How AI is transforming customer experiences and the role of APIs
The true value of IoT lies in its ability to revolutionize user experiences, whether that is in your home, in the office, within your car or even as you walk down a sidewalk. Embedded sensors are generating the data that is powering a new revolution for business and their consumers — the power of customer experiences, or CX. As various industries face commoditization on a grander scale than ever before, CX has become the prime differentiator in driving differentiation and consumer purchases. Modern businesses must reprioritize around CX to optimize on costs and provide better user experiences, ultimately driving customer and brand loyalty.
Driving these deeper customer engagements will mean using technology to provide the data-driven capabilities that can revolutionize CX. This is where artificial intelligence comes in. Simply put, AI is the simulation of human intelligence processes by machines. This opens a plethora of new possibilities for enterprises, as AI is both scalable and efficient and can enable a business to automate repetitive processes that may be extremely time-consuming for a human employee to perform. By combining the extensive data capabilities of IoT with the data processing capabilities of AI, a business can truly understand the individual customers and craft a predictive customer experience, as opposed to traditionally reactive customer experiences.
These AI-driven experiences take shape in a variety of different ways. For example, AI in CX can come in the form of a chatbot, intelligent voice-operated system or even in AI-driven applications that can provide translation services and pertinent data directly to the customer. Other ways of using AI in CX include the transformation of more back-end services, such as using machine learning to process and customize data traveling to and from an enterprise and its customers.
How AI can transform CX today
AI is not a single technology, but rather a class of different capabilities that can be applied to many different functions and contexts. Here are a few use cases where AI can feed into your CX strategy:
- AI in natural language processing (NLP) based on speech recognition/synthesis. Natural language processing uses AI to “understand” speech requests using a combination of speech recognition and speech synthesis. Specifically, speech recognition technology is used to understand what the person is saying and speech synthesis is used to formulate a response. NLP can transform CX via the use of automated customer service and personal assistants. For example, enterprises can automate the customer service process to help customers book flights or troubleshoot problems by speaking with an AI assistant as if was another human. Apple’s Siri, Amazon’s Alexa and Google Assistant are common examples of personal assistants that use NLP.
- Using AI and machine learning to customize and predict outcomes. Machine learning can be used to train a system to handle requests around a variety of functions. Once trained, a machine learning-enabled system can ultimately be used to understand needs of the customer, customize interactions with customers or predict specific outcomes based on a set of defined events. For example, online music listening patterns and customer-provided data can be processed to curate recommendations of new music that is customized per user, resulting in a more predictive approach to CX. In an IoT scenario, connected device usage patterns and sensor data in manufacturing can be used to predict maintenance before a car or machine breaks down, enabling an enterprise to provide differentiated customer service.
- AI in image recognition. AI can process images to detect specific objects in an environment and enable other interactions. For example, a retailer can use AI via in-store cameras to analyze queues and the number of shoppers in the store, enabling the retailer to reduce checkout times by automatically summoning cashiers to help with checkout. Additionally, retailers can use in-store images to analyze gender, age, body type, style and other attributes in order to make personalized wardrobe recommendations.
Although AI isn’t the Holy Grail in remediating every problem faced by today’s enterprises, the AI technologies available today can prove overwhelmingly effective when used to transform CX and may be easier to implement that you think. Specifically, enterprises can begin infusing AI capabilities in existing applications that power customer service on mobile and IoT devices as well as via web applications.
Adding AI into your applications via APIs
Infusing AI into your existing applications isn’t as difficult as it sounds. By using application programming interfaces (APIs), enterprise and application development professionals can introduce AI capabilities into their apps without needing an AI-dedicated engineer or data scientist to manage the actual machine learning and data training process.
Major enterprise cloud vendors, such as Microsoft, IBM and Google, as well as a number of emerging vendors, are already offering a rich set of AI APIs that can be easily accessed from the cloud, enabling enterprises to easily integrate these APIs into existing applications and add AI functionality in use cases such as vision, speech, language and conversational assistants. For developers of IoT, mobile and cloud applications, all that is needed to do is “call” the API within an application to utilize these functionalities. For example, a natural language processing API can be used to automate actions based on certain written requests or to process and react to insights around historic customer interactions.
APIs provide a simple and easy-to-scale approach to integrating AI in your IoT applications and beyond. As today’s enterprises are facing a flood of new data from sources like mobile and IoT devices, infusing AI APIs in your applications may be key to ensuring unique and customer-centric experiences.
What’s next for AI in CX
Although AI is on its way toward being extensively used in the enterprise, customers of tech-savvy companies are already benefitting from AI use cases through the implementation of developer-friendly tools such as APIs. For example, we are already seeing AI-driven technology via chatbots, which have quickly become a staple of customer service in online shopping.
With the right approach and training, AI will continue to improve its ability to intelligently process data and drive automation. This, in turn, will help improve the state of CX as systems learn and adapt, enabling more predictive, personalized and timely customer service. To keep up with our increasingly digital world, it will be essential to consider how technologies like AI will help drive your CX strategy to differentiate and innovate in a competitive market.
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