On control groups, lift, direct marketing and analytics . . . mainly
05 November 2015
Test-Driven Data Analysis (New Blog)
I've just launched a new blog, in collaboration with star
customer Skyscanner. It's
available at http://www.tdda.info
and is entitled Test-Driven Data Analysis. It will cover a
lot of topics that would otherwise have been covered here,
but with a specific focus on quality in data analysis, with ideas
inspired by the test-driven development methodology.
Do Fitness Trackers Work? (Very Nearly) 23 Months the Misfit Shine
Very nearly two years ago I received a
Misfit Shine, a rather beautiful
fitness tracker from Misfit Wearables.
The Shine resulted from a highly successful Indiegogo
project, and I have written about it previously
Nearly two years on, my Shine has just died, so I thought I’d write up
some thoughts on fitness tracking in general, and the Shine in particular,
ith the benefit of nearly two years of use.
Can Fitness Trackers Change Behaviour? Do Fitness Trackers Change Behaviour?
Everything I read about fitness trackers suggests they have a high
abandonment rate and that many people find they lose motivation to
move more after the first few weeks of novelty wear off. That hasn’t
been the case for me.
My experience is that the Shine has been extremely effective at making me
move more (primarily, walk more), and that effect has increased over time.
I’m pretty convinced that whether it works depends primarily on whether
the user takes the goal seriously or not.
I left the goal at the default 1,000 points a day. This seems to
equate almost exactly to 10,000 steps a day, which is the widely
endorsed minimum amount people should walk (e.g.
Horizon). While I’m not
the most active person, I always thought I walked quite a lot.
Nevertheless, for the first week or two, I quite often found that by
the middle of the evening I wasn’t all that close to 1,000 points, and
clearly wouldn’t hit the goal without specific effort. Perhaps this
shouldn’t be too surprising: when I got the Shine, I worked from home
(behind a computer) and didn’t have any need to move more than
2,000–3,000 steps a day. But I was convinced that 10,000 steps a day
is a pretty small amount for a human to move, and that if I was
failing to reach that, this was probably a very bad thing. So whenever
it looked as if I would miss the target, I’d go for a walk. sometimes
for as long as an hour if it had been a particularly indolent day. As
a result, I hit the minimum the vast majority of days, and probably
averaged about 100,000 steps per week.
Conclusion 1: It can work, and for me it did work. My behaviour
clearly changed as desired: I started hitting 10,000 steps or more
very nearly every day. The key, for me, was a combination of (1) measuring
it (2) believing it mattered (3) being committed to doing something about
it if it looked as if I was going to miss on any day.
Take the Long Way Home: Changing the Objective Function
There’s a rather lovely story about a visit to London by Gandhi.
He was escorted by a bright young man from the Foreign Office who said
to the mahatma:
“If we go through this way we will save a minute”,
to which Ghandi replied
“But what then, young man, will we do with the minute?”
In the modern world, it seems we are all constantly trying to save
time. We cut corners, take short-cuts, avoid traffic lights, eat fast
food, attempt vainly attempt to multi-task; we “cut to the chase”,
avoid “paralysis by analysis”, snd msgs in ncmprhnsbl txt-spk, use
increasingly compress our thoughts to 140-character
tweets. And we do these things largely
unthinkingly, literally without even being aware of them in most
Not everyone does it, of course: there is the slow food
movement, and a woman I knew slightly once said that she liked
travelling “as far a possible, as slowly as possible”, which was such
as strikingly unusual formulation that I still remember it (and her)
a quarter of a century later. But still …
When I started measuring my movement, I found myself repeatedly
thinking something I suspect I’d never thought previously: rather than
taking the quickest route, I could take a long route to wherever I
was going. (I guess I should have taken Supertramp’s
Without dwelling on it too much, I think this is fascinating. In
effect, by “quantifying myself”, as the lingo has it, I changed my
subconscious objective function from “minimizing time” to “maximizing
walking”; or more accurately, not—obviously—maximizing walking, but
at least selecting from among the reasonable alternative routes the
one with the most walking rather than the least.
Real-Time Information and Staying Ahead of the Bus
During the time I had the Shine, I changed from working alone, from
home, to employing a couple of people and working in an office in
Edinburgh. I live about 8 miles south of the centre, so walking in
isn’t a practical option, so I got a bus pass. There’s an excellent
bus service from near my house to near the office (the Lothian
31/X31), so I use that. I don’t really mind the 30–40 minutes on the
bus, not least because I use it mostly to continue development of
Miró, which I continue (only half faceciously) to call “the world’s
only analytics package developed primarily on public transport”. For
the first few weeks, I boarded the bus at the nearest stop to my
house, and disembarked at the last stop on North Bridge; the stop in
front of Waverley Station is probably closer, but the time the bus
waits at the lights to turn onto Princes Street means that I probably
reduce my overall travel time by walking from North Bridge,
“saving time”, like a good little human optimizer.
Then things then changed.
