From How to Start a Two-Bit Operation: Small Business Tips

A few days ago we asked the supportive community over at Hacker News for some feedback on PickFu. We were extremely pleased to see that the overall sentiment was positive and that there were other entrepeneurs out there who have the same need for quicky and cheap polling.  In the spirit of some of the comments, we now offer a few more options for the number of reponses (50, 100, and 200) and for some basic demographic targeting (gender and age group).

If you’ve got some new logos you need to a/b test go give it a try!

Justin

From Startup Whisperer

I was talking to a friend of mine recently who runs a major national brand.  We were talking about the perils of running brand ads online.  His concern was that he didn’t have the ability to really understand where his ads were being placed or whether they were being seen by the right audience.  The folks at Mpire rolled out a service last year called AdXpose.  It asks as sort of the “Omniture for online advertising.”  Its an all-in-one solution to provide brand verification and campaign optimization for online ads.  The team put together a research white paper that you can request here that shows over 50% of online advertising is being wasted.

The chart below looks at the cost of delivering an ad impression.  As you can see for a standard $1.00 CPM remnant ad the cost of delivering it is typically .$10 when you load in all of the manual cost and technology.  This is basically a fixed cost so a higher CPM brand campaign ($10-$40 CPM ad) barely feels this cost.  Knowing that there is so much waste in advertising today – brands and agencies are starting to figure out that they have to tackle transparency and accountability.  The price of this brand protection is relatively small especially considering that there is so much waste.  Plus, the opportunity cost is huge since there is so much upside in having consumer brands move their budgets online.  If you no that 50% of your advertising is being wasted and/or harmful to your brand, then it would seem to make sense that you’d want to track your campaign(s) with a microscope.

A recent PriceWaterHouse Coopers study indicated that nearly 1 in 3
ads is never even seen because they are below the fold.  Today, only 7%
of the global US media budget is spent online.  80% of that volume is
distributed thru indirect channels like ad networks or ad exchanges.
The answer to the question on what is the price that a brand manager
would be willing to pay for brand protection – its priceless.

Some interesting thoughts from Mpire’s Kirby Winfield from this post on Adotas.  Kirby is always excited about talking to potential customers.

From cdixon.org

Anyone who has pitched VCs knows they are obsessed with market size.  If you can’t make the case that you’re addressing a possible billion dollar market, you’ll have difficulty getting VCs to invest. (Smaller, venture-style investors like angels and seed funds also prioritize market size but are usually more flexible – they’ll often invest when the market is “only” ~$100M).  This is perfectly rational since VC returns tend to be driven by a few big hits in big markets.

For early-stage companies, you should never rely on quantitative analysis to estimate market size. Venture-style startups are bets on broad, secular trends. Good VCs understand this. Bad VCs don’t, and waste time on things like interviewing potential customers and building spreadsheets that estimate market size from the bottom-up.

The only way to understand and predict large new markets is through narratives. Some popular current narratives include: people are spending more and more time online and somehow brand advertisers will find a way to effectively influence them; social link sharing is becoming an increasingly significant source of website traffic and somehow will be monetized; mobile devices are becoming powerful enough to replace laptops for most tasks and will unleash a flood of new applications and business models.

As an entrepreneur, you shouldn’t raise VC unless you truly believe a narrative where your company is a billion dollar business. But deploying narratives is also an important tactic. VCs are financiers — quantitative analysis is their home turf. If you are arguing market size with a VC using a spreadsheet, you’ve already lost the debate.

From cdixon.org

I recently tweeted:

New early-stage start up trend: get big quietly, so you don’t tip off potential competitors.

Chris Sacca agreed:

@cdixon Agreed. As of this morning, I have four companies who don’t want investors mentioning that they’ve been funded.

Business Insider took these tweets to mean “Stealth mode is back.”  But that’s actually not what I meant.  The companies I’m referring to (and I think Chris is referring to) are publicly launched, acquiring users and generating revenue. They are modeling themselves after Groupon, where the first time the VC community / tech press gets excited about them, they are already so successful that it’s hard for competitors to jump in.

