With the AI revolution coming to reality, I started exploring how we can benefit from systems that, amongst other things, are capable of deeply understanding human personality. While in my previous post “Can Artificial Intelligence make the world better” I discussed how IBM Watson Personality Insights works, and in “The Naked Me. Rising Awareness With AI” I have shared the depth of insights elaborated by the service, here I will highlight how AI will transform customer journeys and ultimately relationships between brands and individuals, enabling hyper-personalized engagement, creating more relevant interactions, and constantly learning from outcomes. In three (not so simple) steps, here is my recipe for companies that wants to embrace the AI revolution.
- Build personality based recommendation engines, creatively collecting and integrating data from disparate sources like interactive kiosk, social media and existing enterprise demographic data, to understand your customer personality characteristics, needs, and values. Psychologist and behavioral scientists over time have validated hypothesis that can make insights derived from WPI at work to improve both the marketing effectiveness and customer satisfaction. For example, we know that: retail customers are more ore likely to redeem coupons if they score high on orderliness, self-discipline, and cautiousness, and score low on immoderation; people with high openness is likely to respond to product design; individuals with high conscientiousness tend not to abuse credits cards; people with high scores in emotional range and especially in immoderation tend to consume high-fat food, while on the other side conscientiousness and self-discipline influence the consumption of low-fat food and regular weight control. Personality insights coupled with behaviour based researches are the two cornerstones of next generation recommendation engines.
- Enable with AI technologies every step in the customer journey. Be very explicit about the goal you want to achieve: is it better targeting? Or smoother customer acquisition? Or improved customer care? Throughout the customer engagement lifecycle, from discovery to product use and customer service, companies can use the Personality Insights and other Watson-based services to build better, more lasting relationships with their customers. Businesses extract early, near real-time signals of customers’ purchase intentions to identify quality leads, create hyper-personalized marketing plans based on customers’ intrinsic and behavioural preferences to improve conversion rates, use customers’ personality characteristics to determine which interaction medium to use, what web page to display, and what video to share. Define your cognitive roadmap, with short term quick wins and longer term transformation initiatives.
- Rethink and collapse the customer journey: cognitive experiences bypass traditional web constructs (with things like registration, pages, forms…) allowing to quickly focus on the user need and what would be the best thing for them. It’s not just about getting better at every single step of the customer journey: with the support of cognitive-enabled recommendation engines, you have the opportunity to redesign each interaction points and the overall customer journey.
This is not futuristic, it’s happening today. From big brands to startups, leading companies are transforming the way they engage with their audience using artificial intelligence.
Adidas built a cognitive enabled engine to deliver personalized product and content recommendations based on users personality and lifestyle. Users provide access to their social and are provided with rich, hyper personalized content and product recommendations based on their individual behavioural data: after log in with social accounts, likes and posts are analysed using Watson Alchemy Language, photos are analysed for content and colour using Watson Visual recognition, resulting in a list of user interests and preferred colours. Posts are analysed for user personality with WPI. All these elements feed the product recommendation engine.
Rotzayger has developed a designer match system, that suggests the labels that best fit your personal style, based upon an analysis of your personality. NYC School Finder is a beta application helping you find the best NYC school for your child. The Centers of Arts, Culture and Tourism of Lanzarote developed a cognitive customer care mobile app to deliver quality, personalized service: using natural language processing the app can understand visitors’ needs, returning relevant answers and helping visitors weigh their options while collecting data in the background to help the organization improve the island experience.
Personalization is no longer optional, it’s the expected behaviour of modern brands. With AI, business have the opportunity to design and build better relationships with their customers.
