What behavioral economics can teach about PM’ing: the affect hueristic

(NOTE: This is part II in a series of behavioral economics lessons for product management. You can find part I, on the remembering self, here.)

In part I, I covered the remembering self: the term describing humans consistently biased process for creating memories of events/products/experiences. It’s a critical lesson because the human biases are 1) understandable 2) predictable and 3) most importantly, hack-able if you understand how your users are likely to think.

Another key behavioral economics insight is the affect heuristic: the tendency of humans to rely on emotions to supercharge the decision making process by putting a subconscious stake in the ground at the beginning of the process. It’s particularly powerful because it kicks in *right before* weighing the pros and cons, and thus influences (read: biases) how pro and con lists are constructed.

For example, if a friend asks you what you think of Nike’s new running shoe, the affect heuristic kicks in immediately, queries your memory, collects any related emotions (positive or negative) you have toward Nike, running shoes, or this particular sub-brand. Then your conscious, rational thought process will kick in to tally pros and cons. But the damage is already done. If your initial emotional response is favorable toward an idea/concept/product/technology, you’re systematically biased to overrepresent benefits (pros) and underweight risks (cons). If your initial emotional response is negative, the opposite holds true: you’re biased to overrepresent risks while neglecting benefits. That’s the affect heuristic in action.

Paul Slovic, an expert in psychological heuristics, has studied this in many forms and in one study asked participants to note simply whether they liked or disliked a series of new technologies. Participants were then asked to enumerate the pros and cons for each technology they previously stated an opinion on. Slovic and his team found “implausibly high negative correlation.” If a participant liked a technology, the stated risks were implausibly low. If a participant disliked a technology, the stated benefits were shockingly low. Participants’ pro and con listings were remarkably biased by initial opinions.

Slovic’s team took the study a step further. After the initial the pro/con exercise, participants were asked to read additional information on the technologies. Some participants received a blurb *only* discussing benefits, others received blurbs *only* discussing risks. After reading, the participants were re-prompted to provide their opinions. Unsurprisingly, participants that read about additional benefits were now more positive about the technologies. However, the critical finding was that the participants who read about additional benefits now also believed those same technologies to possess fewer risks. A rational participant should have only found themselves counting more benefits, not adding more benefits and eliminating risks simultaneously!

The affect heuristic was kicking in. Participants were simplifying decisions by letting positive emotions (triggered by additional information) create a world that was more black and white than reality. A favorable technology has lots of benefits and few risks while an unfavorable one has few benefits and many risks.

Why should I care?

1) Immediate emotional reactions will bias any conscious, rational thought. No matter how rational anyone is, his/her judgment will be immediately biased by sub-conscious emotional cues. If you’ve successfully appealed to emotion, you’ve given yourself an unfair advantage.

2) Well defined benefits will proactively minimize risks. If you can clearly communicate the benefits of your product and/or service, you get a double win: the benefits will go-up and the perceived risks will diminish significantly.

Examples of the affect heuristic in the wild

Dropbox is a fantastic example of a product well designed to take advantage of the 1st principle. Think about Dropbox’s competitors Google and Microsoft. Any rational comparison of the features largely favors big G and MS. Both companies offer more free space: Google offers 5GB and MS offers 7GB, compared to Dropbox’s 2GB. Google and MS are stable, cash rich companies with nearly unlimited resources to support any initiative they want. Dropbox has ~300 employees and $250M in cash; Google makes $250M every 2 days.

But Dropbox is winning. And part of it is definitely due to a positive outcome of affect heuristics. They’ve hacked the first impression to successfully appeal to potential users’ emotions. Ask yourself what you think of Dropbox’s homepage (below). Most people say “clean” and “simple.”

Now ask yourself what you think of Microsoft SkyDrive’s homepage. I’ve heard “confusing”, “cluttered”, and “Why is that girl in a tree?”

Now ask yourself what type of cloud storage solution you want. A confusing one (eg “girl in a tree?”) vs. clean and simple. When it comes to pros and cons, 7GB of free storage is less compelling under the specter of a confusing, cluttered experience. It seems that simplicity has resonated with users as well, it’s not the be-all, end-all stat by any means but the Google traffic for the various services is telling… 

Airbnb is a great example of a company that will benefit significantly from nailing the 2nd principle: clearly defining benefits to boost appeal and reduce perceived risks. They stand to benefit dis-proportionally more than other consumer services – eg Uber, Fab, Amazon, Netflix where the risks of poor performance are relatively low (eg my Uber cancelled on me or my movie isn’t playing) – vs. my vacation rental was unsafe or my home was vandalized.