This trend strikes me as a response to the fact that 1) raising money from certain investors can be such a strong signal that it triggers massive investor/tech press excitement, 2) things are “frothy” now – meaning lots of smart people are starting companies and easily raising lots of money, 3) word seems to travel faster than ever about interesting startups, and 4) there are big companies like Facebook and Google who are good at fast following.

I don’t know what to call this but it’s not stealth mode.  Maybe “underhype” mode?

From A Smart Bear: Startups and Marketing for Geeks

In the quest for optimization, A/B tests, metrics, and funnels, we’re in danger of losing the fun and value of creative work.

When we demand overwhelming customer outcry before committing to the slightest product change, we’re in danger of losing the value of creating a cool feature that takes too much effort but people just love.

When we do the minimum necessary to get the job done, we’re efficient but not thrilling. We’re “lean” but we’re not stirring hearts. We’re effective but not playful.

I’m as excited as everyone else about Lean principles gaining traction, and sure most companies are erring on the side of too little objective feedback rather than too much. Still, every article I read turns the creative process of business and product design into Vulcanian objectivity.

Sometimes, you should do something just because it’s cool.

Look at this incredible display of affection IHumanable has for his computer:

This is one of the reasons I love my new iMac, it’s just a beautiful magic floating screen filled with win.

You couldn’t ask for a stronger endorsement. This is even better than “It saved me $725,231.” This is beyond utility — this is love.

Does love come from feature bullet points? Do you earn love through A/B tests and implementing features off the top of GetSatisfaction? Or is this something else, something deeper, something less incremental, less data-driven, more gut feel, more emotional?

My first product at Smart Bear had a non-optimal, floating-in-win invention called the “mini-viewer.” Here’s its story.

Code Historian was my first product. It was the first file difference viewer with built-in support for version control systems, letting you view various historical versions of a file side-by-side. You could switch between which versions you were comparing with one click:

The thing to focus on is that user interface element in the bottom-right corner. That’s the “mini-viewer,” and in every measurable sense it’s a terrible business decision.

The mini-viewer summarized the modifications — the lines added, changed, and removed — so the user could easily see how many changes there were and where they’re located. Sounds useful, right?

Right, except it’s a really wasteful, expensive way to do it. Many competitors used a different technique I call “boogers,” because to me it looks like someone shot snot rockets all over the screen, and also because it’s fun to deride competitors, because it feels good to make fun of other people who (appear to) have more revenue than you do.

But don’t you agree they look like boogers?

The boogers are placed next to the scrollbar, indicating where you’d need to scroll to see differences between the two versions of the file.

Now by all of the usual arguments for Lean, Agile, and minimimalism, I should have used boogers too:

1. Boogers were already semi-standardized. User interfaces should follow the principle of “least surprise” — if people are used to a certain metaphor, icon, or behavior, you should honor that so people understand your product immediately. No one else had a mini-viewer.
2. Boogers occupy minimal screen real-estate. It’s just a thin strip no wider than a scrollbar; in fact some products put the boogers on top of the scrollbar. The mini-viewer is not only larger, it has significant width, which means you have to occupy the rest of the right side of the screen with other crap.
3. Boogers appear right next to the scrollbar, which is where you look anyway when navigating the file.
4. Boogers take less effort to compute than the algorithm for determining color variations in the mini-viewer.
5. Boogers take less effort to draw. Boogers are drawn on the screen once, and don’t change unless the window is resized — an infrequent operation. The mini-viewer however indicates your current scroll position in the file (those black brackets) so when you’re scrolling around the file the speed at which you can recompute and redraw the mini-viewer matters. If you draw directly on the screen it will flicker, so you need off-screen buffering. In short, the mini-viewer is a lot more programming effort with a lot more chance for bugs.
6. The mini-viewer doesn’t convey more information than boogers do.

And yet, everyone loved the mini-viewer. People sent emails saying they used Code Historian just because of the mini-viewer. Some developers wrote in asking how I was able to render it so efficiently. It was always a high point in product reviews.

The mini-viewer was wasteful, but fun. It wasn’t optimal and had no measurable benefit to usability, but it was “filled with win.”  It took extra effort but it was endearing — an important attribute not easily captured with metrics and spreadsheets.

