The bait-and-switch

The bait-and-switch has many names, but the concept is always the same.  You promise one thing (most often without the intention of ever following through) and switch your promise for something less appealing.

Car salesmen use this technique to sell cars.  They promise an incredible price, then later, before the paperwork is filled out, they say their manager won't let them sell it for that price.  

Event promoters are probably the most famous for the bait-and-switch.  They hype an event with the promise of a celebrity and free drinks.  In truth, it's a local celebrity, like a news anchor, and the free drinks are ones you wouldn't pay for anyway.

The bait-and-switch can be frustrating, so frustrating in fact, it makes you feel like you should just walk away.  But you don't.  You don't walk away because the "bait" was just the first push for you to make the decision to go.  

Like the poles propping up a circus tent, the first one gets the bulk of the tent's weight off the ground and makes all the other poles easier to put up.  The neat thing is that after a tent has been put up, you can remove any given pole, including the initial one, and it will still stand.  

Decisions then, are the tent.  They almost always have more poles than they need.  When you decide to go to the event, to rub elbows with a celebrity and get free drinks, your mind puts up a bunch of other poles to keep your decision firm.  You decide the event itself will be fun, and it's a good excuse to get off the couch.  Even at the car dealership, you fall back on your other poles.  You do like the car, and the salesman is very nice. 

These other supports for your decision combined with the justification that you are already there, and have already invested the time to get to this point, make it unlikely that you will walk away.

I don't support the bait-and-switch but the insight it gives us into our decision making is important.  It only takes one pole strong enough to get the side of the tent up for us to find all sorts of other support for a decision.

There is no need to throw all the benefits of your product at a potential customer.  They just need one really good reason to support the decision themselves.

Social Business Syndrome

Medical Student Syndrome is when students studying medicine perceive themselves or those around them to be experiencing symptoms of the disease(s) they are studying.  It sounds humorous, but can become quite serious.

Businesses seem to have a similar issue with the social web.  Every time a business hears about a new digital hangout, they want to be there.  The benefits of marketing where you audience is are obvious, but if you have business goals in mind, you aren't being a good member of the society.  

Some experts suggest that you use a ratio (7:1, 3:1, 9:1) for the number of "social" posts to the number of "marketing" posts.  Personally, I think the ratio method is just as annoying.  Being a part of a group creates a mandate to participate, but the flip side is that the group needs you.  

Posting 9 links to funny cats doesn't make up for your 1 hard-sell.

If you want to get social with your business, figure out where you fit in.  Be yourself and find a group that needs you.  Every business has something to offer.

The success stories of a photographer on Facebook and an author on Quora aren't powered by any ratios.  Success on the social web is powered by using your business product and expertise to help groups of people solve their problems.

How does your business participate socially?

Umwelt Testing

Umwelt is the German word for environment, often translated at "self-centered world."  The idea of Umwelt, with a capital U, is that even though your co-workers share much of the same world with you, their own experiences and biases make them perceive this world differently.  Effectively, we are all living in our own worlds, or Umwelten.

The concept of Umwelt is important to websites because it illustrates how hard it is to create a website that lets everyone else see your company the way you do.  

The following sequence of numbers seems random.

( 8 5 4 9 1 7 6 3 2 0 )

But, if you view them as words, instead of numbers, it's easy to see that they are merely alphabetical.

( eight, five, four, nine, one, seven, six, three, two, zero )

The primary goal of split testing is to avoid the error of rational change.  Rational change is a change that is perfectly logical in your world.  Making such a change to your website is only an error, if your visitors don't consider the change to be rational.  

The numbers above seem to be in a logical order, now.  But the things we don't understand are often labeled mistakes.  Split testing helps avoid this mistake by blindly comparing the "success" of the change to the original, pre-change, version.

The really interesting thing happens when you overlay other metrics onto your testing results; you can identify new segments, not based on demographics, but on how your visitors perceive and process your website.

Advice from the CRO experts

Why do most CRO experts suggest you test "big" changes on your site?

Some small changes can be extremely relevant depending on the site, but in general "big" changes offer the biggest chance of "big" success (and failure).

Move the needle.

Time is a valuable resource.  Big changes tend to move the needle faster.  A 5% increase in conversion can take months to collect the necessary visitor data.  A 50% increase only takes a few days.

The odds are against you.

The average tester, one who runs a split test, only picks a winner 1 in 7 times.  That means 85% of the time, you are hurting your business; costing it time, money, and valuable conversions.  (Even the experts only average 1 in 3.)  This negative record means you need a bigger win to cover your losses.

GreedyTest.com is a better way to test.  It minimizes the risks of testing and increases your ability to test small changes.  The project is just getting started, but if you're interested in learning more, give us your email and we'll keep you posted.

Micro Conversions vs Macro Conversions

Micro Conversions are often viewed as getting someone to move to the next step, while Macro conversions are viewed as someone completing a goal.

A macro conversion doesn't have to be a purchase, it is the completion of any business relevant goal.  Thus, if it is relevant for your business to increase Facebook likes, a "like" is a conversion.  Newsletter signups and survey completions are other forms of macro conversion.

Most analytics advocates disagree with me on this point.    The definition of "micro" is small and "macro" is large or overall.  So, they believe there is only one macro conversion / purpose for a website.  Ie. if you have an e-commerce website, the only macro conversion is a purchase.