This is particularly important in the latter case for host sign-ups where people are putting their most important and personal asset (eg home/apt/condo) up for rent to relative unknowns. As the “meth incident” highlighted, the risks to putting up your asset for rental are real. But there is no doubt that Airbnb also has very real benefits they can tout to counter the risks: 1) the potential to gain a serious revenue stream from an otherwise un-monetized asset (see screen below) and 2) the more nuanced, but powerful, promise of community / friendship that many Airbnb hosts end up building with their guests. Given their recent stats of 200K+ rentals listed, it looks like they’re on their way toward overcoming the hurdles by communicating the benefits.

There are no doubt numerous other examples which I’ve missed (please feel free to call them out in the comments!) but the key point is that it’s critical to think about 1) what is the immediate, emotional reaction users will have to my product and 2) how can I clearly hammer home key benefits, which will not only raise user awareness of benefits but reduce their perception of risks.

What behavioral economics can teach you about product development: The remembering self

If I could sit down with anyone for one hour and then have them pick apart the motivations driving users in my product, it would be Daniel Kahneman, the behavioral economist behind this TED talk and Thinking Fast and Slow. Although he hasn’t set out specifically to discuss consumer tech, gaming or any reach of the interwebs, his insights are real, verifiable and directly applicable.

One key insight is that human memory is significantly biased. And it is consistently biased. So much so that it’s helpful to consider two selves: an experiencing self (the one that fully experiences every detail, nuance, perfect moment as it happens) and a remembering self (the one which packages up that experience, culls through it, retains a few key nuggets and forms a “memory” of it).

Unfortunately, much to the chagrin of traditional economists, the memory is not an exact reflection of the actual experience (eg, people don’t rationally weight all aspects of an experience). Instead, we predominantly build “memories” based on the most extreme peak or nadir and the final moment (eg, “all’s well that ends well”).

How does he know? Kahneman studied this phenomenoa, in multiple controlled experiments. In one instance he studied experienced and remembered pain levels during colonoscopy exams. Each patient participating was asked to rate his/her level of pain every 60 seconds from 0 to 10, (0=no pain, 10=intolerable pain). They tested 154 patients and the procedures varied in length from 4 minutes to 69 minutes. Here is a sample chart from two patients:

behavioral economics experiment

Any rational person can see that Patient B had a much worse go of it. If you totaled the integral amount of pain experienced by Patient B, it would significantly exceed that of Patient A. But, Kahneman’s team consistently found the opposite to be true when they compared patients’ overall ratings of their experiences.  The Patient As of the world invariably described their experience as more painful.

What gives? Two factors drove this:

The Peak-End rule: The top predictors of how one will remember an experience are: the most extreme moments and the moments near the end. In repeated experiments, the patients’ overall evaluation of pain most closely correlated with the average pain in the final minutes and the peak pain experienced.

Duration neglect: The duration of an experience doesn’t factor into one’s overall assessment. This is kind of mind blowing, especially given the knowledge that we are prone to conflating length with value (eg a 3-day vacation is always better than a 2-day one!).

What does this mean for tech products?

1) Do one thing remarkably well. If extreme experiences will drive user’s memory/opinion/position on your product, your best leverage point is to do one thing very, very well to create this positive association. This has been uttered many times in many different ways. Ben Horowitz and Mark Suster have both written about being 10x better when creating a new product, but until reading Kahneman’s experiments I hadn’t seen evidence that demonstrated why it matters so much.

There are lots of great examples of companies delivering incredible experiences in a single category. I’d certainly place Uber in that category for delivering no questions asked, quick, reliable transportation from A-to-B; Kindle (non-Fire incarnations) for delivering an awesome reading experience (despite getting nearly everything else wrong as I posted here); and Instagram for their sole focus on photos and creating the best photo taking & sharing experience.

2) Make the “sign off” experience killer. Again, if a memory is largely dictated by the final moment, you can hack the experience to your benefit by perfecting the finale. There is a lot of focus on “on boarding” and providing a great experience off the get-go, but fairly little on the final moments of a user session. In the service industry, there are lots of great examples of this: the after dinner mint, United’s “PS” service from SFO to NYC where first class passengers were offered warm cookies just before landing, Gary Danko’s sending dinner guests home with a pastry for the next morning are just two examples. These are successful initiatives that appeal to the remembering self.

