You Can’t Solve if You Can’t See
When the Internet gives feedback to brands, the hammer can be harsh.
A well-known example — when Peloton split the Internet with a benign holiday ad. Critics called it “unsettling,” “sexist” and “dystopian.” Others saw it as “normal,” “great PR’’ and viewed the outrage as creepier than the ad itself.
The raging conversation online led to massive international news with everyone from Oprah to Harper’s Bazaar to The New York Times weighing in. Given the gravity of issues making headlines, it’s surprising that a single ad for a niche product caused such a reaction.
While all this was happening I called friends in ad land and Wall Street, wanting to know to know if the ire was an overreach and a buying opportunity for the stock. It was getting pummeled by the hour. Turns out it was best to stay on the sidelines. The stock took a $1.5 billion hit as people swarmed like bees around the story. Two months later the price hasn’t recovered.
And yet Peloton’s business fundamentals are on solid ground. According to Bloomberg, the company has a customer affinity all brands would die for, capturing a sky-high net promoter score of 91 — better than even Apple and Tesla. It has few true threats in its category. As a content producer and community builder, it paints a different picture of what a profitable media business can be.
Even more, Peloton’s greatest asset is a fan base that’s 1.6 million strong, with the potential to grow even faster through a new fashion line and subscriptions that don’t require a $2,000+ downstroke.
With a business model showing so much upside potential, why did financial markets react so strongly against them?
I’d argue they underestimated the impact cultural nuance can have today. Lacking an intelligence model to anticipate varied reactions, the brand they’ve been so expert in building got socked.
Grant McCracken is a longtime advocate of using culture to shape business strategies. He thinks about culture not in the vein of celebrity, influencers or chart-topping content; he comes at it more intellectually. He frames culture as a complex filter that organizes the world into categories — factions, in a business context, with taxonomy and sensibilities that can influence everything from reputation management, product strategy, innovation initiatives and marketing.
In Peloton’s case, it’s a good bet customer knowledge guiding the maligned holiday ad strategy was accurate. Sensitivities related to social issues like #metoo, body shaming, wage inequality, even holiday depression, went missing.
The Peloton case is a vivid depiction of what awaits other companies if they don’t rethink strategy that allows them to see cultural pitfalls and open doors. Here’s why:
- The ad industry is heavily invested in highly personalized, targeted media based on online tracking and offline demographics. This requires doubling-down on known customers and prior behavior. That presents a deep, not wide picture.
- With spend growing in programmatic media, Google and Facebook ad brands operate closer to point-of-purchase. Meaningful, culturally relevant communication — awareness-building — becomes a secondary consideration.
- Given how factionalized the world is today, dancing on a knife’s edge to engage emotionally — how brands build in value over time — requires deeper cultural intelligence.
Robert Shiller, a Nobel Prize-winning economist, studies how talk en masse impacts economics and executive decision-making. In his book, Narrative Economics, Shiller says the health of the economy, or a single company for that matter, can be radically upended by contagious tales. He urges us to dissect the power of talk. “If we do not understand the epidemics of popular narratives, we do not fully understand changes in the economy and in economic behavior.” In order to have economic impact, “stories don’t have to be truthful, good or inherently interesting. All they have to do is go viral.”
The key is to anticipate what those trigger points might be. Our own research at Weber Shandwick found that 76% of global executives who experienced a reputation crisis in the past two years felt it could have been prevented. In a different context, Gartner reports that 76% of marketing leaders already use data and analytics to inform key decisions.
My sense is the disconnect is in large part due to one-size-fits-all intelligence models that fail to account for the critical role of culture.
As McCracken points out in a recent essay, we need new systems to mind the gap. Most miss the necessary spectrum of data needed for culture-based planning as well as the modeling and human analysis necessary to inform decision-making and risk factors.
In partnership with some leading thinkers in the field, we’ve been hard at work building a first-of-its-kind intelligence platform to test this hypothesis. The platform uses artificial intelligence to sift and sort through billions of data points from forums, earned coverage, video transcripts, audio files, social media, search data, survey data and more.
Used in combination with client and paid media data, we have the necessary foundation to demystify market narratives as well as take on bespoke business and communications challenges. The early returns are interesting. A few examples:
- On product direction, we helped a top global food manufacturer rethink its flavor strategy by analyzing more than 1.4 million earned and social data points.
- For corporate strategy, the platform helped teams define a white space for innovation with a multi-billion-dollar healthcare company by understanding the true needs of scientists, media and potential employees, unearthing a unique nexus of new opportunity relevant only to our client.
- On enhancing valuation, we guided a client through a multi-billion-dollar acquisition, identifying a very specific kernel of opportunity from which to build credibility with enterprise customers — one that helped raise purchase consideration by 24% post-merger.
Despite the promise of big data and AI-driven platforms, uncovering new territory cannot be about technology. Over the past two years, we’ve also blended artistic, creative thinkers and producers with quantitatively-minded data scientists, engineers and analysts. The teaming and translation between two sides of the house is where the magic happens.
We’re still in the beginning phases of building this capability, but see immense potential to avoid misdirected communications efforts and unearth new growth opportunities.
One thing that’s become crystal clear in our time spent building an expanded intelligence approach — it’s hard to solve new problems if you can’t see the full picture.
If you have a way to help us enhance our ability to do so, please hit me up.