I’m not a very patient person. In fact, I’m an extremely impatient
person. And I hate waiting for buses. Happily, however, a few years
ago Lothian Buses introduced a real-time bus tracking information
service, with digital displays at some bus stops and phone apps that
give pretty reliable information about the time to the next bus. In
the centre of Edinburgh, bus stops are remarkably close together. The
combination of the reliability of the real-time bus information and
the closeness of stops means that my rule-of-thumb is that if there’s
more than 3 minutes to go until the bus is due, I can safely walk to
the next stop and still catch the same bus. So I do. There’s a double
win here: I avoid the mind-numbing tedium of waiting for a bus and I
walk more, with no cost at all in terms of my total journey time
But there’s more. It turns out that between North Bridge, where I get
on the bus to go home, and Lady Road, about 2 further south, the
average bus speed is less than twice my walking speed. As a result, if
I get to the bus stop and it shows 10 minutes till the next bus is
due, I can probably walk for at least 20 minutes, often more, until
the bus catches me. In fact, I often make it all the way to Lady Road
without the bus catching me, and I’ve yet to miss a bus as a result of
this tactic. (Slightly disconcertingly, in the centre, the bus speed
is not always faster than walking, so its far from uncommon for the
time indicated at each bus stop I pass to increase as I march south
for the first few stops.)
I find this remarkably interesting too. For my whole life, without really
thinking about it, I’ve effectively optimized for “walking as little as
possible” when using buses. But now, simply by consiously changing
this approach to trying to get home “as fast as possible”, but qualifying
this by saying “and walk as much as is consistent with that”,
my activity has changed almost beyond recognition.
Small nudges, indeed (a book,
I should say, I haven’t read).
Don’t Walk; Walk
The third change in my behaviour I’ve observed since getting the Shine
has been to start getting off the bus earlier, particularly on the way
into work. Unlike walking ahead of the bus and letting it catch up,
this isn’t “free”: the result is that I get into the office slightly
later than I otherwise would. (And get wetter, if it’s raining.) But
even here, it isn’t as bad as it seems. I tend to get off around the
Queen’s Hall, and walk to Forth Street, which gives me a 1.3 mile walk
rather than a 0.5 mile walk, so I that probably costs me 12 or 13
minutes gross. But, as mentioned before, the bus doesn’t go that much
faster than walking pace in town. So in fact, I think I
probably only add about 5 minutes to my journey by getting off nearly a
Overall, over the 23 months for which I used the Shine, I made my
daily goal very nearly 100% of the time. I don’t have the full stats
for the two years, but I had a number of runs of 60–90 consecutive
days making the goal, frequently hit 150% to 200% of the daily target,
and would often go weeks at a time without dropping below 150% of
target. Of course, your mileage may vary (literally!)
Conclusion: To Replace or Not To Replace
For me, there’s no question the Misfit Shine worked. It is a
beautiful, minimalist, but very effective step counter. By caring
about achieving the (admittedly modest) goal I set, it definitely
succeeded in getting me to move significantly more than I had been
doing. I’m sure lots of other fitness trackers would have performed
similarly, though it helped that the Shine is attractive to wear, has
excellent software and is backed by a company whose people are
consistently helpful. It’s not a perfect device by any means. Among
its weaknesses, it is very losable, and I’m not convinced it’s
accurate for tracking other activities like cycling and swimming.
Syncronization with the phone was always a hit-and-miss process for
me, though this was more annoying in the early days, when you had to
sync manually, than more recently, since they updated the app to sync
in the background periodically. (Synchronization uses Bluetooth Low
Energy, and I guess that is made more difficult by the Shine’s very
elegant, nearly all-metal case.) Despite these small niggles, the
Shine is excellent at its primary function.
So will I replace the Shine? For sure. While I am confident many of
the changes in behaviour it has facilitated would persist even without
a tracker, at least for a while, I am also convinced that measurement
makes a difference, and that without that quantitative reckoning I
would gradually slide back into less activity.
In this case, however, I probably won’t replace it with another Shine.
Instead, I suspect I’ll now get an Apple Watch. This is not a
particularly easy decision. Most of what I read and hear about the
Apple Watch is that people think it is beautiful but rather lacking in
functionality. My perspective is almost exactly the reverse. I have
little doubt I will love the functionality: the fitness tracking alone
will be fantastic, occasional taptic notifications will be a boon, and
I like the idea of Apple Pay. But I find the Watch physically
ugly—thick, large, square, asymmetrical—what was Jony thinking with the
positioning of that “digital crown”?—and vacuously blank except
when raised. Until now, I’ve worn a traditional watch on my left wrist
and the Shine on my right wrist. There is obviously appeal to going to
a single device, and the total functionality of the Apple Watch is so
far in advance of that of the traditional-watch-plus-Shine combination
that it’s not even a fair fight. So I think I will swallow my
aesthetic objections and try the Watch. But if it disappoints,
or it turns out that I can’t stand the look or bulk of the Apple Watch, I’ll
be straight onto Misfit, ordering a new Shine.