Square is a great example of nailing this concept. The receipts they send (your final moment in a Square experience) are beautiful, simple and elegant. I’m shocked that Apple and Amazon (two companies that do a staggering amount of transactions) haven’t followed suit yet. Currently, their receipts are cluttered and hard to read at a glance. One last good example is Top Chef’s Last Chance Kitchen which is a 10-minute “encore” competition where the chef that just got kicked off competes one last time (these segments are offered free on Bravo TV). Every a time a Top Chef episode ends I go through a little emotional roller coaster: excited to see who gets the boot, dismayed the entertainment is over and finally, thrilled when I remember there is a Last Chance Kitchen I now get to watch.

3) There is no value in adding “empty calories” to session length. In other words, don’t try to eke out additional minutes to your engagement metrics if those activities aren’t adding any new value to the user. Noah Kagan and the AppSumo team have a good YouTube post where they discuss the decision to significantly reduce email frequency (NOTE: AppSumo is a daily deals type of service tailored for businesses). They decided they didn’t want “empty calorie” emails that didn’t “wow” their customers.

There are no doubt innumerate other great examples that I’ve missed, but the key point is that when you design your product, consider not only the experience you’re delivering, but also the experience your user will remember.Understanding how they systematically differ (peak end rule, duration neglect) will help you optimize your product experiences for the human memory biases.

How to build a solid roadmap: Part II

This is my 2nd post on the topic of “How to build solid roadmaps.” In part 1, I wrote about using two vectors to map out the full set of product opportunities for your product/team/company. The 1 sentence summary is that if you consider all trends (from your internal data to external market data) and all beliefs (from the core beliefs you hold to what you hear/see/recognize your customers need), you can map out the set of product opportunities. It looks like this: The Quibb community provided great feedback, many of whom rightly noted something akin to: “Great, but how do you transform this into an actionable roadmap?” Good question. Beliefs and trends are really the fundamental building blocks. A lot of tactics are required before a roadmap emerges. In whole, the process might look like this:

  1. Beliefs and trends -> This helps illuminate the full scope of opportunities
  2. Define priorities -> This forces focus (eg what is most critical next week, month, quarter, etc)
  3. Estimate impact of items -> This forces clarity (eg what 20% of stuff drives 80% of results)
  4. Get costing for items -> This forces reality (eg what can we get done)
  5. Putting it all together -> This forces everyone to exclaim “How could you cut X!?!”
NOTE: When I first started, I thought I’d plow through all 5 points in a single post. I failed, and part 1 basically covers point 1. This post will focus on points 2 and 3. 4 and 5 will be for a future post.

Priorities: It’s critical to define and limit your product priorities, which are distinct from your beliefs. You are entitled to multiple beliefs but not multiple number one priorities. For example, it is quite possible that Phil Libin (Evernote founder) believed since 2004 that his technology would be great for documenting and remembering meals. That is (if it were true) a perfectly valid belief. However, it was not a priority for his team, given that they launched Evernote Food 8 years later. At the highest level, you can bucket priorities into 1) market share and 2) revenue. Market share is about getting customers and keeping them happy and can be broken down into specifics like optimizing user acquisition channels. Revenue comes from having customers so happy they pay you. Again, this can be narrowed to specific priorities. For example, a pre product/market fit start-up might be laser focused on further engaging users in order to get their product well oiled before focusing on acquisition or monetization. Conversely, a later stage start-up considering an IPO or looking to spin up its revenues might completely focus on converting new customers into payers (eg Evernote, which recently re-designed its mobile apps to more prominently feature “Premium” account upsells).

