New book alert: applied mixed methods research

My latest book is now available on Kindle! The book is a short guide to doing applied mixed-methods research. It’s ideal for people who work in applied research role in industry, but may not have a broad, methodological training in both qual and quant research methods.

What’s inside:

Table of Contents
Introduction: Understanding The Qual/Quant Divide
A Mixed Methods Example: Stories as a Network
What Are Mixed Methods? Mixing Objectivism and Constructivism
    • A constructivist view of technology
    • How the qual/quant divide plays out
    • Abandoning the scientific method: the creative encounter
    • Mitigating the weaknesses of qual and quant research

Why mix methods?

Ways to mix methods

How to mix methods, step by step

    • Project kick-off and framing
    • Developing shared understanding about research needs and resource constraints
    • Framing your approach: inductive or deductive frame?
    • Social Infrastructure: preparing teams for mixed methods
    • Research design
    • Priority or dominance
    • Data collection: simultaneous or sequential
    • Sequential designs
    • Simultaneous designs
    • Clarifying concepts or variables
    • Data analysis and interpretation: mixing Induction and Deduction
    • Can analysis and interpretation be a team sport?
    • During reporting

New Horizons for Mixed Methods Research

Conclusion: To Mix or Not to Mix?


What even IS this? Why tech companies are still failing us

Why do we know so little about the social implications of technology? It plays a starring role in everyday life, as essential as food, shelter, and clothing. A huge share (70%) of Americans use social media, and even 65% of senior citizens use Facebook  – that’s more than the number of people who eat family dinner at home, attend church, or have a pet.

Yet, we know so little about technology’s impact on everyday life. We are only just now recognizing problems like coordinated disinformation, breaches of personal data, and algorithmic discrimination.  Clearly, technology companies are falling short on understanding the social implications of their tools before and after they build them. But why? Why are tech companies failing us?

Woman in kitchen.
Woman in kitchen. Source: Art Institute of Chicago

Sadly, it is all too predictable that technologists underestimate, misjudge, or otherwise underappreciate how humans will interact with their technology. This is for one simple reason: engineering, as a discipline, does not bother to ask:  “What is this?”

Engineers are not scientists, much less social scientists. They typically have no knowledge of basic human behavior such as loss aversion or impression management, even though these are the building blocks of social interaction – and entry-level knowledge for social scientists.

Engineers could ask, “What is this?” but instead choose to ask: “Does this work?”

“Does this work?” underpins research within tech companies. Once upon a time, tech companies hired engineers they called research scientists and stuck them in labs to tinker endlessly with pieces of hardware and scraps of computer code. Even today, there are over 7800 job postings for “research scientist” on LinkedIn, which are typically engineers or computer scientists. A posting for an Uber research scientist intern is instructive. In addition to having a Master’s degree in a “technical field,” the intern is also encouraged to engage in “risk taking” and to “turn the dreams of science fiction into reality.”  Another job posting for a research scientist at Facebook asks for skills in the scientific method, but then specifically narrows that down to “evaluate performance and de-bug.” In other words: Does this work? Notably not mentioned: the ability to develop basic knowledge.

Academics would see much of this activity as more akin to prototyping than to scientific inquiry. Indeed, these engineers produced many technology prototypes, but not much in the way of generally applicable knowledge, or what the rest of us might call “science.” In other words, they never seem to stop and ask, “What is this?”

Painting by Salvador Dali
Inventions of The Monsters

Today, tech companies need to ask things like “What is a digital public sphere?” and “What is the nature of privacy?” and “What is artificial intelligence versus human intelligence?” Tech companies need typologies of human-computer interactions, motivations, fears, and human foibles. They need to create a system of knowledge around key questions of technology like artificial intelligence and social media.

Some argue that technology development doesn’t have time for “understanding,” that asking “What is this” takes too long and is too expensive. But this is a false economy. Philosopher Martha Nussbaum tells us plainly that we need that understanding, not for understanding’s sake but because it guides our planning:

“Understanding is always practical, since without it action is bound to be unfocused and ad hoc.” — Martha Nussbaum

In other words, if you don’t know “What is this” you’re probably going to build the wrong thing.

