Numbers answer a big question—"What?” What is the problem? What happened when we did this? “What” gives us so much. It contributes to important decisions that improve people’s lives and business outcomes. But numbers cannot answer another big question—"Why?” Why is this a problem? Why did this happen? “Why” is answered when we use our deep, human-centered skills of empathy and intuition to understand people’s behaviors, needs, and motivations. Make decisions on metrics alone, and the results can be costly.
Blind taste testing might tell you that hundreds of participants prefer a new recipe, but it doesn’t tell you about customers' emotional connection to the old recipe.
Sales data might show that customers will only buy with greater and greater discounts, but it doesn’t tell you that a more honest pricing structure will ruin their experience.
This is why businesses fail—they treat customers as figures on a dashboard, when they’re real people with emotional, cultural, and contextual drivers. Here is where user personas come in. They distill qualitative user insights into a fictional person who represents a targeted group of your users. Personas become your everyday connection to the people for whom you create your product, service, or experience. They ensure you stay on track and design for people, not statistics.
In this video, William Hudson, User Experience Strategist and Founder of Syntagm Ltd, explains the psychology behind user personas and why we should design for individuals rather than groups.
So, avoid the cautionary tales below, combine personas with your dashboard statistics, and get the power to make decisions that create user love and business success.
1. New Coke’s Taste Wasn’t Everything
Amid struggles in the 1980s, world-famous Coca-Cola sought to regain its position as America’s favorite soda. In blind taste tests, participants preferred a new recipe with a sweeter taste to both Coke’s classic recipe and Pepsi-Cola. This led to the release of “New Coke.”
New Coke was introduced on the premise that taste was pivotal in consumer purchase decisions.
© Coca-Cola, Fair use
Fans would love New Coke, right? Wrong. A record 400,000+ complaints and 1,500 hotline calls a day forced a reversal after 79 days. In response, Coca-Cola launched “Coca-Cola Classic,” which used the original recipe.
How the Numbers Misled
Blind taste tests measured preference in isolation. Even though New Coke came out on top in the results from 2,000 tests, Coca-Cola missed its customers’ context and motivation. Coca-Cola was an American institution, and many consumers had a symbolic loyalty toward “real”, “classic” Coke.
How Personas Would Have Helped
Research would have shown Coca-Cola that taste wasn’t everything for a large subset of their customers. They could have developed two personas to put insights like this at the center of New Coke’s creation. One persona, Sally, who is primarily motivated by taste, while Brian is emotionally driven:
He has drunk Coca-Cola since childhood and enjoys the same, familiar taste.
He has a strong emotional connection and is loyal to both the brand and its decades-old recipe.
He sees Coca-Cola as part of his identity and traditions, and changing the recipe feels like losing a piece of the past.
Had Coca-Cola developed and consistently referenced Brian, product teams could have run every decision through the filter of “How would Brian react?” When sales data suggested changing the classic recipe, team members could have asked, “Would Brian feel betrayed by this?”
With Brian and Sally present in all product design sessions, executives might have realized that New Coke could be positioned as an addition to the product line rather than a replacement.
One way to make your personas unforgettable is with merchandise. T-shirts, mugs, and coasters with your persona’s photo and a few key insights will keep your team connected to your users on a daily basis. And if you need your personas present in meetings to keep everyone on track, try cardboard cutouts.
© Interaction Design Foundation, CC BY-SA 4.0
Perhaps with this persona, Coca-Cola would have still recognized the potential for a new recipe, but kept their classic-loving consumers in mind. They could have launched New Coke with a different name, regained some of their market share, and still appeased their die-hard fans.
2. JCPenney Underestimated How Much Customers Love Discounts
In early 2012, JCPenney’s point‑of‑sale (POS) data showed that most items were ultimately sold at nearly 40% off their list price. In light of this, new CEO Ron Johnson introduced JCPenney’s fresh pricing strategy: “Fair and Square,” believing customers would appreciate an everyday, low pricing strategy to replace the long‑running cycle of coupons and discounts.
Fair and Square aimed to be transparent and spare customers the hassle of hunting for discounts. Pricing was the same or similar for most items, just without the fabricated discounts and limited-time coupons.
© JCPenney, Fair use
However, after a year without coupons, sales were down 25%, and the chain posted a $985 million net loss, its worst performance in decades. Fewer and fewer people were going to JCPenney stores. As one loyal shopper put it, “If I don’t get a special discount, it’s not worth the trip.”
Ron Johnson finally conceded he had misread his core customer: “Coupons were a drug…they really drove traffic.” He was ousted after just 17 months.
How the Numbers Misled
POS analytics captured what people paid, but not why they were happy to pay it. Bargain hunters didn’t shop at JCPenney purely for low prices; they enjoyed the “treasure hunt”—stacking coupons and spotting 60%-off tags. Ron Johnson had removed the excitement from the game and destroyed the perceived value of the items, even though shelf prices were lower.
