Future Facing: AI and Brand Experience

Machine learning in the brand environment

AI and brand experience

AI is Everywhere

Thanks to AI, our shopping experiences are efficient and easier, our search is more meaningful and material, and our entertainment consumption is customized and curated. Virtually all of our modern-day interactions with brands are driven by the backbone of an AI algorithm. AI has become so pervasive that it is both expected and invisible to the average user. As a result, consumer choice has exploded, and you don’t have to be Amazon or Google for AI to have a big impact on your brand.

Every brand today is touched by AI in some way. Take an Uber? The platform learns how to appropriately deploy enough drivers based on volume. Use Yelp to rate a restaurant? AI is used to rank and sort meaningful data. The whole of social media is driven by AI. That’s why it’s such a big deal when Facebook announces changes to its newsfeed algorithm. Even brands that don’t deploy AI internally are impacted by AI externally. Even the smallest of companies needs to be concerned about SEO, Google rankings and keyword search – because AI algorithms sift through data and refine relevant results. After all, how are people going to find you if you don’t rank?

The big buzz over the last few years is just how far AI will go. Think Deep Blue versus Garry Kasparov in a 1997 chess match was a big deal? Just wait. AI experts are predicting that by 2050, AI will be able to accomplish any task a human can perform. While it may not be splashed across headlines like the man versus machine chess match, AI is improving each and every day. Ultimately, that’s exactly what it was designed to do: learn and iterate to get better and better with each click and each interaction. While many companies are looking at ways AI will impact internal processes for delivering goods and services, there are ways that brands are already embracing AI to enhance brand experiences. 

Understanding Human Behavior

At its heart, AI in the brand environment allows companies to gather information, study human behavior and act on insights to enhance experiences.  In short, AI allows brands to learn from human behavior in a way that was hard to imagine even a decade ago. One of the biggest questions brands have about AI is the dataset. Do you have to have a huge data operation to get actionable insights? We’re not all Google with trillions of datapoints at our disposal, after all. What’s interesting with the rise of AI is that brands can access external data to complement and contextualize a growing internal dataset. While brands are creating an internal process for AI, they are able to get relevant external data to inform their brand.

What this means is that brands are able to classify targeted data into meaningful categories. For example, brands can use an external dataset to develop creative messaging and imagery and align and assess its effectives. An internal dataset that most brands have at their disposal is unstructured social data – how consumers have interacted with brands via their social channels. AI will help brands classify and comprehend those interactions and leverage a strategy based on their own data. From there, brands can identify influencers, trends and content that is resonating with their audiences. This will empower brands to build awareness, advocacy and ultimately, adoption among their target audiences.

Creativity Unleashed

Sure, we all know about the big tech giants like Google and Amazon using AI as a central function of their offerings, but what about other brands that are not necessarily operating squarely in the tech space? There are a host of brands dipping their toes in the AI waters with their focus on consumer and brand experiences. Thinking outside the box based on AI learnings, many consumer-facing brands have gotten quite creative with inventive ways to surprise and delight their customers. We’ve taken a quick peek at some of the brands doing this innovative work.

  • In 2017, Sephora deployed a chatbot to help its customers make beauty choices easier. When a regular search for “red lipstick” returned 200 results, the beauty brand knew it needed to do something to help its customers make informed, personalized choices. Starting with a quiz about product preferences, the chatbot then shared product suggestions, making the sales process less off-putting and more interactive. 
  • For audiophiles, Spotify’s Discover Weekly is a way to get access to new music without having to do anything other than what you were already doing: listening to music. The algorithm gets to know your personal tastes and curates a massive weekly playlist based on your preferences. Gone are the days of needing thousands of songs on your phone. You can now stream what you already like and be exposed to new stuff at the same time.
  • In advance of the 2016 Super Bowl, Kia undertook an unexpected and somewhat unorthodox use of AI. The car brand used machine learning to identify which social media influencers to approach for partnerships for their game-day campaign. They were specifically looking to deploy an influencer marketing campaign and wanted to partner with particular personalities to spread the word about Kia cars.
  • Working on mobile phones and Amazon Echo, Starbucks developed its personalized My Barista app where users can use order and pay for their customized drinks using voice commands through their phones or Alexa. The app tracks your preferences like your favorite drink and pickup locations, making the coffee buying experience tailor-made, just as you would expect from Starbucks.
  • Marrying tech and fashion, Levis launched a Virtual Stylist to help consumers discover their favorite pair of jeans. The assistant – which is a chatbot on Messenger and the brand’s website – collates knowledge from their style experts and provides customized recommendations based on a customer’s preferred fit, rise, amount of stretch and wash. Now you don’t have to go to the store and try on a giant pile of pants, looking for that one great pair.

The brand applications for AI are exploding. If a brand can dream it, AI can help make it a reality. But what about specific industries – will AI have an outsize effect on particular subset of experiences?  In our next installment on AI, we will take a look at the impact of AI on the financial services sector. Will robots be facilitating your investments and banking transactions in the future? They may already be doing it.

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