We can see this pattern of building the wrong thing in technology, over and over again. The term “user friendlywas invented way back in 1972. Curiously, “user hostile” wasn’t invented until 1996, just before Microsoft’s infamous Clippy appeared in 1997. Clippy’s abrupt entre onto the desktops of the world indicated that technology “researchers” had no idea what they had made. Word famously exploded from what appeared to be a digital typewriter, to a swollen behemoth that did everything from create a newsletter to automate mailing labels. Pick a lane, people. Clippy was there to tell users how to make Microsoft Word work, but no one bothered to find out much less explain what Microsoft Word actually was.  Word is still so swollen that a new user today can credibly ask “What even IS this?”

Clippy the paperclip

Flash forward to today, and the so-called “lean startup” approach to building technology is really just a faster, even more facile way to ask “Does this work.” In reality, tech companies still don’t know, “What is this?” even after they’ve built a working prototype.

In my former role as a hiring manager at a major tech company, it took an average of 100 days to hire just one ethnographer and more often than not, the job remained open much longer than that. These are the very people who can tell us, “What is this?” The demand for these social scientists only grows. Yet, the tech industry as a whole has not yet figured out they need to ask “What is this?” before they build something.

Were tech companies to ask, “what is this,” they would learn the basic properties of their tools, their coherence, intelligibility, performance, and affordances. Instead, they are fully occupied with “does this work,” and create horrific blights on our collective consciousness like Tay, the racist AI Bot on the relatively innocuous end of the scale, and Compass, the racist parole algorithm at the full-on evil end of the scale.

Technologists do not know what they do not know. Ethnographers hope for the day when they can just ask “What is this” without worrying about whether it works, because it doesn’t even exist yet. But tech development continues apace.

It’s time for ethnographers to stop this sad venture, and instead insist on asking: What IS this? Before another Tay, before another Compass. Technologists too must take responsibility because if we don’t, the 21st century will become even more technocentric, and even less intelligible. Let’s find out what’s going on before we build anything else.

What technologists can learn from the tragic Greek myth of Cassandra

Lately we’ve been inundated with news about how terrible technology is, and how “no one could have known” what awful outcomes would come from mixing humans and technology together. This blog post is a redux of a talk I gave in Vancouver recently, and it’s a hopeful (though a little stoic) analysis on how social scientists inside tech companies can stay the course, and keep talking about awful outcomes. If you’re just such a researcher, or maybe you’re a social scientist working outside tech companies, this post is for you.

Social scientists inside tech companies might see a little of themselves in another social scientist, Tim Lee. Mr. Lee, a self-employed economist and works alone in an office in Greenwich, Connecticut.

To make his living, Mr. Lee sells subscriptions to his newsletter called piEconomics to institutional and private investors –  a boring, 10-page block of text analyzing, macro and microeconomic trends.

Source: The New York Times

Back in 2011, the bearish Mr. Lee predicted a crash of the Turkish lira. Specifically, he said one dollar would buy 7.2 lira. Most people thought he was crazy. By 2018, Mr. Lee’s prediction came through. In August, the dollar bought 6.95 lira, and it may well his that 7.2 by year’s end. As you might expect, Mr. Lee was rewarded for his prescience…with cancelled subscriptions.

Wait, what?

That’s right, his subscribers rewarded his accuracy and insight by taking back their money. Mr. Lee seems realistic about the whole affair. “It has been some hard sledding,” he told the New York Times. “I have lost a lot of clients because I am too bearish.”

People who do human-centred research inside a tech company know what Tim Lee feels like. These researchers have probably told people what they know to be true, only be disbelieved. Maybe there was a researcher inside Twitter that warned it would be a platform loved by Nazis. Maybe it was a researcher inside Facebook who warned the newsfeed is easily gamed for nefarious purposes. These researchers, just like Tim, both bearish, and probably both “rewarded” in the same way.

Social scientists inside tech companies, and Tim Lee, are a little like Cassandra, the tragic Greek hero who absolutely knew what sorrow was to come, yet no one believed her either. Social scientists inside tech companies, listen up: you can learn from Cassandra. A lot.

Cassandra in the Temple

When Cassandra of Troy was little, she and her brother camped out in the Temple of Apollo. While there, they had their ears licked by the temple snakes. This gave her the gift of prophecy. But Apollo being the vengeful Greek God we know him to be, also cursed her: she would see the future, but no one would ever believe her.

In the beginning, she saw trivial things, like when visitors would arrive. But eventually, here visions became more grand, dramatic, and even scary. It culminated in the mother of all warnings: Cassandra knew there were soldiers inside the Trojan Horse. And of course, no one believed her.

