Executive’s View: The Future of AI in Customer Experience Management

Artificial intelligence is becoming a very common topic in business discussions. Recently, I was interviewed by Gérald Fillion who was hosting a special edition of RDI ÉCONOMIE on the practical application of artificial intelligence (AI) in business.

You can watch it here (in French), in case you missed it:

Image source: communiques.radio-canada.ca
Video source: RDI Économie Official Facebook Page

In this blog post I would like to expand on some of the topics discussed in the interview, with a special focus on how I see AI technology transforming the customer experience landscape, and businesses along with it.

From Text Analytics to AI Business Assistant

In the near future, several industries will be deeply impacted by AI technology, especially mature markets like telecom, banking, insurance and hospitality. These are industries where the differences between competitors are so minor, customers can easily switch between companies. 89% of customers leave without telling the company why.

Discrete signals that customers are about to leave are buried in open-ended survey responses, chat logs, reviews, social media messages and help desk tickets.

While most companies have this data, few are able to extract the relevant insights in time. In the not-too-distant future, prescriptive AI technology will automatically highlight insights and recommend actions that reduce customer churn.

AI to Accelerate the Customer Feedback Loop

Predictive & prescriptive AI will not only support an improved customer feedback loop, but it will accelerate it dramatically. The customer feedback loop principle is simple. You sell a product or a service, you ask the customer about their experience , they provide the feedback, you adapt your products/services based on their needs, their satisfaction level increases, thus preferring you over the competition. Easier said than done, especially for big companies. How can you truly listen to customers when there are millions of them? How can you separate the loud few from the silent masses? How can you follow up with relevant customers to see if you successfully improved?Your organization can already start implementing a true customer feedback loop using text analytics and take the first step towards the full potential this technology will evolve into:

Implement Continuous Feedback Opportunities

Listening to your customer begins by giving them the ability to communicate with you. They are more likely to provide feedback at key moments such as encountering a bottleneck or in close proximity to a transaction. Make sure you give them the opportunity to share their experience: on your website, in your stores, on social media. Currently, surveys are the leading way to collect in-depth feedback. Text analytics solutions are making surveys more useful than ever, by allowing companies to analyze free-form comments at a large scale.

AI technology will transform the way we use surveys. We already see companies implementing chatbots for basic customer service, but in the near-future the chatbots will conduct surveys by engaging with customers in a conversational way.

Collecting data through a continuous dialogue with the customer will produce high-quality data, filled with interesting insights.

Make Sense of Your Unstructured Data

Unstructured data is the most abundant type of information companies have access to and its analysis can yield valuable insights. However, every text analytics AI that supports customer experience needs to overcome a universal challenge: acquiring the relevant business vocabulary. To overcome the vocabulary challenge, most algorithms rely on human knowledge in the form of specialized dictionaries or ontologies. This method is not ideal because it takes a long time to adapt the system to a new company or industry. These databases of words also become obsolete quickly because products and services evolve and new features are added, so constant maintenance is required. Using AI that learns by itself what words are relevant is the only scalable, future-proof way of keeping up with constant feeds of customer comments.

Identifying Business-Relevant Insights

One of the big challenges facing text analytics technology is the ability to provide actionable insights that go beyond automatic dashboards. This will change very soon with prescriptive AI capabilities.

Text analytics reduces the time from data to insights considerably, but future AI solutions will minimize the time from data to action.

Based on the analysis of behaviour patterns, the AI will be able to identify early signs that a customer is about to leave. The AI will suggest a personalized course of action to prevent individuals from leaving and help the business turn displeased customers into devoted customers. While planning and coordinating at this scale is unthinkable for humans, it will be possible for machines to achieve it.

Beyond Text Analytics

As highlighted above, text analytics can already provide a competitive edge in its current state. Moving forward, the same AI technology will evolve into a tool that can assist the business process with predictions and recommendations.

AI will become indispensable to customer experience management as the only scalable way to deliver personalized customer experience.

Finally, I leave you with this question… will you stay up to date with the latest trends or will you let your competitor be the first to adopt this technology?

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