Now sure, there are many of aspects of business and product development where it’s best to stop obsessing and just cut corners. Often we can and should accept 80% of the benefit if it means 20% of the effort. Customers generally prefer the right features over more features.

But sometimes it’s your job to fill the screen with joyous win.

From A Smart Bear: Startups and Marketing for Geeks

They say “statistics lie,” but they don’t. People do.

Well, that’s a little harsh. Sure some people intentionally skew numbers and selectively pull data, but most folks misinterpret data by accident.

Why do you care if you’re not a scientist?  Because you collect data about your business all the time — web traffic, revenue sources, expenses, customer behavior — and make decisions based on your (mis)understanding of that data.

Here’s a few basic mistakes I encounter constantly.

Statistics don’t tell the whole story

It’s easy to boil a data set down to a single number, like an average. Easy — and often shortsighted.

Single numbers feel powerful; you feel able to wrap your mind around a lot of data. Sometimes that is indeed useful, but it can also obscure the truth.

Consider Anscombe’s Quartet, four graphs that have identical statistical properties, yet clearly represent four distinct processes:

Since the statistics are identical in each case, it’s clear that statistics alone don’t describe what’s actually happening with the data.

The true story of each graph:

1. The process is mostly linear. The best-fit line is handy in describing the relationship, but there are other possibly-random factors at work as well.
2. The data are perfectly related, but not linear. Applying typical linear statistics is just wrong.
3. The data are perfectly linear, with one outlier. Probably the outlier should be ignored, and the best-fit line should reflect the other points.
4. The data don’t vary at all in the x direction, except for an outlier which probably should be ignored. All the standard statistical numbers are useless.

Lessons:

• Processes can’t be boiled down to a single number.
• Blindly applying statistics doesn’t explain what’s happening.
• Charts can help.

“Average” is often useless

You can’t open an analytics tool without being attacked by averages: Average hits/day, average conversion ratios, average transaction size, average time on site.

Trouble is, the average is often not only useless, but misleading. Take “average time-on-site,” a typical web analytics metric. It’s important enough in Google Analytics that it appears on the top-level site information dashboard, as shown in this real example from my blog:

Of course it’s better if a visitor spends longer on a site because it means they’re engaged.

Is 1:33 good? Actually that’s the wrong question. The true story becomes clear when you break this single number into pieces:

The “average” time-on-site of 93 seconds is useless when trying to explain user behavior. The correct way to think about time-on-site is:

1. Most visitors “bounce” off the site without really looking at it.
2. About a third of the visitors stayed long enough to read some articles.

Furthermore, the way you optimize #1 and #2 are completely different:

1. Bouncing can indicate that the traffic source is poor (i.e. we attracted eyeballs, but they weren’t the right eyeballs) or the landing page was poor (i.e. we attracted the right eyeballs, but we failed to lure them into reading further).
2. Getting a few minutes of time on a blog is already “success.” Trying to get someone to stay even longer (e.g. 10 minutes instead of 5) probably isn’t useful. So the better question is: How do we get more people into this category, rather than trying to “increase the average” in this category?

So not only is the average value 1:33 useless in describing reality, it’s useless in deciding what to do next.

Lessons:

• The simple “average” is often meaningless.
• Using a single number to describe a process obscures the truth.
• Using a single number to describe a process prevents you from learning how to improve and optimize.

The dangers of “Top 10″ and “Others”

Whether it’s a cover article in Cosmo or a web analytics report, people love to read “Top 10″ lists.

Top lists can be useful. For example, here are the origins of search engine traffic to my blog:

There are several “other” search engines (e.g. Ask and AOL), but the traffic doesn’t amount to a hill of beans (as we say in Texas). It’s useful to cut those out of the chart because they’re just noise.

The trouble starts when “Other” isn’t so trivial. The following chart is a real report from a board meeting I was in years ago (only the names and layout have been altered):

Looks fine. But later I was poking around the data myself and decided to add a category for “Others”:

Some people call this the Long Tail — a pattern wherein a few big players are far larger than any other single player, but when you add up all the little players they collectively match or — as in this case — tower over the big players.

