Brand perception is notoriously hard to quantify. AI can help

4.6.23 / 4 min read

We live in an age where people skim headlines, scroll for their news, and glaze over subject lines. It’s rare for people to “go deep” these days. So it’s no surprise that a company’s reputation has become as important — if not more sothan what it actually does or makes. Perception, as the saying goes, is everything. But how much do most brands actually know about how their company is perceived? The growing importance of public perception means that organizations need to reevaluate not only the substance of their brand messaging, but the very tools by which they measure its impact as well.     

“Keeping employees, customers and suppliers engaged and inspired…is necessary to ensure those parties keep delivering profits to shareholders—and thus ensure long-term business profitability.”

Many of today’s business leaders agree. Just last year, Laurence Fink, CEO of BlackRock, underlined this point in his annual letter to fellow CEOs. In his level-setting correspondence, he opined that “Keeping employees, customers and suppliers engaged and inspired…is necessary to ensure those parties keep delivering profits to shareholders—and thus ensure long-term business profitability.”

And just a few years earlier, in 2019, the Business Roundtable, which includes the heads of Apple, Walmart, JP Morgan Chase, and many more of the world’s largest companies, embraced the same idea: To be fully responsible to shareholders now includes understanding that the public expects a company to take care of it employees, engage ethically with the global supply chain, and take care of the environment. 

An ever-growing emphasis on notions of trust, credibility and authenticity raises the importance of brand perception

Harvard Business Review estimates that 70 to 80 percent of a company’s market value comes from hard-to-assess intangible assets like brand equity, intellectual capital, and goodwill. And it’s true: reputation isn’t something that’s easily scored, let alone in any consistent and objective way. But if approximately three quarters of an organization’s value is determined by this factor, well, it sure seems like improving reputation data gathering capabilities should be a priority. 

Most traditional monitoring tools just don’t cut it in the modern landscape; they provide an incomplete view of brand perception and are labor-intensive to operate due to their reliance on Boolean search. Sure, consumer surveys can offer a glimpse at a brand’s perception, but conducting them can be cost-prohibitive for most organizations. Plus, surveys look only at a fixed moment in time and are often not immediately actionable. In today’s digital landscape, there are almost an uncountable number of places where brands are discussed: blogs, news sites, television, live streaming services, podcasts, social media platforms. Organizations are also increasingly global, creating new linguistic, regional, and political dimensions for brand messaging. 

Better understand brand perception with data and AI

So what’s a communications leader to do? Many are turning to AI tools to address these challenges. Measuring sentiment with AI can eliminate much of the tedious drudgery of conventional monitoring solutions, giving executives the brain space and bandwidth to develop informed strategies based on thorough information. Plus, AI-powered tools can not only analyze huge volumes of data in real-time, but can also synthesize its findings, sorting through what would undoubtedly be far too much data for a human to manage manually. This means real-time insights to identify specific risks and opportunities 24/7. 

With information moving as fast as it does, consumer sentiment can change on a dime. And in most cases, the validity of that information is becoming overshadowed by how loudly and often it’s being repeated. This makes real-time reputation analysis (and not just the collection of reputation-adjacent data) crucial. On the flip side, reputation analysis and consumer sentiment data also play a critical role in identifying new reputational whitespaces in which a brand has an opportunity to lead the conversation and set the standard. 

There’s a Chinese proverb that says “The best time to plant a tree was 20 years ago. The second best time is now.” The same can be said for reputational data and story-telling: an organization’s communication and reputation management plan is only as good as its data. The sooner an opportunity or issue can be identified, the sooner it can be acted upon. AI-powered reputation analysis gets decision makers the information they need when it matters.