The demand for superior experiences, including seamless omnichannel availability and personalization, has made it challenging to stand out from the competitive crowd.
There was a time when a great customer experience was a competitive advantage. With research showing that the vast majority of companies (81%) compete almost exclusively on CX, it’s moved from differentiator to table stakes.
Consumer expectations aren’t letting up, either. The demand for superior experiences, including seamless omnichannel availability and personalization, has made it challenging to stand out from the competitive crowd.
Worse, how we traditionally measure customer satisfaction falls short in providing clear and actionable direction. Research from the University of Cambridge indicates that the two most common quantitative measures - Net Promoter Score (NPS) and customer satisfaction (CSAT) don’t provide organizations with information about what customers really think and feel.
Where numbers fall short, though, modern technology bridges the gap. Today, artificial intelligence and machine learning are making it possible to not only understand customer thoughts and feelings better but can provide individualized experiences and even direct messaging to meet consumer needs and organizational goals.
Chatbots are currently all the rage and with good reason. They provide an avenue for the self-service that customers desire and reduce the load on human customer services and support agents. However, AI makes these programs far more useful than the simple, scripted bots of a few years ago.
Backing your chatbots with AI means that customers can have dynamic conversations with questions and answers based on information about the individual. Greetings and order information can be personalized, and solutions offered to the customer in a predictive manner. Plus, chatbots can be integrated with process automation, making everything from order placement to returns streamlined.
The ability to personalize communications - in a limited way - has been available for a long time. Consumers are no longer satisfied with having their first name inserted into a marketing communication or receiving a list of products that "other shoppers also browsed." With the expanding choices available as both B2C and B2B consumers, advanced CX needs to let customers know they truly understand them not as a persona but as a person.
AI enables companies with hyper-personalization. From content delivery that is relevant to the customer based on previous interactions and purchases to creating individualized experiences, artificial intelligence is allowing companies to adapt to what one single customer needs or wants.
Take an example that nearly all of us are familiar with - Netflix. The homepage for the streaming service is different for every single subscriber. Hyper-personalization is at the core of the Netflix user experience - it combines watched content, browsed content, preferences, and more to develop precise recommendations of the more than 15,000 titles in its library.
Traditional fraud protection isn't always effective for e-commerce. For instance, in the past and with simple, rules-based fraud engines, a card not present (CNP) transaction is evaluated based on flags like location, order size, etc. However, many of these indicators could reject a genuine purchase, auto-declining a good customer and creating frustration and abandoned purchases. Nearly 90% of auto-declined orders are legitimate.
Using AI, fraud detection and prevention applications can better assess a transaction for risk. For instance, ClearSale, a global e-commerce fraud prevention platform, leverages machine learning to evaluate orders on a range of factors and adapts to a merchant's unique fraud profile. The company stands as an example of adaptive AI for customer experience combined with human intelligence - when a purchase is declined, it is passed along to an in-house fraud specialist for review.
Some customers will have issues that a chatbot can't resolve. Human agents are still a crucial part of the CX process, but those agents can be better prepared to help customers with the assistance of artificial intelligence.
By analyzing a host of factors, including past experience, language choices, chatbot inputs, order history, and more, Salesforce’s Einstein in Service Cloud can better route calls to agents who are able to help customers without repeated information or multiple transfers. Plus, sentiment analysis can suggest the best responses to the customer in real-time, even during an ongoing conversation.
AI systems have long since left science fiction behind and become commercial fact. What's relevant now isn't that AI is here but its wide availability for companies large and small. These algorithms aren't here to replace humans but to help guide and elevate the work of humans by processing the available information - like customer sentiment and purchase activity - at scale.
Six Consulting can help you bring the power of adaptive AI to your business. Contact us today for more information on how you can leverage the power of AI to advance your business and excel at the customer experience.
compete almost exclusively on CX, it’s moved from differentiator to table stakes.
that the two most common quantitative measures - Net Promoter Score (NPS) and customer satisfaction (CSAT) don’t provide organizations with information about what customers really think and feel.
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