If you discover a Long Tail in your data, there’s several ways to react. Consider the case of having a Long Tail in sales of your product line, as with iTunes and Amazon who have a few blockbuster hits plus a long tail containing millions of products that sell infrequently. Here are four opposing viewpoints of how you could approach the situation:

• The Long Tail is too expensive to sell into because it requires reaching a lot of people, each of whom don’t give us much money, so it won’t be cost-effective.
• The Long Tail is the least expensive way to sell because it means reaching under-served markets, which means cheap ads and hungry customers.
• Addressing the Long Tail means we have to be all things to all people, and that means we’re unfocused. Instead, let’s try to be #1 at one thing.
• Trying to be #1 at anything is hard, and often the spoils go to those with the most money, not to the smartest or most passionate. Rather than fight the 800-pound gorilla, let’s address the rest of the market that gorillas ignore, but which contains a ton of potential business.

No one of these views is automatically correct. For example, iTunes gets most of their revenue from the big players (contrary to “common” knowledge), but other companies like Beatport make millions of dollars off the Long Tail of niche music markets (electronic music, in their case).

The only wrong thing is to ignore your “Others” column.

Lessons:

• “Top 10″ lists can hide important data.
• Any time you truncate data you must first be certain you’re not throwing away important information.
• Data patterns like the “Long Tail” aren’t “good” or “bad” per se. There are usually many equally-viable ways for you to react.

Metrics and statistics “rules” cannot be applied blindly

Consider the following (intentionally unlabelled) chart:

It’s tempting to start making observations:

• The average value is 57. (But you already know this is crap, right?)
• The value is generally increasing as we move to the right.
• Some data is missing. Maybe they should be discarded.

Unfortunately, even these basic observations are assumptions, and could be wrong depending on context. Consider these scenarios:

1. These are a student’s test scores over time. The student was failing and not turning in assignments. However, in the middle of the period the student hired a tutor. Results improved, and by the end of the class the student had mastered the material.This student should probably be awarded an A or B because of the clear improvement and steady results at the end of the year when tests are hardest. The student should not receive a grade of 57 — the average.
2. Each result represents a survey of one person on the effectiveness of a certain advertisement.The “zero” rating from subjects #2 and #4 is real data, and it’s a bad sign. This could indicate something drastically wrong with the ad, for example being offensive. We need to dig in with those participants and learn more about this failure.In general the average value — including the zeros — is probably a useful indication of the ad’s overall effectiveness. It’s curious that the results “improved” so much in later trials since the participants were supposed to be randomized.  This may indicate a bias in the test itself.

An interesting result of #1 is that in order to obtain a useful “average” value we ought to throw away almost all our data points! The opposite is true with #2.

The point is that the context for the data determines how the data is interpreted. You can’t blindly apply a “rule,” such as which data points can be ignored.

Lessons:

• You have to interpret results in context, not blindly apply formulas.
• Form a theory first, then see whether the data supports or invalidates your theory.

Formulas are not a substitute for thinking.

Like any tool, statistics is useful when used properly and dangerous otherwise. Like any algorithm, garbage in yields garbage out.

Yes this means “metrics analysis” is harder than it looks. Yes this means you have to take time with your data and verify your thought process with others.

But what’s the alternative? Thinking about your processes incorrectly and then wasting time on senseless “solutions?”

Final lesson: Since metrics are hard and take time and effort to get correct, don’t attempt to measure and act on 100 variables. Pick just a few you really understand and can act on, and optimize with those alone. You’re more likely to make a genuine, positive change in your business.

What tips do you have? Leave a comment and join the conversation.

From cdixon.org

From far away, things that are very different look alike. I grew up in a family of musicians and English professors. To them, the entire financial industry seemed corrupt. When I worked in finance – first on Wall Street and then in venture capital – I saw that the reality was much more nuanced. Some finance is productive and useful and some is corrupt and parasitic.

Most financial markets start out with a productive purpose. Derivatives like futures and options started out as a way for companies to reduce risk in non-core areas, for example for airlines to hedge their exposure to oil prices and transnationals to hedge their exposure to currency fluctuations. The sellers of these derivatives were aggregators who pooled risk, much like insurance companies do. The overall effect was a net reduction in risk to our economy without hampering growth and returns.