Of course, Troy fell and the Trojans lost the war. She was kidnapped and enslaved by Agamemnon, of the winning side. When she got to Agamemnon’s palace, she got a terrible sense of foreboding. Sure enough, she was right: Agamemnon’s wife Clytemnestra murdered her and Agamemnon, and that was the end of Cassandra. All the she ever did was tell the truth about what she saw, and accurately predict the future, and this is what she gets. A little bit worse than cancelled newsletter subscriptions, eh?

Technology researchers know how she feels. They have real information that will help their technology partners do their jobs better. And yet, we often have this challenge: no one believes us. That is some hard sledding.  I mean, sure not-taken-as-a-slave-after-the-war-and-murdered-by-your-slaver’s-jealous-wife hard sledding, but you know, still kind of rough.

What can we learn from Cassandra? This gift – her gift, our gift – comes at a cost. But it’s still a gift. In fact, the fact that it comes with hard sledding is actually a blessing. But Cassandra didn’t understand that. The people of Troy really didn’t believe her, she got more and more hysterical. It was just this vicious circle. She didn’t embrace the cost of her gift.

The Cassandra Complex

 Psychologist Laurie Layton Schapira writes about what she calls the Cassandra Complex, or the persistent experience of being unable to accept that others will not bow to your will. Schapira uses Cassandra to describe her patients who had become plaintive, immature whiny people who continually fail to move past the moment when people disbelieve them. Instead, they stay arrested in time, mired in pain, regret, and anger. That anger is often justified; some of her patients had led very traumatic lives. The problem is that they stay angry, instead of reconciling and integrating that anger. They are unhappy, and stuck. They cannot move on with their lives.

You can see how a researcher could fall into this same trap. She might be literally saying, “My usability test predicted people will mistakenly post personal things” or “My ethnographic data clearly showed that the newsfeed is full of garbage.” But if you are not believed, over and over again, this begins to morph into “I am angry you do not believe me.”

This is where Schapira finds her patients: caught up in the pain and anguish of not being believed. The Cassandra Complex is a real risk for researchers, either working within or even outside technology companies; we predict terrible outcomes and no one believes us. Eventually, they just stop listening.

I cannot tell you how many times I have been the one saying, “There are SOLDIERS in THAT HORSE!”

So how do you solve for the Cassandra Complex? I’ll start with what won’t solve it. First, self-care.

Look, self-care is bullshit. I’m sorry, it is. I’m not going to stop those soldiers from jumping out of the horse by reading a lot skin care advice from some rich white lady. No. It might give me nice skin, don’t get me wrong, but it won’t solve the problem. Sure, go ahead and get your 8 hours sleep, by all means, but that’s not what keeps Tim Lee alive during patches of hard sledding. So forget self care.

Do people fail to believe social science warnings because we are bad researchers? Also no. Decades of psychological research has shown that fixed minds are hungry for confirmation, not for refutation. Data can be valid and sound and still no one believes us, so it’s not the quality of the research.

No, wait, that’s not entirely true. Absolutely we can improve. We don’t spend enough time analyzing our data. We report a laundry list of “things that happened” instead of providing explanations of why they happened. We are fearful of making universal statements. We’re afraid of our voices, so we bury them. I quote here the Robert Solow, who says, “The fact that there is no such thing as perfect antisepsis does not mean one might as well do brain surgery in a sewer” (cited in Geertz, 2000). So just like self-care, being good researchers is necessary but not sufficient to solving the problem.

Why do people fail to believe when the evidence is clear? I gather data, as I’m trained to do, with the utmost rigor and care. I take pains to present the data in rigorous but also compelling ways. I encourage stakeholders to come along with me, to witness product failures first hand. I build relationships, and above all, I care. And yet I still fail. Why?

This phenomenon of not being believed is not about any individual but about the cultural context in which researchers practice their work. I like to believe it’s all about me but it’s not about me, or you, or Tim Lee, or even Cassandra. It is about the way we organize ourselves, as humans, into groups. It’s very difficult not to take things personally, but it helps if you understand that the context, which is not something you can control. Culture is, as Peter Drucker said, what eats strategy for breakfast. Culture is what makes confirmation bias a generalized phenomenon; one person’s disbelief is confirmation bias, but a whole organization full of confirmation bias? That is culture.

Humans need consensus for groups to stay cohesive and unfortunately, the nature of what we do attacks that consensus. The data we collect is what anthropologist Elizabeth Coulson calls, “uncomfortable knowledge” (as cited in Ramírez & Ravetz, 2011).