Many factors will determine your priorities (stage of product, funding situation) and this post won’t discuss those. But I will stress the importance of setting clear, stack ranked priorities. My personal preference is 3 priorities for the product (but this could scale depending on your team). No two priorities are created equal. Rank them. As Hunter Walk points out, “hard decisions make great products.” This will help you make trade-offs when putting together a final roadmap and it will help you navigate unforeseen bumps in the future (eg “delays on project X mean we won’t get to all items, what can we cut?”) At this point, you can take all of your concepts (from the beliefs and trends matrix) and see which priorities they fall into. It’s likely that many will be outside your priorities. That’s fine (they’re probably good ideas it’s just not their time in the sun yet). You might end up with something akin to this: Impact: Each item must have a tangible expected impact. This does not mean that you must have specifics like feature A will drive $342K incremental revenue in 2012 (although you could and some companies do operate this way). Rather, the critical component is that each item has a stated, measurable purpose. For example, a re-working of an app homepage screen might be to reduce clutter and drive up a core user action (eg think Evernote’s redesign to highlight grabbing a screenshot of a notebook). Any item will have some measurable impact whether it’s reducing customer support tickets, increasing revenue from a specific channel, reducing sign-up flow drop-off, etc. This will help when finalizing a roadmap and deciding what to keep vs. what to postpone but it has further value in protecting against feature creep down the line (because the feature owners can use the initial stated impacts as a guiding lighthouse). Now your roadmap is filling out. You’ve got the initial items, which fall into your top priorities and estimated impacts for each: In the next post, I’ll go through the final steps of costing and putting it all together. To bring things to life, I’ll use an example (likely Evernote to stay consistent) to walk through the final steps.

(NOTE: I have no official association with Evernote, excepting that of a mostly satisfied user).

How to build solid roadmaps: Part I

Recently, I’ve spent more time mentoring and managing junior PMs and the other day one posed a deceitfully simple question: how do you build a good roadmap?

At first blush, it seems like an easy question to answer. Consider what your current customer base wants, what unmet needs they still have, what your product vision is, how it aligns with company strategy, what new capabilities exist (or will exist) that you can take advantage of, what your engineering team wants to build, your sales team, your UX team, and so on.

You could answer those questions and build a roadmap. In fact, you could just stack rank a list of features you have on your to-do list, team idea wall, hack-a-thon whiteboard, or brainstorming area. That would make a roadmap. But it’s liable to be an ineffective one, and at worst, a train wreck. A roadmap should be a cohesive plan – grounded in data and beliefs – that will take the product forward in building the customer base and delivering more value.

You need a framework to get there.

One way to think about this is in terms of trends and beliefs. Beliefs come in two forms: what you fundamentally believe (read: I believe we need to deliver X) and what your customers believe (read: I need this product to do X). Trends also come in two forms. There are internal trends, which you can tease out from your usage data, statistics, and historical performance. And then there are external trends, like the fact that the usage of tablet computers is growing at X rate YoY (Brad Feld has a good post on identifying external trends here).

If you map this out, it looks like this:

The framework does *not* provide the answer. Rather, it serves as a forcing function to get yourself thinking about the right issues. For example, do you (your team, your company) want to put all the proverbial eggs in one quadrant (see Instagram example below)? Or are you under-representing a quadrant that you do believe to be important? If so, the framework acts as a catalyst for highlighting the trade-offs implicit in any roadmap (eg, Are we too focused on quadrant X to the detriment of quadrant Y?).

The purpose of the framework is *not* to advocate for a standardized pattern across the quadrants (eg, A balanced 4-quad approach is better/worse than an imbalanced 1-quad approach). Rather, the goal is to enforce clarity and alignment around the strategic bets you’re making.

The framework is also helpful for what it doesn’t specifically emphasize: what your manager wants, what your competition is doing, what other internal teams are doing, other startups, etc. Certainly all of these other sources *can* provide roadmap inspiration but they should only do so if they are congruent with your trends and beliefs. If your manager (board, investors, etc) are advocating a feature or project, but you don’t believe in it and your customers don’t need it, why build it?

Here are a few examples and where they fit in the framework (some are bigger than just a feature but help illustrate the concept):

Instagram: Founded as Burbn, an HTML 5 based Foursquare-esque local, social network, Instagram found success when it listened to internal data from customers which suggested all they wanted to do was share photos. (Customers beliefs + Internal trends)

Evernote for Food: Based off Evernote’s mission of being your brain’s external hard drive, Evernote for Food melded this core concept with the growing external trend of sharing food photos, moments, etc.  (Your beliefs + External trends)

The iPad: Jobs held a strong belief in the importance of tablet computing despite no positive external trends (Microsoft’s tablets had failed earlier) and no customers banging down the door. (Your beliefs + Internal trends*)

Twitter’s Hashtag: Started by Twitter power user Chris Messina, the hashtag took off and was eventually “productized” and built into Twitter (Messina’s post on the evolution of the Twitter hashtag). (Customer beliefs + External trends)

Part 2 now posted here! (Thanks again to the @Quibb community for great feedback on Part 1)

*NOTE: The iPad example likely belongs in the very, very upper left quadrant where a visionary like Steve strongly believed in the opportunity and that was the sole driving force (eg, He believed in it and served as his own internal data). The x-axis of trends can be thought of as a continuum from the extremely internal (only 1 person knows it) to the external (everyone knows it).