Most mornings, I get off the bus near the Queen's Hall and see posters advertising gigs for exotic-sounding artists I don't know but who look interesting. Then I make a mental note (or possibly a digital note) to look them up later. Then I forget.
The last couple of mornings, I've said to Siri "Play me some Rachel Sermanni" and "Play me some Aaron Parks Trio" (then, "Play me some AARON Parks trio"; then "Play me some "AARON PARKS TRIO"; sometimes you need to shout at Siri a little). And in the case of Rachel Sermanni, I then booked tickets, and I probably will for Aaron Parks too. (Siri doesn't know how to book tickets yet...)
Anyway, it's pretty great.
But I really wish I could tell the phone to use cellular data for Music but not App Store downloads...
As a follow up to the previous
if an olympic swimming pool has under a million gallons of water,
rather than the billion gallons claimed by Glasgow 2014, what
does have a volume of 1 billion gallons?
Well, obviously an olympic-size swimming pool of depth 3–4 km deep would
have that volume, but you don’t see too many of those around.
Also, the volume of the Great Pyramid of Giza is
apparently around 2.5 million cubic metres, which is about 550 million
gallons, and as far as I can tell both the John Hancock Tower and the
Burj Khalifa have volumes of around 330 million cubic metres so other
2 Great Pyramids of Giza
3 John Hancock Towers
3 Burj Khalifas.
But a more interesting answer is suggested by Wolfram Alpha. It suggests “1% of all humans alive on the planet Earth” (which I suspect is very similar to “1% of all humans alive”). This is a fantastic answer, especially since the population of the world is about 7 billion and the population of the UK is roughly 1% of that (some 63 million in 2012). (Wolfram alpha defaults to US gallons, but that’s a only a factor of 0.8, and in fact if you switch to imperial gallons the the 1% just switches from being a slight underestimate to slight overestimate.) So perhaps the best answer I can come up with is
all the people in Britain.
We can sense check that, and it seems to work. 1 billion divided by 70 million is about 14, so if a person is about 14 gallons, this is right. And since a gallon is about 4.5 litres, this is about 63 litres, and since people are mostly water and have a rather similar density to water, this corresponds to an average weight of about 63kg. This is at least in the right ballpack, and perhaps quite close, since the BBC reports the ONS as saying that the average British man weighs 83kg and the average woman 70kg. Allowing for some children, 63 sounds about right.
In fact, since people are 70% water, a billion gallons of water isn’t even
that far off the amount of water in all the people of Britain. Fantastic!
A friend mentioned that the diving events in the current (Glasgow)
Commonwealth games are being held here at Edinburgh’s Commonwealth Pool.
She was right:
(That’s a screenshot from Glasgow 2014, which, with luck, will change soon.)
But what’s this “1 billion gallons of water”? Surely that can’t be the amount of water in the pool, can it? I mean, that’s obviously wrong. Isn’t it? It is obviously wrong. But let’s just double check.
As we all know, an Olympic/Commonwealth pool is 50m by 25m. And the depth is something like 2m on average. So the volume is 50m x 25m x 2m = 2,500 cubic metres. That still doesn’t seem like it’s going to turn into a billion gallons, but let’s carry on. A cubic metre is 1,000 litres (a cube of side 10cm has a volume of 1 litre). So the pool has about 2.5 million litres of water. And a gallon is more than a litre. So QED.
Trying slightly harder (and still not looking anything up) a gallon is 8 pints and there are about 1.75 (imperial) pints in a litre (or about 2, if we only care about orders of magnitude). So we need to divide that 2.5 million litres by something between 4 and 5 (8/1.75 = 4.57) which will give us something a little over half a million gallons.
So there not only aren’t a billion litres of water in the pool: there aren’t even a million by my estimate. The claim is out by 3 orders of magnitude.
Now, of course, if you want to defend Glasgow 2014, they don’t actually say that the pool’s volume is a billion gallons. They just stick the phrase “1 billion gallons of water” under “Royal Commonwealth Pool”. Maybe it’s the amount of water the pool will use over its lifetime. Maybe it’s just an impressive amount of water. Who knows.
Why do I care? Only because I think it’s important people develop a good
sense of scale, and can spot when numbers are “obviously” wrong (even if
sometimes “obviously” wrong numbers turn out to be correct). An excellent
discipline physicists are often taught is
meaning that whenever you’re calculating anything you should first
guess the answer (literally, just guess); then make a crude estimate
by approximating the key components of the formula; then calculate the
precise answer. The idea is that this leads you to first to develop
better intuition about orders-of-magnitude sizes (by seeing when your
guess is significantly off), but also helps you to avoid believing
calculations that are orders of magnitude off, because the guessing
and estimation stages lead you to be surprised by an answer that
seems as if it can’t be right.
Ordinary people, quite reasonably, have no feeling at all for what a billion is,
because in ordinary life you rarely if ever encounter such numbers in contexts
where they can really be appreciated. Sure, people might know that the
population of the Earth is about 7 billion, but you can’t see 7 billion
people. Even more, people will hear about states and companies spending
and earning quantities of currency measured in billions (or occasionally
even trillions), but again, those are just abstract numbers. Even when
there’s hyperinflation and prices begin to measured in millions or billions,
the appreciation doesn’t really increase, because the million or billion
just becomes a suffix.