Technology researchers are the bearers of news, which can often mean bad news. It’s not about the individual researchers, but the hard role they are required to play. We are here to tell people things they don’t want to hear. It’s a hard job, and hard sledding is guaranteed.

But it turns out, being the bearer of bad news is a unique and wonderful opportunity to become more self actualized, and lead a more meaningful life.

It is the opportunity to be a hero. All heroes must deal with failure. W.H. Auden wrote, “The typical Greek tragic situation is one in which whatever the hero does must be wrong” (Auden, 1948, p. 21 emphasis mine). So, you know, we are doomed. Sorry. We researchers are heroes, but more specifically, we are tragic heroes. Being Cassandra is actually a GIFT. It is something that many people only dream about. It is the gift of self-creation. Sure, it’s foisted upon us, but it’s a wonderful gift. We know from philosophy that making oneself is the key to becoming a realized person.

Nietzsche wondered what makes a hero, and he found that it’s about integrate the best and the worst together: “What makes [us] heroic? To go to meet simultaneously one’s greatest sorrow and one’s greatest hope” (Nietzsche, 1977, p. 235). This is the path to a unique and truly meaningful life. Imagine if you lived your entire life without meeting your greatest sorrow. On the surface, it seems like a pretty good life, but it’s not. You cannot make sense out of goodness without badness.

People whose job it is to point out the essential problems with their company’s products must face their sadness. But this is a gift.

Simone de Beauvoir puts it bluntly. “Since we do not succeed in fleeing it, let us therefore try to look the truth in the face” (de Beauvoir, 1948, p. 24).  Let us embrace looking truth in the face.

Facing your sorrow can be a path to reinvention. Polish Canadian psychologist Kazimierez Dabrowski has a wonderful way of thinking of meeting one’s greatest sorrow. He called it the theory of positive disintegration. Contrary to most psychologists, Dabrowski believed there was value in fear, anger, despair, and psychic pain because it can lead to a crisis, and then, ultimately, to growth. The key to this growth is taking advantage of psychic pain, making an opportunity to question yourself, your beliefs, and the gap between your ideal self and your current self.

The key to weathering being a Cassandra is making peace with the gap between your ideal self and your actual self. As Schapira tells us, “She needs to pull herself out of her with her own ego, finally to meet her own animus equal terms” (Schapira, 1988).

What does this mean? This means respecting that power you have inside you and embracing your masculine animus, or masculine power. Your animus is strong, confident, but can also be arrogant and aggressive. Cassandra is insightful and prescient, but she is plaintive and whiny. Imagine you integrate the two. Incorporate that power, don’t being afraid of it.

We need to take a stand, be bold, and tell people when we disagree. At the same time, we must accept that we will probably fail. We must have courage in the face of this failure and instead of attaching ourselves to “success,” we should attach ourselves to the struggle. This is how we become whole: by recognizing the struggle. There are some specific steps you can take to focus on the struggle, and meet your animus.

To do this, researchers will need a daily dose of meaning. A lot of us believe meaning is something that exists out there, in the world, and our life’s task is to just find it.

Meaning is not something you can find. Creativity coach Eric Maisel tells us that meaning is not something sitting on a shelf somewhere. It is something you must make, with the processes of your own mind.

“There are so many ways to kill off meaning: by not caring, by not choosing, by not besting demons, by not standing up” (Maisel, 2013, p. 129).

Incidentally, Maisel does endorse self care as well, but note that he too sees it as a enabler, not the outcome itself.  “You will also have to change your life so that you feel less threatened, less anxious, less rageful, less upset with life, and less self-reproachful, and so on” (Maisel, 2013, p. 63).

I keep asking myself, why didn’t Cassandra just go up to the horse and open the door!? Why didn’t she go all Arya Stark and just kill them all herself? Or at least die trying to kill them? What was WRONG with her? She let us all down, really.  So don’t be like Cassandra. Be more like Tim Lee. Tim Lee is now predicting a new crash, bigger than 2008, bigger than the Turkish lira. People don’t believe him, because of course.

Courage, Sartre wrote, is the ability to act despite despair. So if you come in tomorrow and that same goddamn boulder is at the bottom of the hill, look at it. Think about its meaning. It your chance to be courageous. Tim Lee is still going. He’s had some hard sledding sure, but he’s also accepted that. And he has also said he stands by his predictions. So should you.


This post the full text of a presentation at the Radical Research Conference in beautfiul Vancouver, British Columbia in September 2018.


