Editorial
The Gist
- Boosting engagement. AI chatbots offer efficient customer support.
- Streamlining data. Prioritize accuracy and accessibility for AI use.
- Navigating ethics. Recognize responsibilities in AI implementation.
The customer journey, ecommerce and the overall shopping experience has already been forever changed by artificial intelligence (AI) and machine learning. After all, most of us are not surprised to see personalized recommendations pop up along the digital journey. The sites we visit and apps we use know our buying histories, our preferences, our search indicators and more. And that intelligence is used to provide us with custom experiences so that we click that buy button one more time.
Chatbots can answer our questions with accuracy, as long as we know what to ask and how to ask it! And now AI tools are introduced to the employee journey, to assist contact center agents with dynamic knowledge banks and salespeople with AI-empowered customer relationship manager (CRM) tools.
The future holds even more promise. Supply chain inventory management will automatically stay updated and fluid thanks to AI. And customer feedback insights will drive faster change as the feedback tools themselves become smarter and able to create plans of action.
It’s exciting to consider all the possibilities. But we can’t let the machines lead the way completely. Customer experience leaders can lead with strategy and leverage these tools.
As you consider introducing or expanding the scope of the tools available, be sure to address these questions.
1. What Problem Do We Want AI to Solve?
Typically, AI is part of the solution, but not the exclusive answer to a problem. For example, introducing a smart CRM tool that uses AI so salespeople can access personalized information about prospects won’t be useful if the sales team isn’t trained on how to use the information. The wrong approach can feel intrusive or aggressive to potential customers.
The entire customer journey should be proactive, intentionally designed and aligned with the promises made to the customer. If a tool is just unleashed without context, the power of information may actually do more harm than good to the customer relationship.
Machine learning means the results should get better, but machines aren’t the only ones who will be learning. Have a plan for training, coaching and updating processes and communications accordingly. Define the problem to solve first and know what success looks like before launching AI into the journey.
Related Article: How AI-Driven Data Enhances CX
2. Is Our Data Structure and Access at the Right Levels for AI?
It’s true what the old saying predicts: garbage in means garbage out!
Many organizations still struggle with accurate, connected and transparent customer data. If the data in the system is not working today, adding AI to the mix won’t magically make it better. In fact, the system will “learn” based on the data it receives, so ensure the data is accurate and access is at the right levels.
Customers on the receiving end of a bad chatbot experience are typically frustrated by the robot’s lack of knowledge about them and their customer journey. This is often because the customer data is not centralized in a way that “sees” the customer in the right way. If your chat history is stored separately from your purchase history and your contact center agent can’t see any of that anyway … you can see how even robots can’t reconcile that experience.
There are certainly tools available that can help organize and correct data, but know what you’re working with before jumping into the wrong data lake!
Related Article: Transforming Ecommerce With Artificial Intelligence & Machine Learning
Learning Opportunities
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ChatGPT and the Future of Conversational AI
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The Evolution of Employee Listening - 2023 Trends & Best Practices
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The Future of Social Media: Emerging Trends and How to Stay Ahead of the Curve
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The Building Blocks of Personalization
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The Future of Contact Centers with AI at the Helm
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30
ChatGPT and the Future of Conversational AI
This discussion explores various aspects of AI implementation, ethical considerations, and challenges for your organization.
Webinar
May
31
The Evolution of Employee Listening - 2023 Trends & Best Practices
Learn proven effective methods and solutions to supporting an inspirational future of Employee Voice
3. How Can We Watch out for and Avoid Bias?
Humans aren’t always great at recognizing our own biases. I once worked with a client who described their up-and-coming customers as a diverse, younger group. Yet when designing the “new” website, every single image representing customers was a white man in his 60s. They didn't see this themselves — I had to have that awkward conversation. Once they saw it, they recognized it in many other communications. Awareness can go a long way, but it takes time.
And when machines learn from us as flawed humans, they develop the same biases, unfortunately.
There are now tools and best practices around introducing the right training data sets and ways to test, as well. Customer experience leaders should be asking these questions so the entire customer journey is as inclusive and representative as possible.
4. What Are the Ethical Implications and Responsibilities of Using AI?
Customers deserve transparency. Define what is expected around revealing when AI is in use. Tell the customer when they are chatting with a bot, for example, versus an agent. And define what information is used and when.
And if customer information is provided due to a specific circumstance, like resolving a customer issue, then train and discuss the ethics of confidentiality around customer data.
There will be hiccups and disagreements. So it’s a great idea to either include an ethics subcommittee or task force within your customer experience team or encourage an organizational-wide ethics committee to address these sticky issues. Leaders may want to consider a special feedback process for employees and/or customers to report issues. This feedback can be evaluated and addressed as part of the ongoing training and communication with employees.
5. What Are the Future Uses and Benefits to the Customer Experience?
AI is here and the adoption of it is speeding up at a record pace. Customers will see it used in many parts of their lives. They will expect experiences that are personalized and predictive. Automations will speed up response times and problem resolution.
The exciting part of this technology is how it learns and grows to fit different situations. So now is the time to start thinking about the future. What COULD be possible?
What parts of the customer journey are currently not ideal? Could AI help improve the overall journey?
Where do employees get stuck? Do they have trouble finding the right information at the right moment? How could AI assist them most when they need it?
How do our internal processes negatively impact the customer experience? Could connecting data like supply chain updates and predictive analytics better serve the customer and the organization?
How can we provide more self-service options for customers? Customers want choice and self-service tools are in demand.
What does the definition of “seamless” look like in the future? What if we didn’t have to force a customer through one channel at a time? What if their order and purchase information was always accessible and updated proactively for them?
Identify what you WANT the future to hold. Then define the steps and tools and technology to help you get there.
We are at the dawn of big changes, and as customer experience leaders we have a role to play in shaping the future. AI can help us do our jobs better, deliver more for customers and create an improved employee experience. Now is the time to define what’s next.
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