Square is one-upping Apple (and Amazon)

Apple & Amazon should take the time to re-do their digital receipts. The current ones are sub-par at best.

Digital receipts should communicate the two key pieces of information: 1) what did I buy and 2) how much did it cost as clearly as possible. Why not include those in the subject line?

Interested parties can follow a link to get more advanced info.

Despite the fact that I get multiple Apple and Amazon digital receipts per week I always find myself struggling to quickly locate the relevant info as I look quickly scan through them to make sure there aren’t errors.

FULL DISCLOSURE: I get a little worked up about this because I was once burned (somehow accidentally ordered 48 packs of ramen, the Land Before Time DVD and a useless book by the founder of IDEO from Amazon and only caught it by checking the receipt…).

Regardless, I think everyone could benefit if Apple & Amazon took a page out of Square’s book on this one:

Amazon’s digital receipt:

And Apple’s (getting slightly better…)

And finally, Square. Putting the above to shame:

Beauty & the Push (Thoughts on Path)

Everyone talks about how beautiful Path is. Instead, they should talk about how push-y it is.

Why? Because Path has 1) identified the critical mobile social channel (push notifs) and 2) executed on them like a pro (Dave Morin co-invented FB connect & understands channels well).

Here is why this is critical:

  • Morin wants to build a “slow” company (specifically a “slow” social network)
  • By Morin’s own definition this means “slow” organic install growth driven family, close friends (150 max friend limit)
  • Social networks increase in value as user base grows
  • If emphasis is truly on “slow” growth, extraordinary attention must be given to retaining the users that come in the door
  • Push notifs (PNs) are *the* critical mobile retention driver
Given the above, Path has executed very well:
  • High quantity of PN: nearly every type of user generated content (photo, thought, location, I’m with, I’m listening to) generates a PN to everyone in the user’s network. Basically, if you use Path, you generate PNs.
  • Quality of Path PNs is high. Two reasons for this 1) Path embeds user generated content into each PN (as a result you get personalized PN) and 2) length of PNs are very short
  • PN looping -> Since each user generated action creates a PN, users often create PN loops (Joe posts a thought, which sends a PN to Jill, Jill comments on it, which sends a PN to Joe, Joe comments back, which sends a PN to Jill, etc…)

Why does it matter?

  • A great PN strategy will act as a force multiplier on growth -> by dramatically altering the user retention curve for the better
  • Even low quality PN, sent at higher volume can have a material impact on app retention (think 1,000 basis points all across the retention curve)
  • Given Path’s good execution on PN, it’s likely that they are seeing retention gains in excess of 1,000 -> maybe as high as 2,000 basis points
  • This creates a material difference in daily average users (DAU) -> by D90 Path could be seeing a 500K+ incremental daily users due to their PN strategy (this is even under more conservative assumptions than a 2,000 bps difference throughout the retention curve)
  • As a result, PN strategy is likely driving an incremental ~35%+ increase in DAU

Why Facebook bought Instagram for $1B

Insta-book. $1B! 13 employees! 700K+ a day “salary”! Systrom! Photos! Yay! FB! OMG. LOUD VOICES!

Ok, now that Instagram madness is covered above let’s talk about why FB bought. I’m breaking down my thoughts into 2 categories: 1) Why I think FB bought and 2) how they helped justify the price tag. I should highlight that the thoughts below are mine alone and are simply an exercise in thinking how FB arrived at its 1B conclusion.

Why did fb acquire?

Instagram is a legitimate mobile force, with the results to back it up:

  • Getting mobile right is a strategic imperative for FB. Why? Mobile is where the users are moving (see slide 11 here)
  • FB doesn’t have a track record of getting mobile right (it’s got a 2-star app rating).
  • Instagram is getting mobile right. 30M downloads and a perfect 5-star rating prove that.
  • That Instagram has 13 employees is irrelevant. FB likely has 300+ super-talented people focused on mobile. Has it produced Instagram like results? No. If you’re still arguing that FB should have just hired 13 great mobile developers for 0.1% of their acquisition cost, please read the preceding 3 sentences. The results are what matter.