Auden, W. H. (1948). Introduction. In W. H. Auden (Ed.), The Portable Greek Reader. New York, NY: Penguin Books.

Bailey, F. G. (1983). The Tactical Uses of Passioin: An Essay on Power, Reason, and Reality. Ithaca, NY: Cornell University Press.

de Beauvoir, S. (1948). The Ethics of Ambiguity. New York, NY: Open Road Integrated Media.

Geertz, C. (2000). The Interpretation of Cultures. New York: Basic Books.

Gilligan, C. (1993). In A Different Voice: Psychological Theory and Women’s Development. Cambridge: Harvard University Press.

Maisel, E. (2013). Why Smart People Hurt: A Guide for the Bright, the Sensitive, and the Creative. Red Wheel Weiser. Retrieved from

Mills, C. W. (1959). The Sociological Imagination. New York: Oxford University Press.

Nietzsche, F. (1977). A Nietzsche Reader. London, UK: Penguin Classics.

October, T., Dizon, Z., Arnold, R., & Rosenberg, A. (2018). Characteristics of physician empathetic statements during pediatric intensive care conferences with family members: A qualitative study. JAMA Network Open, 1(3), e180351. Retrieved from

Ramírez, R., & Ravetz, J. (2011). Feral Futures: Zen and Aesthetics. Futures, 43(4), 478–487. Retrieved from

Schapira, L. L. (1988). The Cassandra Complex: A Modern Perspective on Hysteria. Toronto, ON: Inner City Books.



The Desirability of Handbags

Handbags, like technology, can become part of your “everyday carry” – if they fit into your everyday life. Sometimes a handbag doesn’t “fit” your lifestyle, but you buy it anyway. Good handbags should be usable, but some very popular handbags are not at all usable. Why do people buy handbags that are hard to use?

In my last post, I outlined the major dimensions of handbag usability. In this post, I describe another “job” people hire handbags to do for them: social signaling. This post might help you avoid buying the wrong bag, but it will also reveal something quite invisible to most folks: consumer products are not pragmatic, functional things, but complex cultural memes that are infused with social meaning. People buy handbags (or phones, or software) not just to carry their stuff, but also to project a desirable image.

Beyond usability: what “job” do you hire your handbag to do?

Some in the user experience community talk about products and objects you “hire” to do a job for you. The Jobs-to-be-done (JTBD) framework is highly influential beyond the UX field; business strategists use it as well.

Using the JTBD framework, we might ask, what do we “hire” handbags to do for us? First, the obvious: we do hire handbags to carry our stuff for us.  But if that’s all that handbags are, we’d all be carrying plastic shopping bags. Something else is going on here. But what?

Here’s Miley Cyrus with a truly stylish white plastic tote and brown plastic jumbo tote.

Many technologists make the mistake that functionality will automatically translate into product love – it doesn’t.  Plastic bags are pretty usable, but they are not at all desirable. Some of the most desirable handbags are not usable at all (I’m looking at you Hermes Kelly bag).  Even unusable handbags will be highly sought after if they effectively project a desirable image.

We “hire” our handbags to tell other people: “This is the kind of person I am.” No amount of Carry-ability will convince me to buy an all-crocodile handbag, for example, because I don’t like killing crocodiles for leather, and, more germanely, I don’t want other people to think I support killing crocodiles. Jane Birkin herself did not like killing crocodiles, and begged Hermes to stop using crocodile leather on their Birkin bag (They did not stop but managed to come to an agreement with Birkin).

Projecting An Image: Handbag as PR Machine

Handbags tell people what kind of person you want them to see in you. Sociologist Erving Goffman called this “impression management”; a handbag is part of the impression you architect.

We “hire” a handbag just like we hire a PR firm to create an image for us. Who can forget the Sex in the City episode where PR executive Samantha bought a Birkin, pretending it was to enhance the image of her client Lucy Liu? Ironically, this is exactly what Samantha was hiring the Birkin bag to do for herself.

Consider the person who might carry each of these bags.  The Kate Spade Mini Simone Satchel is feminine, even child-like, and playful. The Marni shoulder bag is clean, lean, and minimal. The Gucci Babouska Boston Bag is sumptuous, bursting with ornamentation, and brassy in its presentation. Each bag would perform similarly on the Handbag Usability Themes, but they signify very different concepts. Feminine, clean, or sumptuous: people recruit a handbag to project one of those ideas.

