Let’s get personal: Creating a more personalized customer experience with Conversational AI
Personalization efforts made more powerful with AI
Aside from expecting us to understand them, customers want us to know them. And to use that knowledge to provide highly personalized experiences. In multiple surveys, consumers want that personalized experience, and are more likely to make a purchase with brands that meet those wants.
What is personalization?
Forrester defines personalization as “an experience that uses customer data and understanding to frame, guide, extend, and enhance interactions based on that person’s history, preferences, context, and intent.”
Personalization allows brands to overcome surrounding and competing noise by connecting in ways that are relatable, appropriate, and beneficial to the consumer. Brands should know their customers, and they can use that knowledge to build those personal customer service experiences and predict the needs of their loyal customers. All of that can increase engagement and create customer loyalty.
Microsoft did that by personalizing its XBox gamer platform. Microsoft knows when gamers log into the platform and what games they play, and how they play them. It combines this with additional context, and uses AI to reinforce the desired outcome, delivering personalized customer experiences that led to a 40% increase in gamer engagement.
Whether it’s purchasing more, searching more, or taking advantage of various services a brand offers, this type of increased usage from personalization results in a valuable benefit to the customer and your business.
How to build a personalized customer experience when messaging
In the messaging space, such as conversational texting or in-app messaging, we have different information at our fingertips than we have in the web or content space. We can — and should — glean as much customer data from that first message as we can. This might include intent, product name, or historical contact information, which can be used to personalize the next response. Follow-up questions may be needed to collect additional information to provide that personalized customer experience. If we are communicating within an authenticated experience, such as an app that the consumer logs into, we have all kinds of information already collected about the consumer: purchase history, purchasing trends, historical conversations, and order status, among other information. All of it is valuable and can help us provide a great experience throughout the customer journey.
The customer should never have to tell us what we already know about them. Asking them for that information diminishes confidence in the brand, implies that our systems do not talk to each other, and makes it harder to complete the intent. We can avoid this by asking relevant questions for new details, and not repeating requests for what we already know. When we properly use the customer data we already have, and combine it with insights that we learn from real-time responses, then we can make the conversation more personal, and we can talk to millions of customers as we would talk to someone in a one-on-one conversation.
That is the power of personalization: It takes us one step closer to providing messaging at scale.
Scaling your conversational personalization strategy
As messaging popularity rises, it becomes increasingly important to support conversations with automation to provide the best possible quality of service with the same precious number of resources. Since LivePerson launched messaging in 2017, and especially as consumers and contact centers struggled through the pandemic, we have seen explosive growth in messaging on our Conversational Cloud®. We also see that brands understand the importance of AI chatbot automation to support these conversations.
In Q1, 63% — over 60 million conversations — included some sort of automation, and 28% — over 25 million conversations — were fully automated with bot users. Automation is critical to scaling messaging, and can be applied in many ways to help brands meet their personalized customer experience goals and successfully contain conversations within automation (i.e., bots completing end-to-end tasks for consumers). Containment is reliant on providing personalized service, meaning a brand has to understand intent, preferences, and context to enhance the customer interaction.
At LivePerson, our innovation drives increased containment as we scale messaging and create tools like MACS™, our new Meaningful Automated Conversation Score™. MACS launched in November and is an innovative bot measurement that helps brands identify not only how their bots are performing, but also where they struggle. This overcomes the challenges of traditional measurements like containment, CSAT, and NPS, which just don’t work well as chatbot metrics when trying to define bot success. Instead, MACS uses machine learning to identify where and why the bot is failing, and provides easy-to-access insights into those failures and the interactions that are performing worst. Then it applies a score to help you see how your bot is trending over thousands of conversations.
Our work in Conversational AI helps brands truly listen to consumers, then apply context, history, and knowledge to understand customer expectations, develop those incredibly valuable relationships, and deliver great customer satisfaction with better personalization.
Valuing your customers: A personal use case
I would like to take you through a use case that reinforces the value of personalization.
I have been with the same mobile telephone company for over 15 years — I know, I am not the norm! They have seen me add new users to my plan as my children grew up, and remove them when they struck out on their own. My telephone company knows what devices I like, that my partner and I rarely damage our phones, and that we always keep our devices through the full term of the contract, and beyond.
Yet, when I contact them with an issue or a question, it feels like it is the first time I have ever spoken to them. Why!?! I have invested a lot of money into my relationship with them, but I feel like they have invested nothing in their relationship with me.
Let’s look at how they could use personalization to make my experience with them better:
In this scenario, I have a problem with my phone. It is super slow when I browse the web and takes forever to watch my favorite YouTube puppy videos. I need help. That’s when I log into my telco brand’s app and start an in-app messaging conversation to access customer service. I type, “My device is really slow and I need help getting it fixed.”
The brand knows:
- My intent – troubleshoot my device
- My upgrade eligibility status – eligible for upgrade, per the CRM system
- The device type that I always purchase – I am an Android user, and have been for my entire relationship with the brand
Using this information, the brand can change the tone of the conversation almost immediately. Instead of starting a troubleshooting flow or asking questions they already know the answer to, imagine that a bot lets me know it understands my intent, and uses the additional customer feedback I provide to make me a special offer for a new Android at no additional cost.
It would probably be better for me than trying to fix this old phone, so I let the bot know that, yes, I would like to discuss an upgrade. The bot then transfers me to an Android expert and passes all my pertinent information to the human agent, who can pick up right where the bot left off.
As a result, I get a new Android device, which allows me to watch my puppy videos and has several other cool capabilities that I didn’t even know I needed! And my telco has a highly satisfied customer, who has a new two-year contract and a higher lifetime value.
By using information that they know about my history with the brand, the brand in this imaginary use case was able to upgrade me and drive increased value from our relationship, all through a positive, personalized customer experience. What might a personalized experience look like for your brand?
Personalization in conversations across multiple channels is not only possible, it is critical. Consumers demand it. Let’s start evolving our relationships with consumers and drive the amazing benefits that we know we can obtain.