How Personas Could Have Helped
Qualitative methods like user observations would have revealed customers' emotional drivers when shopping in JCPenney. These insights could have fed into a persona, Tammy, who:
Is budget‑minded and likes to buy at a discount.
Relishes the bargain-hunting aspect of shopping.
Prides herself on winning deals, especially when there is a time limit.
Tammy's persona card on the boardroom table would have been a constant reminder that JCPenney’s customer isn't just looking for low prices—they’re looking for victories. When reviewing the Fair and Square proposal executives could have asked “Would Tammy feel accomplished with this pricing structure? Would it give her stories to tell her friends?”
If Ron Johnson's team had consistently referenced Tammy in strategy meetings, they might have designed a 'Fair and Square' program that still preserved the excitement of the hunt. They could have combined Tammy’s behaviors with their sales data to create a comprehensive picture of how customers shop and built a strategy just for them.
3. Snapchat Tried to Put Out Fires with Gasoline
Social media and photo messaging service, Snapchat, introduced some of the hallmarks of modern social media, namely, stories.
However, in 2018, Snapchat’s analytics were flashing red. Snap Map and Stories—two primary features—were losing users fast, particularly new users and those in the 35+ demographic. Fewer users meant less advertisement income. Snapchat boiled this down to usability issues.
The only positive trend was in Chats, where users were sending more and more private photos to one another. That led to the solution: combine Stories and Chats with a new algorithm to sort content and move all ad content to the Discover tab. A/B tests even projected retention for older users could rise by 8%. The result? It didn’t work.
Snapchat’s update resulted in 83 % of App Store reviews in pilot countries being one‑star, a Change.org petition that passed 1 million signatures within 72 hours, and a 6 % stock drop.
© Change.org, Fair use
How the Numbers Misled
The dashboards pointed to usability issues, but the reality was much more nuanced than that.
Numbers don’t tell you anything about mental models—the simplified internal representations of how people believe something works, guiding their thoughts, decisions, and interactions.
For Snapchat’s biggest user groups, teenagers and under-30s, the new update made no sense. “Why is celebrity and influencer content mixed with my private Snaps? This isn’t why I use Snapchat.” And for advertisers, “Why is my content somewhere fewer people will see it? I’ll spend my ad dollars elsewhere.”
How Personas Could Have Helped
Snapchat could have conducted observations and usability testing with participants from their most significant user segments to understand how they used the app. This would have informed a persona, Mia, who:
Uses Snapchat as her primary tool to communicate with her friends.
Likes to browse celebrity and influencer content, but this activity is separate from private chats.
Wants quick access to her friends’ chats to share important life updates on the go.
With Mia's persona front and center in Snapchat’s offices and meeting rooms, engineers and designers would have been constantly reminded of how their primary user mentally separates private and public content. When considering algorithm changes, the team could have asked, “Does this change respect how Mia navigates through her day with Snapchat?” and “Will this interrupt Mia's established patterns?”
This primary user persona, combined with usability testing and consideration across a wider user group, could have led to a redesign that kept what Mia loves but made the app more inclusive for less experienced users and pleased advertisers.
Usability, accessibility, and learnability are essential elements to consider for all users in any design. However, as William Hudson explains in this video, they are outside the scope of personas.
4. Tata Motors Didn’t Consider What “Cheap” Meant to Consumers
Indian car manufacturer, Tata Motors, launched the Tata Nano in 2008 as the “world’s cheapest car”. Tata saw that millions of Indian families relied on two-wheelers, like scooters or motorcycles, for transportation. Their analysis suggested that price was the primary barrier keeping those families from upgrading to a car.
Tata engineered the Nano so they could sell it for just 100,000 INR—around $2,000—and forecasted an annual demand of up to 250,000 units. Reality never matched the spreadsheets, though: sales didn’t get at all close to the forecast, and finally, in 2018, production quietly stopped.
The Nano’s utilitarian looks and barebones interior didn’t win over consumers who wanted a car they’d be proud of. A lack of air conditioning—an almost-essential feature in many parts of India—only worsened the situation.
© Tata Motors, Fair use
How the Numbers Misled
Tata’s price target and forecasting focused on market data, leading to a purely rational strategy—“cheap + four wheels = automatic adoption.” However, in India, for these two-wheeler families, car purchase is deeply aspirational. A car indicates high status and wealth.
Therefore, when Tata labelled a car “the cheapest in the world,” this signaled low status and poor quality, feeding a narrative of a “cheap car for cheap people.” The car scored poorly in safety tests, and later, when several Tata Nanos caught fire on the road, the narrative was worsened.
How Personas Could Have Helped
Personas, combined with Tata’s metrics and market data, would have shown them a different path. Research would have surfaced the importance of status symbols, interior features, and perceived safety. Qualitative insights could have built a persona, Arjan, who:
Prefers to wait and save for a costlier but more respectable car model.
Would rather continue using his scooter than drive something branded as “cheap.”
Cares how peers perceive his financial wealth and status.
When deciding which features to include or exclude, executives could have asked, “Would Arjan feel proud showing this car to his extended family?” or “Does this reinforce or undermine Arjan's desired social status?”
