Название | The AI-Powered Enterprise |
---|---|
Автор произведения | Seth Earley |
Жанр | Программы |
Серия | |
Издательство | Программы |
Год выпуска | 0 |
isbn | 9781928055525 |
AI can be a powerful way to contextualize the customer experience by seamlessly serving up the information, products, services, and solutions they seek, but it cannot make sense of bad data and it cannot substitute for an understanding of the customer. AI cannot make up for your sins of poor information practices and bad customer experiences. Some of the tools can help, but they need a structure, a scaffolding in which to operate and in which to contextualize information. Successful AI programs require that the organization has its data house in order and that it understands what customers and end users need.
The Promised Land: Applying the Ontology
There are thousands of ways to apply an ontology.
There is a sculpture on my desk (the inspiration for the cover image on this book) that represents the infinite ways of applying an ontology while also representing the structures within it. The piece is made of glass of varying types with different refractive characteristics. There is an easily seen cubical structure within it; it is complex but not mysterious. But when light goes through the sculpture, it creates infinite representations of that light. The ontology is the cube. The ways of using the ontology are the light that goes through it. It changes depending on perspective but in predictable ways. It is infinite in its output but made of a finite number of elements.
The ontology is the foundation of language and business terminology and concepts that are important to the organization. It becomes the knowledge scaffolding and reference point for building various applications and powering AI tools. It has to be designed into the downstream systems and be the starting point for any data definitions. For example, it contains the lingua franca and golden record for product information in an ecommerce system. It does not always house the product information, but it holds the categories of products that would also be used in marketing tools, in customer engagement applications, in analytics programs, in internal knowledge and content bases, and so on. It can be used in search to provide conceptually related results that might otherwise come from a reference librarian. Every information system should begin with consistent language, concept relationships, terminology, and organizing principles; the ontology supplies these.
Now you know what an ontology is. What’s it good for? We’ll explore the uses of ontologies in many contexts in the chapters that follow, starting with the way an ontology improves the most fundamental process of any company: delivering an excellent customer experience.
TAKEAWAYS FROM CHAPTER 2
In this chapter, I’ve described what an ontology is, how it’s useful, and how you can create one and put it to use to power your enterprise. These are the main points in this chapter:
•Ontologies help deliver the right information at the right moment, faster, and more accurately, which will give you an edge in the battle for customers.
•An ontology describes all the knowledge and data within your company and the relationships among different concepts.
•The main building blocks of ontologies are taxonomies—hierarchical classifications of various domains of knowledge.
•Ontologies power AI capabilities like chatbots by delivering a core understanding of the business problem and a mechanism for identifying reference signals within the company’s data.
•To be valuable, ontologies must reflect the architecture of the data within a company.
•Creating useful ontologies demands a careful, deliberate approach—you can’t just turn a machine loose on your data; nor can you stitch together “accidental” taxonomies that have developed throughout the business.
•Ontologies vary across industries and are unique for every business.
•One of the best ways to develop an ontology is with a nine-step user- and problem-centric approach that includes identifying problems, collecting them into themes, and developing solution scenarios.
•You can enhance ontology development by adding a data- and content-centric approach—for example, interviewing employees about the various data elements they use and how they use them.
•An ontology isn’t done until it has been tested for validity and with actual user scenarios.
•Once created, an ontology can power a limitless number of AI-driven improvements within the business.
CHAPTER 3
CUSTOMER EXPERIENCE: THE FRONT LINE OF THE BATTLE
What is customer experience? What makes it good . . . or terrible? Let’s take a look at three experiences I recently had with different companies. In each case, ask yourself, How did the information systems or data within these companies create—or destroy—the opportunity to deliver an experience that would make me a loyal customer?
Experience the first: I needed to clean my granite countertops. The local store stocked only the brand I didn’t want. I found an online retailer that stocked the brand I wanted and I purchased a bottle. Unfortunately, the online retailer delivered the same undesirable brand stocked at my local store. When I called to complain and say that the return was not even worth my time, the service rep assured me that it would not take any of my time: UPS would come to pick it up with a label and all I had to do was give them the package.
When I put the package out, my local mail carrier (USPS, not UPS) tried to help by taking it. When UPS showed up, the package was gone, so they did not leave the label. Then the post office called to tell me I had to pick it up or they would throw it away. I drove to the post office, picked up the package, and then called UPS—spending 30 minutes on hold and leaving a voice mail—only to receive a callback from a rep who told me to call the retailer and promptly hung up the phone! Somebody at the retailer emailed a label, and I then had to find a drop-off location for the package after I printed the label. It took four hours of my time to process a return for a $12 purchase.
In this instance, the breakdown in customer experience happened at many points in the process. There were data issues at the point of purchase, a lack of clear explanation of the process, a breakdown at the local post office, and a disconnect at UPS. Do you think I will go back to that online retailer?
Experience the second: I received a mortgage refinancing offer from my bank. It was a great deal. But I was already in the process of refinancing with the same institution, a process I’d started a month before I received that particular offer. The bank’s marketing organization was trying to sell me something that I had already purchased.
Experience the third, which restored my faith in companies’ ability to do customer experience properly: My wife is an avid cook, as well as a fan of any and all quality cooking tools. I had heard good things about Kamikoto chef’s knives, but I assumed they were very costly.
I clicked on an offer in my Instagram feed and found a deal for a Kamikoto knife set at a savings of several hundred dollars. This engaged me enough to take the next step and continue exploration. I researched the knives a bit more by reading web reviews and comparisons and decided to buy them for my wife (okay, they were really for me). The purchase process allowed me to use my Amazon account, which made it simple since Amazon already knows my credit card number and shipping address. After the purchase, the retailer enabled me to track my shipment (text or email) and a mechanism for returning it for any reason to reinforce the wise choice that I had made to purchase these fine knives.
The knives arrived in a beautiful wooden display case, along with certificates of authenticity and information about the history of the company, its manufacturing process, the high grade steel