Photo sharing is critical to FB: 

  • FB is a social network. And by definition benefits from network effects.
  • Engaged users are engaged because user generated content continually draws them back in.
  • A massive component of that UGC is photos (FB became largest photo sharing site all the way back in 2009).
  • All of a sudden, a new photo kid is in town & growing quickly. And he understands how people share photos today (via mobile devices).


  • Google has plenty o’ cash & has signaled their intent to muscle into the social space.
  • FB is understandably concerned about the Google threat. While Google may not “understand” social the way Facebook might not “understand” mobile, big daddy G is still a veritable opponent.
  • Instagram would have given Google+ a menacing shot in the arm (new users, social networking chops, mobile networking stronghold)
  • If you’re FB, that sounds terrifying.

Given the strategic reasons above, how might have FB have justified the price?

If FB wants to monetize Instagram, they can. In a big way.

  • Instagram had roughly 30M installs at time of acquisition.
  • Assume a growth curve like below, with roughly 20% of total installs coming in the last 3 months.
  • This is what avg. daily installs might have looked like for last 2 years (forecasts err on conservative side)

Instagram likely has solid retention

  • We don’t have great data here so we’ll make some assumptions
  • Systrom spoke about “FB levels of engagement” here
  • They have an impeccable 5-star rating on the app store (correlation of app store rankings to retention is very strong)
  • We’ll assume they have D1 retention of 80% and D90 retention of 30% (meaning 90 days after install 30% of the users still use app).
This means awesome daily average user (DAU) base
  • Given their reported installs and our assumed retention patterns, Instagram’s DAU at time of acquisition is around ~2M.
  • 2M is already huge. But potential for further growth is massive.
  • Given the app’s launch on Android and overall mobile trends, it’s possible they’d hit ~7M DAU by March next year
  • (SIDE NOTE: Post acquisition facts have confirmed significant growth, 10M more in 7 days).

Let’s monetize.

But how?

  • You could argue that Zynga is an unfair comparison because games are different.
  • But consumers have an even longer history of paying for photography (digital cameras today, online space today and albums, films, disposables, polaroids in the past).
  • Regardless of the route, it seems highly plausible Instagram would be able to monetize 0.8% of DAU through some combination of added premium filters, special albums, editing features, extra space or other add ons.

What else crossed FB’s mind (the frosting on top)?

  • New data access. Semil Shah has a good explanation of some potential network mapping FB could do.
  • Recruiting top engineering talent in the valley is cutthroat. Instagram is the hip new start-up on the block. FB can sell future talent on the opportunity to work with that team. Nice bonus.
  • “Instragram for video” – I’ll wager good money either Google or FB will scoop up an Instragram for video in the next year.

Education should = Sim City

Today, Sim City 2000 came up in conversation. It is, despite all the high quality education I’ve been fortunate enough to have access to (top 100 public high school, UVA and an Ivy league grad degree), among the most important educational experiences I’ve ever had in my life.

Rounding out the top 5 would be 1) Ken Elzinga’s class on anti-trust economics 2) a 2 week geo-political simulation game I played in 7th grade history 3) Kumon math and 4) charging down the UVA lawn with a 30 ft piece of PVC tubing with 100 classmates in order to understand the heroic level of discipline required to keep a Greek phalanx together while charging at the enemy – thank you Prof Lendon. (I should note that none of these are the typical classroom experiences we routinely jam down students throats day in, day out. The closet would be Elzinga’s class, which was a socratic method class with only 15 students and Elzinga is a 3 sigma professor. So basically it’s an anomaly).

But back to Sim City 2000 and why it’s such a powerful learning device:

Tactile -> Everything was interactive. You raise taxes too high, the citizens leave. Too low, city gets over crowded and crime becomes a problem. It forced you to really think about actions & consequences.

Dynamic -> There are multiple ways to learn each lesson. Unlike a textbook which provides a static limited number of examples (say on the impact of urban development and planning), Sim 2000 would you let you learn the lesson over and over again in completely new ways.