If you don’t have a feel for a billion (and who really does?), my two
favourite ways of getting some kind of handle on it are the following:
I always remember the number of seconds in a year as “pi times ten to the
seventh”, i.e. about 31 million. Since pi squared is ten (roughly), this means
that a billion seconds is about 31 years.
The other way I like to think about it is with respect to
centimetre cubes and metre cubes. When I was at school, we had wooden
1cm cubes that you could assemble into larger volumes. Obviously, a
1-metre cube contains one million centimetre cubes (100 ⨉ 100
⨉ 100 = 1,000,000). If you don’t immediately get a sense of
just how big that means a million is, get hold of some of those 1cm
cubes, and start arranging them to make the bottom layer of the
1-metre cube. (You’ll need 10,000 of them.)
A billion centimetre cubes is either one thousand of these
metre cubes, or a single cube of side 10 metres. Now a 10m by 10m room
is a pretty decent size, but will typically only be 2–4 m tall. So a
billion centimetre cubes would fill a room (say) 50m by 10m by 2m tall.
And so we come full circle. Because that 50m x 10m x 2m is not so far
off the size of an Olympic swimming pool (too narrow, at 10m, but pretty
similar otherwise). And it only contains a billion centimetre cubes.
So even if you have no real sense of how big a gallon is, you probably
know it’s orders of magnitude bigger than a 1cm cube.
Your call is valuable to us. Please stop bothering us.
Your call is valuable to us. (Variation for premium rate phone numbers): we make money by keeping you waiting on a premium-rate phone line, and the longer we keep you holding, the more we make.
We are currently experiencing exceptionally high call volumes. The call centre is open.
All of our operators are currently dealing with other customers. Neither of our operators is currently available.
Did you know that you can [long list of things you aren’t calling about] on our website at double-u, double-u, double-u dot ourwebsite dot com? The only good service is self-service.
One of our agents will be with you as soon as possible. One, Two, Three, Four, make 'em wait outside the door. Five, six, seven, eight, always pays to make 'em wait.
You may prefer to call back at another time. Preferably, once our lines are closed.
Please call back later. We’re going to disconnect you right now.
Please have your account number and password ready. We may have spent millions building this call centre and collecting data about you but don’t think we’re going to figure out your account number from your phone number.
For security reasons. We have crap IT systems that don’t talk to each other.
I’ll just need to pop you on hold for a minute. The system is about to drop the call.
I’ll just transfer you to the right department. Despite making you walk a telephone tree so we know how to direct your call correctly, we misdirected your call and now the system is about to disconnect you.
I’ll call you right back. I’m going home now.
Could you just confirm your phone number please? Our crap IT system doesn’t show me the number you’re calling from.
I’ll just need to take you through security. Our crap IT system handed you off between departments but didn’t pass on information that you’d cleared security.
Please listen carefully and choose from the following options: I’m now going to list four things you didn’t call about.
For anything else, type 4. Type 4 for another list of things you aren’t calling about.
Would you like to hear that list again? I don’t care that none of the options I listed is remotely relevant to your call. You have to pick a number. Take your time. I have all day.
In your own words, describe why you’re calling. You can say things like “to check my balance” or “to pay a bill”. You can say “to check my balance”, or “to pay a bill”. Of course, I might not understand you if you do. Pro tip: No IVR system in the world understands “I need to speak to a human being.”
I’m sorry, I didn’t quite get that: could you say it a different way? I already told you, the only things I understand are “to check my balance” and “to pay a bill”.
You said “to check my balance”. Is that right? I didn’t understand you.
Your call may be monitored for customer quality and training purposes. The NSA may be recording this call.
If you prefer, we can keep your place in the queue and call you back when an agent is free. We might or might not call you back. If we do, you might find there’s no agent on the other end. And regardless, you’ll have to type in the same security information you’ve already given us again. And even though we’ll have called you, we will still ask you for your phone number because our crap IT systems won’t show it to the agent.
Calls to this number from a mobile phone are not free. Just waiting to talk to an agent is going to cost you an arm and a leg.
You are calling the international access number from a UK phone. Please redial on 0870 XXX XXXX. We’d really like to charge you through the nose for this call, and ensure that you can’t use bundled minutes or all-you-can-eat plans to cover the cost.
Interactive Voice Response (IVR) System. Customer Alienation System. [Definition from Herb Edelstein of Two Crows]
Today I called Bank of Scotland because my credit card has almost snapped
Here’s what happened:
I dialled the number on the back of the card.
After one ring, a human being answered and said “Hello, Bank of Scotland
Card Services. How can I help?”
I explained that my card was damaged.
He asked for a few details (card number, address, and a couple of other
straightforward, reasonable things).
And then he said: “No problem at all; we’ll get a new card out to you in
the next few days.”
