AI-based health management start-up Lark has an unusual premise. They’re overturning the belief that older consumers fail to engage with digital tools… and so far, they’re succeeding. Lark’s chatbot is kind and humorous. She befriends seniors, and cheers them up. She’s even helping users manage stress and anxiety through COVID-19.
One user described the app as, “kind of like my own little life coach.” With “unlimited personal guidance and support, anytime, anywhere.” The chatbot has transformed into a social outlet for the isolated while helping healthcare providers scale cost-effective solutions for chronic disease management.
Chatbots, virtual assistants, predictive personalisation — artificial intelligence is changing the way brands approach customer experience. Well-designed user interfaces and user experiences are re-imagining customer journeys to feel more integrated, and more personal. With algorithms sifting through larger and more complex data spaces, we’re looking at 3 ways brands are using AI to uncover new opportunities; customers and prospects they didn’t even realise they were missing.
1. Acing cross-selling and customer retention
Citi recently implemented a pilot program that utilises a virtual agent with the goal of improving customer experience in their Commercial Cards division. Since the pilot launch, Citi’s had over a million calls with a containment rate (that is, the virtual agent fully services a call without switching to a live agent) of roughly 40%, which is pretty impressive.
A small but growing number of banks are creating “decision hubs” powered by statistical models and fed by readily available customer data. One bank discovered that customers were calling helplines during the web-onboarding process, and reported poor net promoter scores (NPS) as a result of their experience. To fix customer churn, the bank turned to AI and machine learning. Breaking down data silos and pulling together dozens of data sources — CRM, front-end, website and app — AI helped create a clearer picture of customer preferences and pain-points. Learning from data, the bank set up a new onboarding process that achieved both; lower helpline volumes and higher NPS.
For others, AI is helping identify unique behavioural segments that are more likely to convert on cross sell offers. Wireless carrier Sprint implemented AI to personalise product recommendations for millions of its customers, boosting clickthrough rates to 30%, and achieving a 14% uptick in conversions.
But AI isn’t a quick fix. Both Citi and Sprint took over a year to implement a data-first approach across their websites and apps. With time and careful planning, AI tools are making it possible to target customers who are otherwise almost impossible to identify, and costly and time-consuming to target individually. They’re helping brands predict the likelihood of future behaviours with high accuracy, while simultaneously finding what’s driving, and destroying customer performance.
2. Getting better at predictive personalisation
Netflix, YouTube, Spotify, Alibaba, and Amazon aren’t the only ones predicting our moves. Tommy Hilfiger, H&M, Macy’s and ASOS are analysing receipts and loyalty data to improve fit, reduce lead times, and choose merchandise for each store. The brands of tomorrow are going beyond reactive personalisation based on buyer history to proactive and anticipatory business.
Now refrigerators and supermarkets track our inventories to predict and deliver goods home before we realise we’re running low. Cars can use knowledge of our past behaviour to choose preferred routes and in-vehicle entertainment as we go about our day.
Data is also shaping the way chatbots interact with us, mirroring our emotions and preferences back at us across channels (we’re thinking of Alexa’s ability to detect emotional changes via voice analysis) and smoothing every speed bump in the customer experience.
3. Controlling what we share… and what we don’t
A great deal has already been said on data privacy and AI will only increase privacy concerns. From news that Amazon had live personnel listening to recordings from Echo devices (entirely anonymised for training purposes, but still a cause for alarm for most users). Brands will have to implement rigorous standards when gathering and deploying personal data for machine learning and AI. Millennials and Gen Zs have come to expect that brands be more transparent with their data collection, storage, security and usage.
Poorly designed AI and porous privacy has the potential to demolish customer experience just as swiftly as one disgruntled customer service executive. Which is why experts emphasise testing, and re-testing, and calibrating AI until brands can find a tone and platform that fits.
An experience customers will remember
Not all chatbots are created equal. We enjoyed chatting up Mitsuku, five-time winner of the Loebner Prize. She’s whip-smart, and never drops the conversation (chat her up to see what we mean).
In MIT’s Technology Review Insights’ survey of 1,004 business leaders, customer service was the most active department for AI deployment. By 2022, it will remain the leading area of AI use in companies. By 2025, as many as 95% of all customer interactions will be through channels supported by artificial intelligence (AI) technology.
This focus on experience is eliminating differences between large businesses and small ones. Does the customer feel better every time they interact with you? AI or not, the brands that deliver a service that empathises with the customer — whether via robots or humans — are the ones we’ll remember. And Mitsuku certainly fits the bill.