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Conversational AI: Another Driver of CIO/CMO Collaboration

AI-blog-2


Over the next five years, research firm IDC predicts that conversational AI applications will become increasingly prevalent in business enterprises.

Not exactly shocking, but consider the specifics: By 2024, IDC says, “AI-enabled user interfaces and process automation will replace one-third of today’s screen-based apps. By 2022, 30% of enterprises will use conversational speech tech for customer engagement.”

Applying Siri- and Alexa-type interactions to customer relationship and branding strategies creates enormous opportunities. For example, grocery chains could use an AI chatbot to provide shoppers with suggestions for recipes, spice combinations and wine pairings. Fashion retailers might deploy smart agents to offer shoppers advice on colors, styles and makeovers.

Beyond delivering digitized Q&A functionality, conversational AI could support the creation of distinct and engaging personality types that align with a brand. Take the grocery and fashion examples – which are good ones since they often involve emotional investment and a possibility of personal connection. Imagine bantering with an Italian-accented “Chef Luigi” about the right amount of basil to add to bruschetta? Or asking a snooty French sommelier for a Burgundy recommendation to go with a stew? Or having a glamorous fashion diva suggest the blue blouse because it makes your eyes sparkle? And, imagine if these bots recognized you on your next visit and remembered the details of what you talked about and purchased?

If the AI bots in these hypothetical examples provided useful information and engaged in real conversations, they’d be engaging, memorable and fun. As a customer, you’d likely enjoy the experience and return to shop there again. The grocery chain and retailer, meanwhile, would benefit not only from customer loyalty, but from collecting and analyzing valuable data from your conversations. On the other hand, if the bots couldn’t answer your questions or provided nonsensical information, or if their personalities were annoying, you’d bypass the bot and shop the old-fashioned way – and quite likely do that shopping elsewhere.

Judging from IPSoft’s eerily human Amelia and other examples, the technology to create chatbots with real personalities certainly exists, and can only improve over time. That leaves a number of questions around the types of personality a business would want to represent its brand. For instance, should the bot be a man or a woman? Have an accent? How many languages should he or she speak? More subtle considerations around personality type include: Will shoppers prefer straightforward factual advice? Will jokes or gentle teasing from a digital assistant be a turn-off? Would customers find over-the-top personalities engaging or grating?

Addressing these questions involves gaining customer insight; specifically, insight into the desires and preferences of the particular customer persona a business is targeting. That means gauging the different ways in which, for example, urban hipsters, midwestern baby boomers and college-educated women respond to different types of robotic personality types.

In other words, the exercise that marketing teams have traditionally conducted to select celebrity spokespeople for their brands will now be applied to define a digital personality. This will require increased collaboration between the technology and marketing functions, as well as strategic new approaches to measuring the ROI of technology investment. As such, the potential role of AI chat is one more example of how digital transformation – and its focus on the customer experience – is disrupting the marketing function and redefining the CIO/CMO relationship.


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