Twenty years ago, that would have been normal. Today, it counts as such
exceptional telephone customer service that I was moved to blog about it.
How times change.
By way of comparison, earlier this week (on 24th September), when my
land line (and therefore internet) had been down 5 days, and I was
trying to get better information from BT on a likely fault resolution
date than the website was predicting (23rd September, i.e. the
previous day), it took me 40 minutes, multiple lies, multiple security
interrogations, multiple holds, interminable muzak, endless
exhortations to visit bt.com and inordinate frustration before I
succeeded in talking to a human being. And when I did, he not only had no
information, but didn’t call back, as he promised to do within 15
Twenty years ago, that would have been unimaginable. Today, its as common
as the constant “exceptionally high call volumes” that seem to characterize
modern customer alienation systems.
When you set it up, you need to choose a daily target number of points. You get points for movement, but it doesn’t really tell you anything about the scale. It suggests three levels, which (from memory) were 600, 1000 and 1600, and it
described these with fuzzy terms that were something like “kinda active”, “active” and “super active”. I chose 1,000 points.
The obvious question is: how many steps is that, and how does it relate to the widely used recommendation that people do 10,000 steps a day (e.g. the UK National Health Service; according the Horizon episode Monitor Me, this is recognized standard).
Misfit Wearables don’t really tell you, so I thought I’d measure it. I did a short walks around the block three times, taking 1630 steps the first time and 1640 steps the second and third times. (I didn’t have a pedometer handy, and didn’t really want to compare one measurement error against another anyway, so I used a counter app, Tally Counter on the iPhone and counted every 10th step. I walked a few extra steps to make it a multiple of ten each time.) It doesn’t make any difference, but I know my typical stride length is just over a yard so this walk was around a mile (1680 yards). For the first circuit I wore the Shine using the sports band on my right wrist (I was also holding the phone in my right hand and tallying). The second time I used the magnetic clip on my shirt near the neck. The third time I clipped it onto the ticket pocket on my jeans. I synchonized the Shine immediately before going out and immediately upon return.
These are the results:
First (right wrist)
Third (jeans ticket pocket)
The first result seems very strongly to support my guess that they are simply using 1 point for every ten steps and seems to suggest that the Shine is very accurate at detecting steps both on the wrist and on the neck. The second and third ones are slightly off, but still close to that at 10.6 steps and 11.8 steps per point respectively. Obviously I don’t know whether I got lucky the first couple of times, or whether the wrist is a better location, but I still think this data suggests quite strongly that the Shine uses 10 steps = 1 point.
One thing the Shine doesn’t seem to have is a way to export the data (either in processed or raw form) from the phone. As a data analyst, I would definitely interested in getting some kind of data export so that I could look at other things myself. It would be great if Misfit were to add this at some point.
A long time ago I backed a crowd-funded project on Indiegogo for the Misfit Shine “the world’s most elegant physical activity monitor”. It blasted through its funding goal and suffered delays, but about a month ago they asked for a shipping address, though I don’t recall receiving a shipping notice. Nevertheless, two days ago my doorbell rang and a man from FedEx handed me a packet containing a Shine.
And I love it.
The Shine is elegant, beautiful even. It is understated but playful. It looks like a small, grey pebble, until you tap it twice. Then one or more of its twelve, twinkling, pure-white LEDs will shine, telling you how much you have moved today, relative to your goal. After that, in a delightful, ingenious way, the lights tell the time, to five-minute accuracy, a small antidote to the second-precision punctuality that modern life and gadgets so often seem to demand.
For me, so far, everything about the Shine is perfect. To sync it to an iPhone, you download and launch the app and then place the Shine on the phone’s screen. Activity data uploads, while the Shine puts on a light show and ripples spread out on the iPhone’s screen. It’s simple, but satisfying. One synchronized, the app shows graphs of your movements, highlights notable achievements and summarizes how you’re doing, this week, relative to a points target that you can set.
Unlike many activity trackers, the Shine uses a replaceable battery that lasts 4–6 months, so no recharging is required and you can wear it at night if you want to track sleep. It is waterproof and rugged, so you can swim with it. It comes with a simple magnetic clasp that makes it very easy to attach to clothing, and there are various watch-strap and necklace attachments too. In a touch reminiscent of the special tool Apple provides for iPhone users to open their SIM slots, the Shine comes with an elegant dedicated, tool for opening the battery compartment. (You could use a screwdriver, but it all adds to the feeling that they’re not skimping, that everything should be perfect.)
Oh: and as far as I can tell, it works. I don’t know how accurate it is, but the activity graphs look to match what I have been doing well, and the granularity of information is just right. Both days, so far, it’s encouraged me to move more, and it doesn't seem as if it's going to become a burdon.
I think Misfit Wearables has got just about everything right. I hope Shine becomes a massive hit.
So what’s this got to do with Scientific Marketing?
I didn’t post this with a view to its relevance to the usual themes of this blog; I just wanted to spread the word about my lovely new toy. But in fact, it’s not so far off topic.