Engaging -> Not much needed here. Sim City 2000 vs. this drab tome. Don’t get me wrong, it’s a good book but students deserve better. We want them to learn, not suffer through 90 pages cramming for a mid-term.

Cheap -> $40 bucks vs. $150.

There is no doubt in my mind that Sim City 2000 was a better learning tool than ECON 301 at UVA. Unfortunately, the all in cost of the latter is probably north of $2.5K incremental cost. Sure Sim City didn’t cover everything in macro economics BUT that wasn’t the goal of the product. And even then, it did a superior job to a intermediate level economics course at a top tier university. That is sad.

Among the lessons a few hours of Sim City can hammer home are:

  • role of taxes / city finances & budgeting
  • supply & demand (enough electricity, police force, commercial business etc for citizens)
  • importance of zoning laws (particularly city layout and how proximity of heavy industry next to residential will impact real estate prices, etc)
  • importance of public services and finding the right mix for citizens
  • international trade (represented through neighboring cities)
  • importance & development cost of infrastructure (highways, subways, water, power, etc)

It makes me sad that Sim City bests ECON 301. But more importantly, it makes me hopeful that a better educational future is within our grasps. We have the tools and technology to significantly up level education. Sim City 2000 is a shining example of how we could better teach economics. And it is only scraping the surface.

I’m excited for what’s to come.

Do the (one) right thing

Yesterday, I had a conversation with a PM @savored who is newer to developing mobile apps. We chatted about what’s important to keep in mind when developing for mobile. My answer: it’s simple, just find the one (or two) things that matter most and nail those. You can ruthlessly deprioritize everything else. Seriously.

Let’s take a favorite example of mine, my Amazon Kindle Keyboard 3G. It lets me take 1,000 books anywhere and read them. When I first got my Kindle, I fell in love it with immediately. It was a clear, distinct step-function improvement over my status quo reading experience (trying to stuff 2 or 3 books into my bag before a week of travel).

It does not matter that 80% of the features on it are complete garbage. Tweet a quote? I’d wager that <1% of users have ever tweeted directly from Kindle and I bet less than 2% of users even realize it exists. The highlights section is cumbersome and painful to search through. The dictionary lookup forces all sorts of unnecessary clicks (if I’ve painfully scrolled to a certain word and double clicked to see a definition why am I forced to go to a new page if the definition happens to be longer than 100 characters?).

But you know what, it doesn’t matter. At all. The core reading experience is a quantum leap improvement over the status quo. Amazon got the one thing right and it makes all the difference.

The Flipboard I want (in the future)

I love Flipboard. I’m impressed with what they’ve done so far. But I want it to be better. Overall, I want it to be killer at highlighting the best content for me with as little manual work on my part. The key things I’d love to see Flipboard do:

Be my personal shopper & curator. The President gets a daily intelligence brief, why shouldn’t Flipboard users? There is more content on three of my favorite blogs than I will ever have time for. Help me filter. Curate it more for me and tell me what to read first. If it’s a rare day where time is in abundance, I’ll keep going. But on the 99% of days when time is scarce, I’ll thank you dearly for telling me what I need to know and sending me off.

Be the newsboy of the future with push notifs: Remember when they used to shout “Extra! Extra” while clutching a group of freshly printed newspapers? I don’t, actually. But I’d love it if Flipboard took a cue from corner newsboy here. When great content (which they know I like from my browsing history and possibly Pandora style feedback loop) comes out, I want to know about it. Send me a push notification. Seriously. If good content comes out, I want to know. Push notifs, when used right, are a great experience.

Be (even) more visual. Everytime I login to Flipboard, I want an on the fly, awesome looking magazine quality cover highlighting the top stories. How awesome would that be? I know Flipboard will have great content for me but I want it to sell the dream too. If I login each day to find one great article with magnificent visual presentation that would make an indelible impression (as opposed to just being a great way to read blogs).

Nix the photos only: Why is there a “photos only” option? Seems to muddle the picture (no pun intended) of delivering on the vision of a social magazine. I’ve seen magazines with lots of pictures but never one with “only” pictures. I can suffer through my FB timeline (or numerous other apps) if only photos is what I really want. Unless the usage data suggests otherwise, I’d nix it and focus on the true magazine.

Time sensitive (bonus): Detect patterns in readership (eg tech in the morning, economics blogs at night) and use that signal for curation. Doing this well will be really difficult and it’s definitely a P2 at best.