The UX of Desire

The Botany of Desire by Michael Pollan gives a compelling perspective on how desirability determines viability and how plant species have thrived by co-evolving with humans. Michael Pollan’s insights are wildly applicable to software User Experience (UX).

Pollan begins with the premise

Design in nature is but a concatenation of accidents, culled by natural selection until the result is so beautiful or effective as to seem a miracle of purpose.

He demonstrates how four plants have survived through adaptation, and have ultimately thrived by capitalizing on human desires and needs:

  • The Apple – exemplifies our desire for sweetness & intoxication (apple jack),
  • The Tulip – exemplifies our desire for beauty,
  • Marijuana – exemplifies our desire for pleasure, and
  • The Potato – exemplifies our need for sustenance.

Human Desire & Software

Facebook grew from an idea in a Harvard dorm room to over 500 million active users in a hand-full of years (cf. Facebook Timeline). My hunch is that Facebook’s popularity is based on its appeal to human behavior and its fulfillment of human desires. That is, by tugging at our narcissism, our curiosity and our instinct to connect with others, Facebook enables us:

  • to know what our friends, and would-be friends, are saying & doing, 
  • to surreptitiously learn more about particular love interests, 
  • to be flirtatious within a socially removed virtual cocoon, or simply 
  • to be noticed.

The Botany of Desire reversed my bias about humans domesticating plants like corn or apples or cotton. Perhaps it was the other way around – could it be that the plants domesticated us? Plants have, at the very least, used humans to co-evolve and thrive.

I now think of my killer app as a “species” co-evolving with humans. Future startup software might well have to be every bit as cunning as a Venus Flytrap. Our software must provide the sensory lures, then deliver on needs. Future apps might well be like successful plants — spawned by and grown by adaptively fulfilling specific human needs in a survival-of-the-fittest environment.

The Lean-Startup approach seems a fitting platform for the evolutionary experimenting that future killer apps might require. Lean-Startup is rooted in the principle of iteratively adapting and refining a business model (i.e., an evolutionary concept), based on proving the viability of features (meeting needs that customers desire).

INot only will killer apps have to provide features and fulfill needs, they will also have to present desire fulfillment in an alluringly positive experience not unlike a flower’s nectar lures and intoxicates a honey bee to better serve the flower’s ongoing reproductive purpose.

The UX of Desire means attracting and delivering (…so beautiful and so effective) as if the life of your app depended on it!

Startup Pivoting & Software

What is Startup Pivoting?

As Alan Cooper says in To Pivot, Or Not To Pivot,

When a startup company discards Plan A and moves on to Plan B, it is called a “pivot.”

The Lean Startup approach suggests that entrepreneurs use the Lessons Learned from the inevitable failure of Plan A to adjust their business model. An iterative approach that rapidly continues until the business model proves the viability of the idea.

In the context startups, pivoting is a term coined by Eric Ries. Pivoting is when, through a series of small-scale trials (hypothesis testing), a startup moves incrementally toward a better business model.

Each failed trial causes a pivot point where some element of the business plan is tweaked (e.g., customer segment, feature set, positioning).

Does Pivoting Apply to Iterative Software Development?

I propose that we – the iterative software development community – think of each release of new features as a business proposition and an opportunity to Pivot, much like a lean startup. Then, ask

  • What is our feedback loop with our customers?
  • Would our team modify a feature based on negative feedback?
  • Would our team roll back a feature based on negative feedback?

Further, I challenge the iterative development community to think of meaningful measures of the value of a new feature, whether value is measured by revenue generated or by the coolness buzz created.

Beware of Shadow Beliefs

One term I learned from Eric Ries is Shadow Belief. Shadow beliefs are the closely held, somewhat notional beliefs and assumptions that frequently sink good-intentioned entrepreneurs. All of us fall somewhere in the continuum of delusion, particularly those under the spell of a great startup idea or cool software feature.

One shadow belief is We know what the customer wants. Another shadow belief is Advancing the plan is progress.

Hypothesis Testing & Software

What is Hypothesis Testing?


Hypothesis testing is used by Eric Ries in the context of the Lean Startup. Hypothesis testing encompasses:

  1. Proposition – for example: How many users will pre-order our product?
  2. Test – e.g., a website with a picture of the product and an accompanying pre-order button.
  3. Results – Evaluate the number of pre-orders.
  4. Action – Refine the test (e.g., A/B testing or different market segment) or tweak business model (see pivoting).

Does Hypothesis Testing Apply to Iterative Software Development?

A shortcoming I repeatedly see in Agile software development is what I derisively call bogus prioritization. That is, the business or product owner sets the direction of the development team based on seat-of-the-pants guesses of what’s valuable, rather than on something more verifiable.

I propose that we – the iterative software development community – think of each release of new features as a business proposition, much like a startup company. Part of the Lean Startup philosophy is continuous testing and refinement as you converge to a better business model. Can we do the same with each software release?

We might ask,

  • What is a hypothesis and how best to test it with real customers?
  • That is, how do we make a bold hypotheses like “mCommerce will double eStore revenue” testable?
  • What hypotheses are we hoping to get answers to in this release?
  • How might prototyping of features be used to test hypotheses?
  • Will test-marketing feature sets be off-putting to our loyal customers? To new customers?

Believe those who seek the truth. Doubt those who find it.
~ Derek Sivers