Artificial Intelligence has become a buzzword over the last two years and there has been good development around it as well. However, customer experience still hasn’t seen any drastic improvement. The reason often stated is that automation lacks creating an atmosphere of emotional engagement which is a must for positive customer experience. This is where artificial intelligence is going to come to our rescue. AI-enabled technologies can help us understand customers at a deeper level, and predict what they really want, helping us craft campaigns and product experiences that lead to better customer experiences.
Let us take a look at how you can start using artificial intelligence quickly and easily, in order to enrich the customer experience.
Implement AI-enhanced customer service
Artificial intelligence-enabled tools process gigantic amounts of data to quickly understand the situation and history of a customer, helping customer service agents to respond accurately. In addition, customer service enhances customer experience only when it is available 24/7, on all channels. Only artificial intelligence can make that possible for you in a cost-effective manner via chatbots and virtual assistants.
Here are some specific uses of implementing AI-enhanced customer service:
Use case: CIMB Bank now offers 24/7 customer service by integrating EVA, a Chabot-enabled mobile app. Bank customers can perform a number of activities such as transferring money. paying bills, checking balance, etc. The bank could reduce its dependence on human customer service agents, and also provide 24/7 customer service.
Point to note: AI can be used independently if you cannot afford an in-house customer service team.
Consider AI-assisted after sales support
From Internet of Things to predictive analysis, after-sales support is rapidly changing in recent years. Thanks to artificial intelligence and the many technologies that fall under this bracket, implementing after-sales support is easier than ever. Internet of Things-enabled devices can help provide predictive product support, thereby enhancing customer experiences.
Here are a few situations when you can use IoT-enabled after-sales support:
Use case: Syncron Uptime is an IoT-enabled product by Syncron, which helps manufacturers to provide after-sales support. The technology helps identify when a product will require replacement or repair, by tracking equipment in real time. It uses sensor data to identify malfunctioning and other anomalies, and help manufacturers respond before the customer has knowledge of something going wrong.
Point to note: If you provide services rather than products, you can use textual analytics to process natural language on social media or email to identify what your target audience wants.
Invest in intelligent data analytics
While older data analytics tools only processed data and generated reports, AI-enabled tools can unify various data sources and bring real-time insights to you. Most importantly, AI helps you put insight into its business context. Text analytics solutions are increasingly being used to identify patterns and predict outcomes and take action when required.
By using an AI-enabled data analytics tool, you can:
Use case: Nordea is a Swedish bank that uses an AI-based text analytics solution. The tool analyses hundreds of inbound customer communications every second and processes them intelligently. Each communication is forwarded to the right business unit, eliminating customer frustration. The tool can also be used to recognize customer churn and eliminate it.
Point to note: Customer behaviours are chaotic and their interaction datasets are messy. Data insights can bring discipline into an otherwise undefined and unchartered territory.
Understand your customers at a deeper level
Affective computing, a branch of artificial intelligence that recognizes people’s cognitive and emotional states, is expected to grow to a $41 billion industry by 2022. Apple, Facebook, Google, and other companies are currently working with affective computing specialists such as Beyondverbal, Affective and Sensay to bring facial analysis, emotion recognition, voice pattern analysis, and other humanizing technologies to software programs that run products and services.
Here is how you can implement effective computing in the coming months:
Use Case: Ford is working with Affectiva to bring AutoEmotive, an Automative AI, to its cars in order to prevent accidents and incidents of road rage. This emotion-recognition software uses AI to identify human psychological conditions such as lack of attention, rage, anxiety, etc. in order to take control over the vehicle or just stop it from moving.
Point to note: Implement a solid privacy and consent policy to keep yourself safe from litigations, and protect your customers as well.
Focus on the humanization of customer interactions
A monogamous relationship with AI may spell doom to your customer experience strategy. Nearly 50% of those interviewed in a survey expressed that they would prefer if AI-enabled interactions were more human-like. While AI has obvious benefits of cost reduction, efficiency in customer service, and access to valuable insight, it may reduce customer experience unless you humanize it as well.
Here are a few tips to humanize an AI-enabled customer support strategy
Use Case: Amtrak’s Julie is a virtual assistant that uses natural language capabilities to humanize interactions. The virtual assistant also has a wide knowledge of Amtrak’s official website, and guides users while making reservations, finding reward programs, and provides route information. Julie can vocalize her written answers too, for those who prefer a more human-like interaction.
Point to note: Real human interactions are important in enhancing AI-enabled customer service and they are not mutually exclusive.
Implement AI to make your customers happy
As you can see, implementing artificial intelligence can quickly lead to enhanced customer experience, and doing so is well within your reach. Start with investing in affordable and scalable AI-enhanced customer service tools such as chatbots. Implement IoT and predictive analysis-based technical support and after-sales support in order to fix issues before they occur, and surprise your customers with top-notch support.
Use advanced data analytics to understand buyer personas and to predict consumer behaviour. Understanding your customers at a deeper level will help you improve customer experience metrics rapidly. Finally, focus on humanizing your customer interactions, as a majority of customers still want to cherish enriching human interactions. Artificial intelligence helps you humanize your customer service by personalizing data and giving you insight about each individual customer.
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