4 Common Brand-Based Problems Marketers Can Solve with AI

min read
4 Common Brand-Based Problems Marketers Can Solve with AI

Historically, many brand-based problems have stemmed from not being human enough. This issue is going to become more complex as people start talking to the smart microwaves and other devices Amazon and other tech companies plan to introduce. While artificial intelligence is here to help consumers, the future winners and losers of marketing will be determined by their AI skills.

According to Adobe, 47 percent of “digitally mature organizations” said they have a defined AI strategy. Also consider that per a recent Deloitte study, 70 percent of businesses rate their digital maturity as “early” or “developing.” Therefore, if you find yourself without a plan, you aren’t behind schedule, though now is the time to act.

A huge first step is to think about what problems AI can solve. A big one—though it may sound counterintuitive at first—is that AI can help your brand feel more real and more human. Here are a few problems it can solve to make that work.

Acting overly transactional

Too often marketing is all about the sale in TV ads, on the radio, in print and in digital ads with retargeting. Even Amazon struggles with the challenge of being too transactional, and the ecommerce giant just began testing a system to make product recommendations more intuitive and helpful rather than simply cross-selling.

Seventy-two percent of business leaders are already terming AI as “a business advantage.”

Financial brands would seem at the highest risk of being too transactional, right? Not TD Ameritrade, which offers an investment bot called Alvi at no cost that allows customers to get personalized care by speaking into the system. AI-powered Alvi asks them personality-minded questions, like, “If you could write a letter to your 17-year-old self, what would you say?” The bot then breaks down the individual according to traits like openness, aggressiveness, neuroticism, conscientiousness and extraversion. Then it provides tailored, investment-based information in an on-demand fashion, an impossible service before AI. When permitted by customers, Alvi also mines their social media accounts for likes and dislikes and decides how to assist them even more intelligently.

On the other end of the consumer spectrum, Stitch Fix uses machine learning to show customers that their fashion interests—not sales—are always top-of-mind for the brand. The online shopping service has around 75 data scientists that employ AI to crunch 85 data points volunteered by customers, including their size or price preference as well as which parts of their bodies they want clothes to emphasize. The brand also has about 3,400 stylists who write notes to customers, addressing their specific situations based on data unearthed by AI.

Creating meaningful relationships

Whether data comes from a phone call, chat session, social media or mobile app, brands can use AI to regularly engage people in timely ways that are new. For instance, working with IBM Watson, Under Armour uses AI to power its app called Record, offering relevant training and lifestyle advice every day. If a male user wakes up after sleeping for just five hours, the app will tell him that the average body mass index is lowest among guys who sleep between seven and eight hours nightly based on the numerous men roughly his age in Under Armour’s database.

The AI also compares the users’ step activity and nutritional data against the larger Under Armour fitness community, helping them understand their level of performance while encouraging optimal fitness results. A brand helping customers become healthier is about as human as it can get.

Wasting budget

Brands have long wrestled with where to invest their ad budget. As marketing pioneer John Wanamaker famously said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”

Marketers increasingly understand that AI can get around this ROI roadblock. Google recently revealed that ads improved upon by machine learning get 15 percent more clicks. For brands in insurance, telecom, automotive, financial and travel where paid search is typically expensive and the advertiser often wants to produce phone calls, it’s important to know if the people clicking through have real purchase intentions. One way to solve that conundrum is AI algorithms that determine the outcome of the call (purchase made, appointment booked, etc.) in real time, which is incredibly meaningful data to marketers.

This kind of intelligence saves advertisers significant budget not only with Google but also other digital platforms like Facebook, allowing them to reallocate spend to better targeting. It also saves customers from retargeting ads for a product they just bought.

Bolstering your career

Indeed, AI can solve three of marketing’s most persistent problems by using data to flesh out what’s missing from the equation. And if you believe AI is still a topic only for future consideration, think again. According to PwC,

Thanks to a wave of smart devices in the coming IoT era, companies that are ahead in the game will reap dividends. These new kinds of digital consumer experiences will also need to entail a human touch that will only be possible if informed by the data-processing abilities of AI.

So, the future is bright for marketers that overcome challenges with AI—as long as they learn to do it early enough in their careers. If they wait too long, they risk falling behind the pack as the big winners humanize brands one algorithm at a time.

This article was originally posted in Adweek.

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