The main focus of this blog is how marketing is used—well and badly, for good and for ill—to attempt to change people’s behaviour. Effective marketing campaigns cause people to do things (purchase, renew, stay, click, visit) that they would otherwise not have done. Proper campaign design, with appropriate use of control groups, allows measurement of the effectiveness of marketing in changing behaviour, while uplift modelling allows us to identify the people for whom a given campaign, action, or activity is likely to be most effective.
In a marketing context, one entity (the marketing organization) is trying to change the behaviour of another (typically a customer or a prospective customer). In the case of activity monitors, the two entities are the same: I wear a Shine with the goal of influencing my own behaviour. Like many others, I know that I am less active than I should be, and would like to get a little fitter. The raison d'être for activity monitors is to encourage us to move more, by providing feedback on how we’re doing and incentives to do more.
Two days in, with only myself as a test subject, there is clearly a limit to how much I can really say about the true effectiveness of the Shine. But I think it gets a lot right.
By being small and beautiful, and pleasing to interact with, it immediately encourages us to use it, to wear it and to interact with it.
By providing only coarse information (it can show only 12 different activity levels) it discourages obsession and constant checking every few minutes (which could easily be negative), but encourages periodic checking, which is helpful.
By including a rather elegant, minimal watch function, it gives another reason to interact with the Shine, giving activity feedback along the way. Additionally, my sense is that the implicit message of the 5-minute accuracy meshes perfectly with the big-picture message of Shine itself: don’t obsess about exactly what Shine’s points measure, just try to make sure you move enough to accumulate plenty each day.
By having a non-rechargable battery that lasts for months, and being sturdy and waterproof, it encourages wearing all the time, even at night, reducing the likelihood of finding yourself without it or breaking the habit of using it.
By making the iPhone app simple and minimalist, and making the sync process artificially pleasing, it encourages frequent interaction with the app, reinforcing progress (or lack thereof).
I think the people behind the Shine have pulled off something pretty amazing, and my prediction for myself is that I won’t abandon it any time soon, and it will prove a useful tool for changing my own behaviour.
My only connection with Misfit Wearables is that I backed their Indiegogo campaign and am the proud owner of a Shine. I would love them to succeed because I think they’ve made something excellent.
Labour MP John McDonnell has defied odds estimated at 58,000 to 1
to top the annual Private Member's Bill ballot for two years in a row.
That sounds pretty amazing.
Where does that estimate come from?
In the next sentence, we learn:
MPs' names are selected at random, with 240 having entered
the draw this year.
See what they've done?
If we assume (as I suspect the estimator did) that 240 people entered
in 2011 as well, then the probabity of Mr. McDonnell's
winning in both 2011 and 2012 is indeed 1/(240 x 240) = 1/57,600.
But that's like saying "isn't it amazing that even though the odds on
winning the lottery are about 14 million to 1 against, someone wins
I don't know how many people who enter the ballot year to year are
the same, but it seems likely it's quite high. Let's assume
(conservatively) that it's half. Then the odds of the same person
winning in 2011 and 2012 are not 1/57,600 but 1/480.
So it should be a rare event; but not that rare.
And of course, the odds of Mr. O'Donnell's winning in 2012 were 1/240.
Just as, if he enters along with 239 others next year, he'll still have
a 1/240 chance of winning. That would, however, be more genuinely
I wrote a book, with my friend and colleague Nicholas Tollervey
(@ntoll). It’s published by
O’Reilly Media and is available both as
a printed tome and a DRM-free, multi-format electronic book
direct from O’Reilly.
If you use the code AUTHD at checkout, you can get a discount, as described
The book is also available from Amazon.com,
Barnes & Noble
and all good booksellers, even local ones staffed by real people who love
Ordering direct from O’Reilly is probably quickest and lets you use the
All O’Reilly “animal” books come be known by the species on their
covers: the rather striking animal on our cover is
“a jellyfish-like animal of the genus Stephalia”, and you can read
all about it in the book’s Colophon. The image is from Lydekker’s
Royal Natural History.
For avoidance of doubt, the animal appearing on this work is real.
Any resemblance to fictitious persons, animals or
deities, is purely coincidental.
It is acceptable to refer to the book as “The Jellyfish Book” or the
“The Stephalia Book”, but definitely not “The Flying Spaghetti Monster Book”.
A new single-page description of uplift modelling in the context of retention
for mobile phone companies is available from Stochastic Solutions.
It aims to be the simplest, shortest description of the problem yet.
Google, Search History, Personalization and Bubbling
If you use Google and are worried by either the amount
of data it captures about you, the amount of personalization
it does or its consolidation across different services
(Web Search, Gmail, YouTube, Picassa etc.) you need to
act before 1st March to change some settings.
There are four main things you may wish to consider doing.
I’m not saying you should do this: if you like Google
keeping and integrating data about you across its services and then
using that to personalize ads, you probably want to leave these
settings as they are. But I don’t like it, so I have turned off
my Web History completely and Opted out of personalized ads.