Then speculators entered the market, creating more complicated derivative products and betting with borrowed money.  This was defended as a way to increase liquidity and efficiency. But it came at the cost of making the system more complicated and susceptible to abuse. Worst of all, these so-called innovations increased the overall risk to the system, something we saw quite vividly during the recent financial crisis.

Venture capital is a shining example of capitalism just like Adam Smith pictured it, where private vice really does lead to public virtue.  Consider, for example, two of the largest areas of venture investment: biotech and cleantech.  Here we see the best and brightest – top science graduates from places like MIT and Stanford – devoting their lives to curing cancer and developing new energy sources.  These students may be motivated by good will, but need not be, since they will also get rich if they succeed.

A strong case can be made that the financial industry needs significantly more regulation, particularly around big banks and derivatives markets. But it would be a tragic mistake to create regulations that hinder angel investing and venture capital.  From the outside, VC and Wall Street might appear similar, but the closer you get, the more you understand how different they really are.

From cdixon.org

It is common to hear entrepreneurs and investors talk about the high level of engagement (what we used to call “stickiness”) of their website.  They quite rightly believe that it’s better to have a more engaging user experience, as that generally means happy users. Unfortunately, the dominant advertising model on the web – Cost per Click (CPC) – rewards un-sticky websites.  As Randall Lucas said in response to one of my earlier posts:

The paradox, it seems is this: in a pay-per-click driven world, site visitors who want to stay on your site — due to it having the once-much-lauded quality of “stickiness” — are worth much less than those who want to flee your site because it’s clearly not valuable, and hence will click through to somewhere else.

Facebook recently became the most visited site on the web. Yet their revenues are rumored to around $1B – about 1/30 of what Google’s revenues will be this year. Google has the perfect revenue-generating combination:  people come to the site often, leave quickly, and often have purchasing intent. Facebook has tons of visitors but they generally come to socialize, not to buy things, and they rarely click on ads that take them to other sites. Facebook is like a Starbucks where everyone hangs out for hours but almost never buys anything.

The revenue gap between sites like Facebook and Google should narrow over time.  Cost-per-click search ads are extremely good at harvesting intent, but bad at generating intent.  The vast majority of money spent on intent-generating advertising — brand advertising — still happens offline. Eventually this money will have to go where people spend time, which is increasingly online, at sites like Facebook. Somehow Coke, Tide, Nike, Budweiser etc. will have to convince the next generation to buy their mostly commodity products. Expect the online Starbucks of the future to have a lot more – and more effective – ads.

From A Smart Bear: Startups and Marketing for Geeks

It’s easy to be taken in by the idea of the Butterfly Effect: That a butterfly gently flapping its wings in the jungles of Madagascar can indirectly cause a Typhoon off the coast of Jakarta.

Or, updating for modern-day relevancy, Naomi Dunford pounds a curse word into a WordPress and Brian Clark makes $172. Or Dave McClure releases a silent-but-deadly outside a Menlo Park Starbucks and a social media company gets funded in Boston.

It’s a great story: Little actions can have enormous influence. A small favor you do on Twitter results in a viral post seven months later. A small change to your download page results in 20% more trials. A subtle shift in background color increases average time-on-site by 27 seconds.

We’re willing to believe it because mathematicians have proven it’s true for complex, fluid systems like weather and economics.

We want to be believe it because it’s harmonious and comforting to think that everything is connected, and that the tiniest action has the potential for significant effect.

“Even the smallest person can change the course of the future.”
—The Fellowship of the Ring, J.R.R. Tolkien

For me the most compelling evidence comes from cognitive psychology where studies abound with astounding tales of subtle environmental changes radically and systematically affecting people’s behavior.

It’s relevant for marketing and sales because it’s an inside scoop about how to manipulate strangers on the sly. It’s akin to subliminal messaging, but more pervasive, more powerful, and less susceptible to biting satire.