Arjan would have also highlighted that safety features and modest comfort upgrades might be worth a slightly higher price point to preserve the aspirational quality of car ownership.
Ultimately, with Arjan guiding product development and marketing meetings, Tata might have acknowledged the aspirational nature of car ownership and repositioned the Nano as “Your first family car” rather than “The world's cheapest car”.
A Persona Success Story: Spotify’s Famous Five
Now you know what happens when you rely on quantitative insights alone, it’s time to see what happens when you combine user personas with business strategy.
In2017, Spotify realized that designing “for everyone” diluted focus. A cross‑disciplinary research team ran diary studies and contextual inquiries with U.S. listeners, clustering needs, attitudes, and device habits into five archetypes—five personas. These listener personas became a durable, company‑wide language that 100‑plus autonomous teams now reference when shaping roadmaps for features such as the Home feed and social‑listening modes.
Spotify uses five research-backed personas to guide them through product decisions. These user personas represent the shared and similar needs, behaviors, and motivations of five key Spotify user groups. Ideally, small projects would have one persona, but with over 600 million users, there is ample room for five. When you focus on a small number of people (or personas), you can map your design to their needs and create products that truly resonate.
© Spotify, Fair use
How the Numbers Helped
Spotify is an excellent example of how to balance numbers with qualitative insights. Analytics dashboards tracked skip rates, playlist saves, device mixes, and session lengths. These statistics gave researchers a grounded map of listening behavior.
They then clustered the quantitative data and ran A/B‑testing, which confirmed that their persona segments truly existed at scale. This research exposed which habits, like high discovery appetite or background streaming, predicted retention. These findings guided algorithm tweaks to Daily Mix, Discover Weekly, and other personalized features that improved user experience.
How Personas Brought Success
Product teams now brainstorm new features based on one of the five personas. They solve for “Shelley the curator” or “Travis the lean‑back listener” to drive concrete UI, copy, and recommendation logic decisions. The payoff is clear: listeners who use Discover Weekly—a persona‑inspired feature—stream more than twice as long as non‑users, boosting engagement and ad revenue worldwide. Personas turned empathy into measurable business wins while keeping Spotify’s autonomous teams aligned.
Design Without Personas Leads to Assumptions
Quantitative data only paints part of the picture. If you stop there, you’ll use preconceptions and personal experiences to fill in the rest. You’ll assume taste beats emotional connection, that low price beats social perception.
Instead, if you get to know your customers, you’ll understand what they truly want and how they interact with your product, service, or experience. With this information, you can build solutions they love. An ideal approach to qualitative research is with grounded theory. Grounded theory lets your findings lead the way and seeks to avoid bias and preconceptions. In this video, William Hudson explains how to use grounded theory for persona research.
The Take Away
The mistake of relying solely on numbers and figures is not new. Many companies and organizations have skipped qualitative insights and gone straight to implementation, leading to user dissatisfaction, staggering losses, and failure:
Coca-Cola thought taste was the key factor for consumers, overlooking emotional drivers and nostalgia.
JCPenney didn’t realize how much their customers relished bargain hunting when they introduced a flat, simple pricing structure based on point-of-sale data.
Snapchat let dashboard analytics guide it to a new UI that didn’t consider how its core users navigated the app.
Tata Motors relied on market and pricing data to build “the world’s cheapest car,” not realizing what “cheap” meant to their target audience.
These companies have made the data-driven mistakes, so you don’t have to. The next time the dashboard tells you to do something, consult your personas. Conduct qualitative research and build a persona that represents the people you want to delight with your product. Personas give you confidence in your decisions, align your team around a singular focus, and keep the connection between creator and customer strong.
But the best part? You’ll create products and services that truly solve people’s problems, level up your career, and help you design a life you love. All this comes from your profound human ability to empathize and understand others, so you already have the skills to start immediately.
References and Where to Learn More
Want to know more about personas and how to use them effectively? Personas and User Research: Design Products and Services People Need and Wantwill show you how to conduct the qualitative research these companies missed, and how to translate those insights into actionable personas that prevent these exact types of mistakes. You'll master techniques for ensuring personas remain central to decision-making processes rather than becoming forgotten documents, and walk away with practical skills and a certificate that demonstrates your expertise in user research and persona creation.
Explore each of the stories in this article in more detail with:
Time’s article, The 5 Big Mistakes That Led to Ron Johnson’s Ouster at JCPenney
Coca-Cola’s retrospective, New Coke: The Most Memorable Marketing Blunder Ever?
CNN’s news story, Snapchat faces backlash after app redesign
Pepper Content’s Marketing Case Study: The Story Behind Tata Nano’s Failure as a Brand
Spotify’s case study, The Story of Spotify Personas
Discover the lengths Microsoft went to with user-centered design in the Guardian article, Microsoft to launch disability-friendly Xbox controller.
Master the original concepts of personas by UX pioneer Alan Cooper in his book, The Inmates Are Running the Asylum.
