. Their use has given customer service teams some much needed breathing space, reducing demand and freeing them to focus on more complex customer requests.
However, there are still some lessons to learn. Chatbots are, ultimately, a form of contact deflection. They block customers from the service teams meant to serve them. Chatbots provide faster service than human agents in certain circumstances, but not always and not all customers are satisfied with the experience.
It speaks volumes that at least 80% of customers have had a conversation with a chatbot, but that 54% expect chatbot interactions to negatively affect their experience and quality of life.
Chatbots are typically rules-based and cannot deviate from their fixed activities. They aren’t a solution that can succeed in every customer service function.
With the integration of more sophisticated NLP and machine learning capabilities, we may see the advent of truly human-like conversational chatbots. But until then, their use should be closely monitored and evaluated with Communications Mining tools. In the near-term, integration with conversational analytics solutions can improve their understanding of customer requests, the sentiment and intents behind them.
Customer Relationship Management
Customer relationship management (CRM) platforms have long been central to the work of CX teams. However, the integration of the latest CRM tools with powerful new AI capabilities is transforming what these platforms are capable of.
AI bots are removing the need for manual data entry in today’s CRM systems. Machine learning and NLP are able to understand and transcribe spoken conversations between agents and customers, automatically logging and categorising them in the CRM.
AI-powered voice analytics can accurately recognise emotional states just by intonations in the voice and changes in the pace of speech. Dissatisfied customers can then be automatically flagged by the CRM for quick follow-up by the customer retention team, protecting the customer relationship before it has a chance to churn.
AI is also playing a crucial role in improving data integrity. According to research, 91% of CRM data is incomplete, 18% is duplicated, and 70% is made redundant every year. Yet, AI can easily detect data errors and duplicates in CRM databases and, therefore, in customer relationships. It’s also able to interpolate missing information and update customer records in real-time as data changes and customers move through the sales process.
In short, AI is helping CRM be better at what it does best - centralising disparate customer data and providing insight into the complete customer lifecycle.
AI and Customer Experience Improvement
CX leaders are beginning to get to grips with AI and realise its full potential. AI isn’t just for automation and contact deflection, it’s advanced enough to provide full, real-time visibility into the entire customer experience. It’s giving them the insight to enhance the customer experience, capture the voice of the customer, and proactively intervene to preserve customer relationships.