Eerie examples:

• Touching merchandise while you’re shopping increases the chance that you’ll purchase it. (source)
• Students performed word-searches from random words. Some of the puzzles were seeded with words associated with old age, e.g. gray, wrinkle, bingo, Florida. While traversing a hallway after solving the puzzle, those students given “old” words walked more slowly. (source)
• Students took a survey about health risks; half walked down a hallway where someone was sneezing. Those who passed the “ill” confederate reported a more negative view of the American health system and believed the average American was more likely to die of heart attack. (source)
• Students were asked to recount memories while moving marbles between two trays. When moving marbles from a lower tray to a higher one, the memories were more positive; when moving downward the memories were more negative. (source)

This news should be simultaneously titillating for marketers (“Ooo, puppet strings!”) and frightening for consumers (Are you ever in control of your own decisions?).

But actually, when taken to its logical conclusion, you have to ignore most of it.

After all, these studies must be just the tip of the iceberg. When I’m at the mall I’m passing people who are coughing just like the experimenter in the study… but also people who are angry, laughing, sitting, jogging, yelling, sleeping, shoplifting, and eating. Each storefront beckons me with colors, shapes, fonts, compositions, arrows, borders, lighting, and even sounds and smells.

All this is (apparently) tugging me in different directions, just below the veneer of consciousness where my impulsive, subconscious lizard brain is eagerly lapping up the stimuli and directing my attention and my wallet.

But then again, despite these impressive efforts, I’m distracted by the P.A. system blaring about a 6-year-old knee-deep in the fountain outside the Men’s Dillards. And then my cell phone goes off with a new tweet mentioning @asmartbear and my heart goes all aflutter (Ooo, attention! Please love me so I can love myself!). And then a butterfly flaps its wings (this time in Argentina) and suddenly and inexplicably I decide against the indulgence of a Double Doozie Cookie®.

It’s worse on the Internet. You’re competing not only with the real world but with the virtual world of tabbed browsing, Twitter alerts, back buttons, bouncing tray icons, and instant messaging.

It seems to me that instead of chasing subtle subliminal effects, most of which will be wiped away by the ambient noise of life, we could spend our time on the big-ass, in-yo-face, non-subliminal effects.

Like, if you get a popular blogger to mention you, that’s more influential than the color of your logo. (200 words from Seth Godin is good for 1000′s of unique visitors.)

Like, if you have a compelling story that people intrinsically want to spread, that’s more influential than building a snappy Flash animation for your home page. (Kiva and Zappos win not just because they are awesome, but because it’s awesome for you when you tell other people about their awesomeness.)

Like, if you thoroughly thrill one person in a product demo, that’s more money in the bank than 1,000 people hitting your website and getting “branded” that you’re “trustworthy” because of your steel-blue color palette and stoic font. (I’ll take one Tom over ten thousand StumbleUpon hits.)

I like the idea of subtle yet powerful influences as much as anyone else, and I’m not saying design and attention to detail isn’t important or valuable. I just think most of our efforts are drowned out by the seething distraction that is the Internet and life in general.

Take care of the big stuff first.

From Inspired Startup

I was turned on to this innovative Seattle startup that focuses on improving the lives of extremely poor through the use of educational loans.  It is self-sustainable as 97% of the loans are paid back and can be used again to loan to more people in need.  Ideas like this can change the world.  I love it and that’s why I just placed my first loan in the program and started a group to compete in their March Madness Challenge – anything that ties in the sports world is very cool.  Having been to Central America several times, I chose to loan to Evalesthy Mercado in Nicaragua.  You can read about her story here.  It is refreshing to see entrepreneurs tackle the issue of extreme global poverty and we need to support them.  Whether it is Vitanna or another great Seattle-based organization like One Day’s Wages – if you have the means to give, please do.  Each dollar is directly given to those who need it most, meaning 100% of your donations go to those in need.  This is the new breed of non-profits and transparency at its best.  If you don’t have the means to give, talk about the issues and raise awareness amongst your peers – it’s what I call “social giving”.

Who are some of your favorite non-profits or for-profits that are doing innovative work in solving global poverty?  I’d love to hear about them!  Perhaps, you are ready to embark on a new journey starting your own?