P.V. Kannan, Co-founder and CEO
Consumer expectations have been driven in large part by the experiences they’ve had with Amazon, Uber and other forward-thinking companies that have made the customer experience a top priority. I’ve heard this new era described as “the age of Uber,” but personally, I think that gives one company, in one industry, too much credit. Uber is just one example of a much larger trend in customer experience, one that’s embodied by companies such as Argos and Hilton.
The Age of Intent is a new era for businesses where consumer expectations are higher than ever, and customer experience is paramount. It’s an era where the companies that understand, anticipate and act on consumer intent will thrive, and those that don’t will be disrupted.
Businesses already have a tremendous amount of data about their customers – what they’ve bought, previous customer service issues, what they want and need and how they like to communicate. Before this brave new age, businesses had a hard time tapping into this information. Customers languished in phone trees, repeated information, channels were not connected, and interactions not personalized. Relations were neglected and money was left on the table, while better equipped competitors picked up the slack. In the Age of Intent, customers have much higher expectations and businesses have unprecedented means to meet them.
What may have been acceptable a few years ago, is not acceptable anymore. Not in the Age of Intent.
The Age of Intent is about fundamentally changing the way that consumers engage with businesses – in all industries. It’s not about channels or devices … it’s about experience. And creating that experience starts by knowing the consumer’s intent. Leading companies (and I mean that as companies that are leaders) are using data to accurately predict consumer behavior to improve and expedite customer journeys, thereby embracing intent-driven engagement.
Forward-thinking companies like Hilton Worldwide and Argos are using data science, artificial intelligence and machine learning (ML) to develop predictive models. These companies can understand, anticipate and act on consumer intent across all channels to create a personalized customer experience that drives improved satisfaction and increased revenues.
Chatbot technology is powering Hilton’s new digital concierge, and they’re using chat data to optimize more than just the interaction. Predictive interaction happens in the chat window, when the guest is greeted with messages like “do you need help picking a hotel in London?” By knowing what the consumer is looking for (e.g. a five star vs. a four-star hotel), the agent quickly becomes a trusted advisor along the guest’s journey.
Not only does this digital concierge experience differentiate Hilton, it’s convincing more guests to book directly through its website, rather than third-party travel sites. To date, Hilton has achieved three times the conversion rate and a 97% satisfaction rate with the chat agent. Those are phenomenal results that help Hilton’s bottom line, and strengthen relationships with the 34 million guests they serve annually.
Argos, a leading digital retailer in the United Kingdom, is using predictive models that anticipate a customer's intent and determine in real time who to engage, when to engage, and what to recommend. This ensures shoppers receive personalized assistance when making purchases online. Argos has capitalized on an opportunity to engage in hundreds of thousands of digital conversations with its customers and has done an incredible job fusing real-time behavioral data with data-driven design. They have removed the friction from the shopping journey, resulting in great customer experiences and increased online revenues.
Most customer engagement today is about reacting to the consumer and their needs. The consumer reaches out to your business and is usually greeted with something generic like “how can I help you?” What a missed opportunity. There’s typically no understanding of what the consumer is trying to do, what they need or why it is they are reaching out to you. The experience ends up being generic, reactive and often-times painful for the consumer.
Today’s problems exist because most companies subscribe to “channel-centric engagement,” where they’ve kept adding channels (e.g. web FAQs, IVRs, chat agents, chatbots, etc.) to keep up with customer demands, but they’ve never orchestrated the customer experience. This is neither ideal nor sustainable. A consumer should never feel anxiety about calling an 800 number because they’re afraid of wait times. Likewise, they shouldn’t dread having to repeat all of the information they just relayed to the previous agent. In the Age of Intent, this is just plain ridiculous.
There are companies that leverage a whole lot of data (journey, device, profile, CRM, billing, preferences, behavior and even weather) to be able to anticipate the customer’s needs and act on it. Tell them what you know about them. Draw from the available data to make the experience as efficient as possible. Towards that end, engagement should be all of these things:
1. More personalized - be empathetic, and have context
2. More proactive - take action before being prompted, based on what a customer is trying to achieve
3. More productive - move customers to another channel if doing that will provide a better experience at that point in the journey
That’s intent-driven engagement.
Under the hood, intent-driven engagement uses a variety of data (profile, interaction, relationship) and applies artificial intelligence and machine learning techniques, including the following:
• Understanding - Data about the customer, their interactions and relationship with your company is combined with what the customer has said or typed
• Deciding / Resolving - AI then predicts what the customer wants to get done and provides the best channel or response for the customer to compete his/her journey
• Constantly Improving through Machine Learning - All of this data, what’s been said/typed, the interaction itself and the outcome is then fed back into the predictive models via machine learning to continuously improve future interactions
Here’s the kicker: with all of these data sources, and with AI and ML, these interactions can be done today with a chatbot OR a live agent, or a combination of both. You already know that consumers switch between channels, so when you stitch together those channels, and not treat them like islands, you can reap huge benefits. What’s more, you can instill new confidence in your customers and create greater brand loyalty.
Wouldn’t you like that for your business? Contact us, we can help you make it happen.
Welcome to the Age of Intent.