I have been using a different search engine called DuckDuckGo a lot
of the time for a few months now. It doesn’t retain data about your
searches and also, doesn’t do what’s become known as bubbling.
Bubbling is the process of returning different results to different
users based on what the search engine thinks you want, based on many
different signals such as what you’ve clicked on before, where you’ve
been on the web, where you are in the world etc.
I’m not going to go so far as to say bubbling is bad or evil: many
people like it. But a consequence of it is that the range of information
you get presented to you is filtered by something guessing what you want,
with the result that you see an increasing narrow, unchallenging range
There are a couple if good resources to learn more about bubbling.
One is DuckDuckGo’s explanation of it at http://dontbubble.us/.
Another is a TED talk by Eli Pariser, who explains the issue very clearly.
You can see it at: http://www.thefilterbubble.com/ted-talk.
He also has a book called The Filter Bubble (which I haven’t yet read).
This article was motivated by listening to Episode 44 of
Hypercritical, the episode of
weekly podcast that focused on the
question “What Ails Microsoft?”; listen to it for context. I agreed
with most of Siracusa’s analysis, but thought he missed a few key
insights and perspectives.
You should listen to Siracusa’s podcast, but here are
some of the key points in his analysis of what ails Microsoft are:
Microsoft consistently refuses bet-the-company radical changes
that will be good for the user and its own long-term business
prospects because it are scared of damaging its cash cows
(primarily Windows and Office, but also servers, Exchange etc.);
Microsoft serves primarily PC vendors, IT departments,
backward-looking developers and perhaps Intel rather than its
end-users; this leads to poor user experiences;
Microsoft follows rather than leads and so is always behind the
curve (think Bing, XBox, Zune, Windows Phone etc.)
Microsoft underestimates its own position of strength, which would
in fact allow it to upset its customers more (to everyone’s
long-term benefit) for fear of losing what it has;
The demands of its core customers for a roadmap mean Microsoft
always overpromises and underdelivers, has low marketing impact
and never surprises competitors etc.
Apple is the reverse of all this, repeatedly taking
bet-the-company risks, always focusing on the end user, repeatedly
canibalising its own products, being secretive and never
publishing roadmaps, constantly leading and redefining categories
(without necessarily being first mover), all in manner of what
Steve Denning calls Radical Management,
which has led to its current position as the world’s most valuable
While I agree with most of these points, here is what I think Siracusa missed.
Clayton Christensen‘s The
is the best business book I’ve ever read. Unusually, it contains a
thesis that can’t be reduced to a single sentence. His interest is in
how great companies get overthrown by disruptive
innovators. His key ideas are as follows:
Christensen defines a disruptive technology as one that is worse
than the incumbent technology on the key metrics that are usually
used to measure quality in that space, but better in some other,
traditionally less important metrics.
Although he offers several examples, Christensen’s clearest
example is disk drives. Here, the two traditional key metrics are
speed and capacity. Disk technologies have been replaced in
waves, first with 8” disks being replaced with 5.25” disks, then
3.5” disks, then 2.5” disks then 1” disks. (Solid-state drives
are now gradually starting to replace rotating disks.)
Christensen argues that incumbent leaders almost always succeed
with sustaining (non-disruptive) innovations that improve the
performance of the technology against the standard metrics, but
almost always fail to bring to market new disruptive technologies,
even though these are often first developed by the market-leading
company. He says this happens primarily because leading companies
tend to be “well managed”, and are strongly influenced by their
best customers and partners, who are, almost by definition, mostly
bought into the existing metrics. So when, for example, Winchester
(the leading 8” disk manufacturer) asks its customers “would you
be interested in lower power, physically smaller disk that has
lower speed and less capacity they say “no, that’s a terrible
thing, we need speed and capacity”.
New entrants, often start-ups, see an opportunity to serve new
markets, often consisting of people not using the incumbent
technology, for whom the alternative metrics (in this case, size
and power consumption) are more important than the traditional
ones. For example, 8” disks didn’t work for PCs but 5.25” disks
did; 5.25” disks didn’t work for laptops but 3.5” disks did (and
then 2.5”); 2.5” disks didn’t work for iPods but 1” disks did.
Now solid-state memory, which is fast but expensive/lower
capacity, works for phones, cameras, tablets etc. in a way that
even 1” disks didn’t.
A key point Christensen makes is that the new market, of
non-consumption, is often unattractive to the incumbent leader, who
typically sees it as small and offering low margins, but is highly
attractive for newcomers, who typically hone themselves on lower
margins as they serve it.
Over time, sustaining improvements to the new technology tend to
improve it against the traditional metrics as well as the new
ones: current 3.5” disks have much larger capacities and better
latencies than did early ones. As they improve, they become more
viable in increasing parts of the “old” market, and the old leader
tends to be reduced to ever smaller, more niche parts of the
market. Eventually, the new technology tends to get good enough
for mainstream use and at this point the advantages of the new
technology start to be more interesting to old customers. (“So I
can enough speed and capacity, but with a smaller footprint, less
power consumption and a lower price: well sure!”) If it survives
at all, the previous leader ends up serving only the very high end
where the extremes of the old metrics are required.