A desirable handbag might be so good at projecting just the right image that you might forgive its lack of Search-ability, for example. A slouchy hobo projects one image, while a crisp satchel projects another, as you can see with Ashely and Mary Kate Olson. One of them (I cannot tell which!) carries a classic black Birkin, while the other carries a slouchy Chanel hobo. These two women are literally identical but the handbags project completely different images.

So it’s about money then? Umm, no.

Handbags are more than just usability – we hire them to tell people who we are. Sometimes, people take this to mean simplistically that handbags are “all about money.” You hire a handbag to tell people how rich you are, right? Wrong.

Sure, the most expensive handbag in the world was the Himalayan crocodile Birkin which recently sold in Hong Kong in 2017 for $377,000 USD. But how much a bag costs is not the only signal people want to send. Notably, this particular bag is, you guessed it, made from crocodile leather (Sorry, Jane Birkin).

You are projecting exclusivity. You can’t just walk into a store and buy an Hermes bag, even if you have the money. You have to “know” when they are available. You can’t just pick the most popular bag – you have to know which bag has cache. It’s more than just the price tag, but also the insider knowledge you possess.

This is sociologist Pierre Bourdieu’s concept of cultural capital – we distinguish ourselves with our “good taste.” Good taste is often expensive, but not always. Too many logos? Too obviously expensive, and worse, readily available? How gauche. Handbags rich in cultural capital are exclusive – hard to find, hard to know about, and hard to buy.

Buying the wrong bag: when desirability trumps usability

If you’re like me, you’ve bought The Wrong Bag. The Wrong Bag looks good, and probably was pretty expensive. It probably has some sort of cache, maybe it’s the “it bag” of the season. You think it will enhance your image. But maybe this bag is simply not usable enough. And maybe you bought into someone else’s concept of desirability, instead of your own.

I do this all the time with certain cuts of clothing; I know what works for my silhouette but I conveniently forget it when something is “on trend.” This happens with handbags all the time, like this Celine. I loved the look of the Celine Tricolor Trapeze bag, but it was the least usable handbag I’ve ever used.  It spilled open at the worst of times, was impossible to open, and was hard to carry. I got a lot of compliments on the bag, but when my rental period was over, I was happy to send it back.


Buying the right bag is about making sure it’s usable enough, and projects the image you are curating for yourself.

The Chanel Perfect Edge medium shoulder bag had great grab-ability, and easy carry. I would have preferred the shoulder strap to be a shade shorter, but I did find the handle to more than make up for that. The challenge here was to hold the bag open while carrying it. The handle was great for grabbing, but poor for opening. But just look at this biker sensibility! The chunk of the handle strap gave it an edge (get it?). I actually really liked this bag. It was easy to use and wasn’t too stuffy. Its unusual style compensated for it usability flaws.


The Prada Saffiano tote was high in Grab-ability, and with a pochette performed well on Search-ability. The problem was that it was entirely too big for everyday carry. I put *everything* into this bag, including my laptop. But you can see, it’s a bulky bag. I found myself toting around more than I could carry. As much as I’m a fan of Prada and its image, this bag was not for me.


The Louis Vuitton Alma was, by far, the most usable and desirable handbag I’ve ever used.

Its classic clamshell shape has a pop of patent leather to give it depth, but it still goes with everything. Note that there is also a shoulder strap, which you can use, in a pinch, though I rarely did. The grab-ability of this bag is second to none, and the full-length zipper made this bag so much more usable – I could unzip to the maximum, and find everything I was looking for. The double handle allowed me to hold the bag securely while I was looking, and the shape allowed me to keep the zipper somewhat open without spilling out its contents. But this bag was also desirable because of its black patent sheen and texture, and its brand identity.

Back to the point: what handbags can tell us about tech

Technologists like to think they are engineers, creating engineered products for humans’ technological augmentation. But we know that tech is just like any other product: it must be usable AND desirable. Handbags hit that sweet spot when they are easy to use AND have an element of exclusivity.

Technologists take note: you are fulfilling both functional and emotional needs. Sure, people want their tools to do heavy lifting for them, but they only love products that fulfill a deep emotional need like “project the right image” or “connect to me to my loved ones” or “make me feel safe.”

Products that can fulfill both types of needs are the ones most likely to become both popular and useful. Handbags can teach technologists a lot about product design, but first and foremost, it teaches us that humans are not “rational” beings, but complex, emotional, and culturally aware. Good products fit simply into a complex landscape, provide emotional rewards, and signal culturally appropriate messages.