Your customers are in control. They demand a personalized, accurate, and fulfilling journey with your enterprise, whenever and wherever they please.
But what does it really mean to be customer-driven?
- being at the ready, at any time, with personalized, curated, and related content.
- a service experience that answers your customer’s questions accurately, and importantly, like a human being.
- anticipating your customers’ wants, needs, and desires, and guiding them seamlessly along your digital journey.
Sound impossible? It’s not. To be customer-driven is to be powered by artificial intelligence (AI).
But becoming an AI-powered organization isn’t as easy as flipping a switch – it requires a strong information architecture (IA) foundation in order to launch. In other words, there’s no AI without IA.
Aristotle Got Personalization Right 2,000+/- Years Ago
Over 2,000 years ago, Aristotle defined virtue as doing the right thing to the right person at the right time, to the right extent, in the right manner and for the right purpose. This is a lot of what we talk about in personalization. It is meeting someone’s needs, much like a concierge does.
In fact, AI is the programmed extension of that original idea –it serves up the right content, to the right person, at the right time, in the right manner and for the right purpose.
A major value proposition for AI is that it applies scale to well understood personal interactions, allowing companies to respond to many more customers in an appropriate, personalized manner.
AI Isn’t Really New
In fact, AI has been around for quite some time – we’ve just known it by a few other names. For example:
- SEO is AI: We’ve been organizing, tagging, and enriching web content for a long time for websites. Google search engine is AI-based. Google is constantly organizing content managing quality, structure, semantics, and metadata.
- Alexa is AI: One of the best-known AI-based systems is Alexa. One of its AI elements is natural language, but what makes it good is the number of skills or use cases that are in fact structured interactions driven by Information Architecture (IA) and content models.
Before Starting AI, You Must Perfect Your IA
Before you consider implementing AI, you should first consider the IA upon which it rests.
Preparing well organized data sets is not easy; it requires knowledge and content. Other required ingredients include a model data collection to capture an understanding of customers, and a model that can process that data and make predictions predict their future behavior. Information such as a person’s past purchasing history helps those predictions.
AI should not be thought of as a black box, but as a tool box. Many tools are available, such as neural nets, algorithms, supervised and unsupervised learning.
The key is to use the right tool for the right problem.
Another source of information for models is reviews, but those are most useful when they can be related to what the customer is looking at. All models need product relationships, information about what the customer has viewed, and what is important about a given product.
Curate Consumable Information
Once your IA is aligned for AI by organizing data and defining relationships, your efforts then need to focus on how the business itself is organized. The data domains required for AI, such as product development, marketing activities, and other content, are complex, with many different workflows.
Successful, AI-powered businesses are intentional about how they organize content around domains. Said another way, they purposefully curate consumable information that feeds interactions and provides value to their customers.
Look at issues like legal requirements for governance, ownership of content. Look at what the dependencies are among data elements and how information flows through the ecosystem. See it as a living, breathing system.
Your Customer Is Your Starting Point
Finally, the best place to kick off your AI initiatives is your customer journey, which includes your product engagement lifecycle, business data flow, and product information lifecycle. All of this disparate content and data needs to work together seamlessly to serve your customers.
Identify friction and touch points along this journey, with a mindful eye on interactions, roles, and personas, and identify the technology needed to support that information.
- Simplicity is hidden complexity. Make it easy for the user by doing the work behind the scenes.
- Identify user journeys, data sources, and data owners.
- Define governance, curation, and scalable processes.
- Clean data is the price of admission for AI.
- Knowledge-driven = AI-driven = customer-driven.
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