AI knows your customer better than you do

This illustration shows that AI will neither redesign a product from scratch nor completely rewrite a UX based on shifts in strategy and user behavior. Humans are best-suited for these tasks.

AI will neither redesign a product from scratch nor completely rewrite a UX based on shifts in strategy and user behavior. Humans are best-suited for these tasks. (Image credit: TotalRetail)

It is inevitable that every customer-facing department believes that they represent the true voice of the customer, that they are closest to the users.

Marketing’s ability to run successful campaigns and acquire users is based on their deep understanding of them, including developing personas that aggregate the core emotional and rational drive behind their target audience. Product, meanwhile, focuses on the user interface and experience, which requires a deep understanding of what drives users, what they’re looking for, and what success looks like for them. Sales, in turn, transforms non-customers into customers by diving into the problems that matter enough to them to make them take out the credit card. They know which features make eyes light up and they know which pain points are most, well, painful.

Not only do each of these teams have direct interactions with customers, but they are all data-driven. Marketing measures ROI of campaigns with respect to their capacity to produce Marketing Qualified Leads (MQLs), and ultimately, opportunities for sales. In-app analytics provide product teams with data on every click, mouseover, and event that users engage in while using the product, enabling the creation of customer journey funnels to identify pain points and friction in the user experience. Sales teams prioritize prospects based on lead scores that take into account company size, industry, job title, and source.

Instincts can no longer be trusted

The problem with humans and data is intuition, and it often provides these teams with wildly different worldviews. Intuition is where you see the same cause and effect 10 times and on the 11th time, you see the cause you expect the effect. Compound that with qualitative experiences like talking to users and building an emotional connection with them and you’ve got yourself a rough guide to how humans perform product management, build marketing campaigns, and close sales deals.

Marketers build habits around channels, segmentations, or messaging – “that worked well before, why wouldn’t it work well again?” Product studies graphs and reports showing a minor subset of data in a way that makes it palpable, potentially reinforcing their preconceived notions about which metrics correspond most to success. Sales make judgments about leads based on country of origin (“I don’t want leads from there”) or lead source (“We met them at an event? Not interested.”) because of their experience dealing with a fraction of the total lead pipeline.

AI, however, doesn’t have intuition. It doesn’t expect a certain effect the 11th time it sees a cause. Instead, it processes innumerable amounts of causes and effects and weighs them indiscriminately.

AI can ingest every deal sales has won and lost, and dissect the anatomy of a good lead vs. a bad lead, combining hundreds if not thousands of firmographic data points about the individual lead. AI can look at every campaign ever run and determine which campaigns generated the aforementioned good and bad leads, therefore providing a single metric for success that is independent of whether sales subsequently closed a deal or not. (The unspoken truth is that good leads don’t always become customers.) AI can ingest every event from every user, and reveal which in-product actions lead to happy customers and which actions to lead unhappy users.

So what do we do with all our human intuition if we no longer need to analyze the past? We write the future.

Trinity of creativity

AI can determine which campaigns are successful, but marketing will always have a place in creating new campaigns that tap into the emotional drives of their potential customers. AI can score, route, and prioritize leads based on correlation to historical data, but only salespeople can create a bond between a prospective customer and a solution. Only sales can go out into new sectors, new markets and encounter new buyer personas to uncover new customers and experiences that ultimately help retrain AI. Likewise, AI will neither redesign a product from scratch nor completely rewrite a UX based on shifts in strategy and user behavior. It will only let you identify where to look for improvements. Product managers will keep making, marketers will keep creating and salespeople will continue building relationships.

Customer-facing departments should jettison their natural tendency for intuition and embrace AIs role in leveraging data. Let the machines crunch numbers so that humans can focus on what they do best: finding creative solutions to their customer’s problems.