Apple was not the first to come up with the idea of a Tablet PC. In
fact, Alan Kay came up with
many of the key ideas in his remarkable 1972 paper on the Dynabook. But in the more recent
past, Microsoft (especially Bill Gates) championed tablet computers
and brought them to market a decade before Apple built the iPad.
Microsoft, however, saw a tablet, through the ever-present and
distorting lens of its Windows cash cow, as an enhancement to a
traditional Windows PC: you add a touch-screen (and a stylus) to
traditional laptop running (of course) Windows and voilà, a tablet
The iPad received a very luke-warm reception when it was launched, and
was widely derided as (merely) a giant iPod Touch. It was criticized
for being underpowered, closed, not running even standard Mac
applications, let alone Windows software, not supporting “true”
multi-tasking or windowing and more besides. Yet it quickly sold in
the tens of millions and is clearly now replacing PCs for some people.
With some caveats, this fits Claytonsen’s model very well. The iPad is
a worse general-purpose computer against the traditional metrics. It
has slower hardware (though rarely feels slow), few ports, no user
accounts, comparatively little storage, no hardware keyboard, limited,
vetted software and (cough) no true multitasking, no Flash, no
replacable battery and limited upgrade options.
But look at the alternative new metrics, that show all the ways in
which it is better for some people and purposes. It is extremely
small and light. It is fantastically easy to use. Thanks to Apple’s
control-freakery, installing software is simple and worry-free. It has
a touch screen. It has no significant issues with viruses etc. Its
battery genuinely lasts over 10 hours even when you use the machine
intensively. It has stores for software, books, music and videos built
in (and it probably already knows your credit card number). It has
numerous sensors (cameras, microphones, accelerometers, gyroscopes and
more). Software for it tends to be really cheap and some of it is of
fantastic quality. It is supremely relaxing to use.
For people who mostly surf the web, do light email, play games, watch
films, read books etc., the iPad is not just a “good enough”
alternative to a laptop or even a desktop PC: it may actually be
signficantly better. The iPad 2 (and iOS 5) followed the pattern of
sustaining improvements, both on the new metrics (usability, weight,
size, sensors etc.) and the old (speed, capacity, ability to link to
an external monitor, multitasking etc.).
Crucially, while Microsoft saw a tablet as a way to extend the PC, and
added Touch features to Windows and made its tablet PCs full Windows
PCs “with added Touch”, Apple redesigned all the upper layers of the
operating system to give the best possible experience for the iPad as
a new class of device. It didn’t worry about disrupting sales of its
own Mac laptops, still less (naturally) those of Windows PCs: it just
made the iPad as good as it could, in its own right.
The other major point I feel Siracusa failed to make, and many people
are missing, is that Steve Jobs’s and Apple’s Radical Management is a
genuinely high risk strategy: it can fail as well as succeed, and
frequently does so. I think we need to separate out two ideas that I
feel are being conflated. The first is “betting the company” on an
uncertain new thing, which isn’t necessarily a good idea for a leading
company, but makes more sense for a struggling company. The
second is the the aggressive development and marketing of new
technologies that might canibalize your existing business; this
probably is a good idea, even if the new business is lower margin or
lower value, because almost certainly someone will do it, and it’s
better for the leader to do it to itself than for a competitor to do
In terms of the risk side, a comparison I like to make is with finding
lucky people. Contrast two situations. If I say to you “Give me a
coin and I’ll toss it ten times and get heads each time”, and then I
do it, you’ll probably think that is quite impressive and either very
lucky or (more likely) manipulated. But if I take a thousand people
and get each of them to flip a coin repeatedly, and after each round
of flipping I get all the people who got tails to stop, after 10
rounds I might well have a single person who got a sequence of 10
heads. But there would be nothing odd about that, and it certainly
doesn’t require the person to have special powers or be “lucky”
(in any non-scientific sense).
Apple now has the largest market capitalization of any company in the
world, with massive success and profits, after a series of audacious,
high-risk moves that worked out. I’m not saying for a moment that this
is pure luck, or that Apple is like the one-in-a-thousand kid who got
ten heads in a row, but I do think that the world has annointed Apple
after the fact when many other companies have made “audacious” moves
that didn’t work out and, in some cases, sent them under.
(Time-Warner’s merger with AOL was certainly audacious.) I think the
modern Apple has made a series of good moves, and combined those with
backtracking where necessary (allowing native apps, giving Final Cut
Pro a stay of execution, allowing various apps and books into the
stores after poorly judged bans etc.), and has won for reasons that combine
skill and luck; but even if Steve Jobs had lived, that doesn’t mean he
didn’t have more lemons in him, and that these might not have come out
and eventually hobbled or even killed the company.
Even today, when Microsoft is routinely left off the list of the key
tech companies (now typically Apple, Google, Facebook, Amazon), or is at
least seen as the laggard among these, it remains massively profitable
and powerful. I think it is in terminal decline, and deserves to be,
but it is far from irrelevant yet.