“Consider the user experience early – Understanding how users will engage with your AI product at the start of model development can help to put useful guardrails on your AI project and ensure the team is focused on a shared end goal.
If we take the ‘”Recommended for You” section of a movie streaming service, for example, outlining what the user will see in this feature before kicking off data analysis will allow the team to focus only on model outputs that will add value. So if your user research determined the movie title, image, actors and length will be valuable information for the user to see in the recommendation, the engineering team would have important context when deciding which data sets should train the model. Actor and movie length data seem key to ensuring recommendations are accurate.”
“Combining insights from all of these touchpoints will create an even more robust profile of your customers that can improve engagement success. Remember, consumers no longer walk into a branch or pick up a phone to voice a concern or to make a purchase. Instead, they often interact on other channels hoping that their financial institution will “figure it out.”
“So anyone interested in CX trends should pay close attention to the latest Customer Experience Index report from Forrester Research. The annual survey asks nearly 120,000 U.S. consumers to rank 287 brands across 19 industries, focusing on how their company-specific experiences impact brand loyalty. The alarming surprise was that the aggregate measurement of customer experiences failed to improve, with more brands than ever ranked “mediocre.” Just 37 brands rose in the rankings; the remaining 250 stagnated or declined.
With the advent of artificial intelligence (AI), companies can now improve CX by learning more about the customer and anticipating their needs. Many CX-focused brands are deploying artificial intelligence technologies strategically at key customer touch points.
To illustrate what that looks like in practice, we’ve assembled five examples of AI-powered CX from five different industries—showing that 5-star customer experiences can be just an algorithm away for forward-thinking companies:
1. In retail, AI-enabled personalization unlocks access to the 1% customer.
Data shows thatthe top 1% of a retailer’s customers are worth 18x more than its average customer.
2. For a global bank, AI builds trust and loyalty.
Its approach was to leverage data intelligence into entirely new forms of customer contact.
3. For one airline, new data intelligence drives CX innovation.
Seeking to better understand its customer and, ultimately, improve its mobile app experience, the company deployed an AI and machine learning data analytics system that provided insight into customer behavior across digital and offline channels.
4. In entertainment, AI battles ticket bots.
Ticketmaster turned to AI to rewrite the rules using a machine learning system called Verified Fan
5. For one luxury hotel brand, new insight required new AI.
Until the luxury hotel brand Dorchester Collection did just that, creating a custom AI analytics system that is essentially a giant focus group operating continuously in real time.”
“A recent survey of design professionals by Adobe finds more than half, 62%, expressed interest in AI and machine learning and what they add to the creative process. AI and machine learning will have a “democratizing effect on creativity” in applications and products.
Eliminates one-sided testing approaches. “AI deals with the A/B testing, which considers a majority of votes rather than individual opinion,” says Morgan.
AI applies user behaviors. “AI algorithms simplify and ease out the process of improvised user experience by utilizing the information derived to revise user behaviors,” says Morgan. ‘This settles down in more personalized designs that are able to provide, the better individual user experience.'”