While I can't argue with their logic, I believe that most companies have many different factors that drive business.  Thus, any full conversion that is relevant to a company's bottom line, is in fact a macro conversion.  Macro meaning purposeful and useful conversion.

To illustrate how a small non monetary conversion can drive business, we'll go back to the Facebook like.  I may "like" a Photography studio on Facebook because I think they take great photos, but that doesn't mean I have or will ever use their service.  My like isn't as relevant for me as it is for their other visitors.  By having the social proof that they do good work, they are able to drive more monetary conversions too.

Ultimately, your website shouldn't have any possible macro conversions that don't drive business in one way or another.

Micro conversions are checkpoints along the path to a macro conversion.  A micro conversion by itself is not a complete conversion and thus does not drive any business.  Micro conversions can simply be moving to the next page, watching a video, or filling out a single field on a form.  

Completing and submitting a form is not a micro conversion, unless you consider the form to only be a single part of a larger process.

In this way, signing up for the newsletter is not a micro conversion, because while you hope they come back and purchase later, the purchase process is not directly tied to the signup process.  It is, hopefully, tied to the awesome newsletter you send out.

If you set up your micro conversions correctly, they can help you identify the roadblocks in your conversion flow.  If a lot of people make it to the second checkpoint, but not the third, you can easily examine this segment of the process.  This laser focus will keep you from becoming overwhelmed and trying to test everything.

Are you measuring micro and macro conversions correctly?

Smarter split testing

The goal of split testing is to maximize conversions on your website.  A conversion can be any desired action or change from your users.  The general reason for using a split test is to be able to accurately measure the affect of your change on your conversion rate.  Assuming the change is in your favor, you can safely implement the change for all of your visitors without having to worry about the error of assuming your visitors will like your change.

The biggest problem with split testing is that it doesn't always increase your conversion rate.  In fact, there are three possible outcomes of a test.

• Increase conversions (by up to 50% of the possible increase)
• No change to conversions
• Decrease conversions (by up to 50% of the possible decrease)

The followup issue is that if you do come up with a positive change, you won't be able to fully realize the affects of your change until you stop the test.  

For high traffic websites, this may not be an issue, but for a 5-10% increase in conversion (depending on your current conversion rate), you need 100,000 - 1,000,000 visitors to reach statistical significance.  Meaning the results of your test are not random.  If your website gets 1000 visitors per day (nothing to sneeze at), it would take at least 100 days before you can comfortably stop the test.  

If your change would win you a 10% increase in conversion, 100 days of only a 5% increase (the amount you can realize during the test), isn't too bad.  But, if your change is a 10% decrease, that means for the next 3 months, you will have 5% fewer conversions than if you didn't test at all.

This issue is pervasive in the A/B testing world, and I have decided to do something about it.  I am starting a project at GreedyTest.com to create a split testing tool based on a modified Epsilon-Greedy algorithm that will maximize conversions during the testing period.  

The GreedyTest algorithm dramatically changes the possible outcomes of a split test.

• Increase conversions (by 98% of the possible increase)
• No change to conversions
• Decrease conversions (by only 2% of the possible decrease)

Note: the worse case scenario for a test is a decrease of only 2% of the potential decrease.  If you have a 2.0% conversion rate and the "bad" option has a 1.8% conversion rate, an A/B test will have a conversion rate of 1.90% during the test.  The GreedyTest will have a 1.996% conversion rate during the test.

The project is just getting started, but if you want to stay up to date with our progress and be the first to know when we are ready to launch, go to GreedyTest.com and give us your email.  A smarter testing platform is on the way.

Accurate or Usable?

Many great minds including William of Ockham (Occam) and Albert Einstein have come to the conclusion that solutions should be as simple as possible.  While "as simple as possible" implies that over simplification isn't any better than over complication, there seems to be a void between accurate and usable solutions.  

In statistics, higher levels of accuracy are achieved by adding complexity to the system.  If you could take into account enough variables, you could rather accurately predict the future.  But complex systems are highly vulnerable to errors, generally have a steep learning curve, and are hard to use and maintain.

Our mind solves the issue of over complication by looking for indicators that something familiar is about to happen and then turns on "auto pilot" to navigate us through pre-charted waters.  In business, we often try to do the same by looking for easy indicators vs worrying about the actual, complex results (which may come too late to be relevant or be too difficult to measure).

Google Analytics, along with almost all other third party analytics software, is notoriously in-accurate.  They gloss over the fact that all the numbers are wrong by highlighting their use for analyzing trends.  

A/B testing software is based solely on conversion rates, and disregards all other business indicators that would suggest a meaningful increase in business.  They brush off this criticism because conversion rates are generally a strong indicator for business.

To have a truly accurate analytics report, you would have to collect and maintain the data yourself.  To run A/B tests that take into account your other important business indicators, you would have to have a custom solution that hooks into your analytics and business data.  Creating and maintaining this level of accuracy would be difficult and require vast resources, not to mention how easy a tiny mistake could bring the entire system to its knees (or worse, incite the wrong business decision).  Systems like this don't scale to the outside world.

It seems the question in the modern digital world, isn't "how simple can we make it?" but rather, "How accurate can it be and still be useful?"