August 17, 2023
The lightning-fast evolution and adoption of AI is the kind of major societal transformation that only happens once or twice in a lifetime. One area where AI is making a positive impact on today's brands lies in its ability to parse raw unstructured customer data to extract hidden gems of consumer insight.
When businesses develop a 360° understanding of what their customers think, feel, expect, and desire, they have a tremendous opportunity to build specific strategic goals based on what their customers say they want – which directly correlates to a better bottom line. For CMOs specifically and C-suite leaders overall, it could not be a more exciting time to build a business.
In large part, CMOs are already embracing AI technology to improve their marketing workflows and engage consumers. A new survey from Boston Consulting Group found that CMOs are optimistic about AI’s ability to help them gain a competitive advantage to drive growth and gain market share. In fact, approximately 70% of over 200 CMOs from several sectors said that their organizations already use GenAI, while another 19% are testing it.
Unstructured Data Diamonds
Unstructured data from online consumer chatter is a goldmine of untapped opportunity. Customers aren’t shy about sharing their experiences, good, bad, and indifferent, online every day – and they expect brands to engage and respond – fast. Consumers today talk, share, celebrate, and rage everywhere. So, instead of being focused on pushing out content to enhance an omnichannel strategy, savvy brands now must also show up to listen – deeply – wherever, whenever, and however their customers are talking.
In fact, 80 to 90% of today’s enterprise data is unstructured, Unstructured data is all the unorganized chatter dispersed across emails, social media, online reviews, images, photos, emojis, customer service calls, chats, messages, and more. It is in unstructured, emotion-based data where the richest insights into customers exist. It’s where you’ll find the clues that reveal your blind spots, misplaced assumptions, and incorrect assessments about the human beings you call your customers.
For brands with hundreds of locations, managing vast amounts of unstructured data can be challenging. Something akin to standing in a football stadium with thousands of consumers all talking at once about your brand. But in the midst of that cacophony, consumers are sharing invaluable insights that could turn a good brand into a great one. The problem is, how do you extract those insights from the rest of the chatter?
What if you could turn the volume down on all that data “noise” and sort, analyze, and compare each piece of customer feedback at scale? That’s where AI comes into play. Using today’s AI-powered sentiment and deep listening solutions, CMOs can pinpoint and analyze the chatter that matters most to improving their CX and building customer relationships that last.
AI-Driven Sentiment Analysis
I’m talking about AI-driven sentiment analysis that seamlessly mines the treasure trove of unstructured data to reveal trends and themes, positive or negative, that give businesses from the C-suite to the boots on the ground the information they need to identify successes and pinpoint issues before they get out of hand.
For example, say you own a fast-casual restaurant chain and see mentions of “cleanliness” linked to 1-star reviews begin emerging as a negative theme. That’s an insight you can act on by drilling down into the data to determine the specifics. Is this a hyper-local problem at a single location or a recurring issue across your brand? Is it in the dining room? The restrooms? Something employees are doing? The parking lot?
AI-powered sentiment analysis software acquires intelligence from unstructured data in near real-time so businesses can quickly pivot to not only identify issues but also to reveal which employees at which locations are providing stellar CX.
Ferment Fierce Customer Loyalty
So, what separates an average brand from a brand that enjoys fierce customer loyalty? Building brand love is a blend of listening, learning, responding to, and connecting with customers in the most genuine ways possible. AI-powered sentiment analysis solutions help brands do exactly that – at scale. When national or global multi-location brands succeed at creating resonant customer experiences at the local level, the results are powerful.
Comments about Chewy, a national pet supply company, went viral as a result of the brand’s focus on creating highly personalized, two-way customer interactions. Chewy takes the time to send flowers and offer condolence messages to customers grieving the loss of their pets. AI helps brands keep their ears tuned to what customers are saying they care about and can surface potential opportunities to create lasting connections with your customers.
In that sense, AI is re-imagining multi-location reputation management by empowering brands with the ability to parse unstructured data with speed – and at scale. Through AI, marketers can gain an understanding of customer sentiment and feelings about a brand in real time. They can then act on those insights and respond to opportunities to connect with and engage consumers.
AI has the potential to responsibly transform the marketing industry for the better. Deep listening through AI-powered access to unstructured data trends and sentiment pattern analysis in concert and alignment with omnichannel marketing approaches can pave the way to developing more human-centered, authentic relationships with consumers. And that leads to the kind of champions who readily and freely share their brand love and spend their dollars.
John Mazur is CEO of Chatmeter, the brand intelligence company reimagining customer connections and reputation management through AI-powered deep listening. He joined Chatmeter from CoStar Group, where he was President of Residential, responsible for the brand’s marketplace business from 2020. Previously, he was CEO of Homesnap, which he helped build into a market leader before selling to CoStar Group for $250M in 2020. He holds an MBA from Columbia Business School.
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