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When you’re creating content for the web, it’s easy to make assumptions about what you think your audience might respond to — but that’s not necessarily the right mentality.

Enter A/B testing: one of the easiest and most popular forms of conversion rate optimization (CRO) testing known to marketers. And while many businesses have seen the value in using this type of validation to improve their decision making, others have tried it, only to be left with inconclusive results — which is frustrating, to say the least. converting more visitors into customers, so let’s dive in …

4 Common A/B Testing Mistakes (And How to Fix Them)

Problem #1: Your testing tool is faulty.

Popularity is a double-edged sword — it’s true for high schoolers and it’s true for A/B testing software.

The ubiquity of A/B testing has led to a wide range of awesome, low-cost software for users to choose from, but it’s not all of equal quality. Of course, differing tools offer differing functionality, but there can also be some more tricky differences between tools. And if you’re unaware of these differences, your A/B tests may be in trouble before you even get started.

For example, did you know that some testing software can significantly slow down your site? This decrease speed can have a harmful impact on your site’s SEO and overall conversion rates.

In fact, on average, just one second of additional load time will result in an 11% decrease in page views, and 7% decline in conversions. This creates a nightmare scenario where the websites you were hoping to improve through A/B testing are actually hindered by your efforts.

It gets worse: Your selection of A/B testing software can actually impact the results of your tests, too. Entrepreneur and influencer, Neil Patel, found that the A/B software he was using was showing significant differences, but when he implemented the new page he failed to see conversions change. His problem turned out to be a faulty testing tool.

So with all these hidden pitfalls, what can you do to make sure your A/B testing software is working fine?

The Fix: Run an A/A test.

Prior to running an A/B test, you should run an A/A test with your software to ensure it’s working without impacting site speed and performance.

For the uninitiated, an A/A test is very similar to an A/B test. The difference is that in an A/A test both groups of users are shown the exact same page. That’s right, you need to literally test a page against itself. While this may seem silly at first, by running an A/A test you will be able to identify any distortionary effects caused by your testing software.

An A/A test is the one time you want your results to be boring. If you see conversion rates drop as soon as you start testing, then your tool is probably slowing down your site. If you see dramatic differences between the results for the two pages, then your software is likely faulty.

Problem #2: You stop testing at the first significant result.

This is the statistical equivalent to taking your ball and going home. Unfortunately, when it comes to A/B testing, stopping your test as soon as you see a statistical significant result is not just bad sportsmanship, but it also produces completely invalid results.

Many tools encourage this behavior by allowing users to stop a test as soon as statistical significance has been hit. But if you want to drive real improvement to your site, you need to fight the urge to end your tests early. This may seem counterintuitive, but the more often you check your test for significant results, the more likely you are to see incorrect results.

The issue here is false positives: these are results that incorrectly show a difference between pages. The more often you check your results, the more likely you will hit a result that has been thrown off by false positives.

This isn’t an issue if you stay calm and don’t end your test early. However, if you end your test at the first sign of a significant result then you’ll likely fall victim to deceptive false positive outcomes.

Analytics firm Heap published the results of a simulation, which displays how ending your test early compromises your results.

Using standard significance testing, results from a 1,000-user test are checked once there is a 5% chance of false positive. If the tester checked the same group of users 10 times, the chance of a false positive result balloons to 19.5%. If checked 100 times, our 5% chance of a false positive increases eight fold to 40.1%.

These are good numbers to remember next time you get excited about early promising results.

The Fix: Stick to a predetermined sample size.

To combat false positives, discipline is key. You should set a sample size in stone prior to running an A/B test and resist the urge to end your test early (no matter how promising your results look).

Don’t fret if you’re scratching your head on how large your sample needs to be. There are plenty of tools available online for calculating a minimum sample size. Some of the most popular are from Optimizely and VWO.

One last note on sample size: Keep in mind that you’ll need to pick a realistic number for your page. While we would all love to have millions of users to test on, most of us don’t have that luxury. I suggest making a rough estimate of how long you’ll need to run your test before hitting your target sample size.

Problem #3: You’re only focusing on conversions.

When you’re deep in the weeds of an A/B test, it’s easy to focus on the trees and miss the forest. Put more literally, in A/B testing, it is easy to concentrate only on conversions and lose sight of the long-term business results produced.

While adding new copy to your site may produce higher conversion rates, if the converted users are of lower quality then a higher conversion rate may actually create a negative result for the business.

It can be easy to fall victim to vanity metrics while A/B testing, yet these metrics will distract your focus away from the actual revenue-driving results. If you’re testing a call-to-action that leads to a landing page, you should not just focus on conversions to the landing page. Instead, measure the leads produced from the page and ideally try to tie those leads to the revenue they produce.

The Fix: Test a hypothesis.

Before you start your A/B test you should outline a hypothesis you wish to validate or disprove. By focusing this hypothesis on a KPI that drives actual business results, you’ll avoid being distracted by vanity metrics.

Your A/B test should be judged on its ability to affect this KPI, and not its impact on other associated figures. So if your goal is to increase sign-ups, always judge success by measuring sign-ups, not on clickthrough rates to the sign-up page.

When working to validate or disprove your hypothesis, don’t just throw out any results that aren’t statistically significant — use these results to inform your later tests, instead. For example, if a change to your page’s CTA showed a small, statistically insignificant improvement, then this could be a sign that you might be onto something. Try running further tests on your CTA and see if you can hit on one that produces a significant improvement.

Problem #4: You only test incremental changes.

The button color test may have ruined A/B testing, as this test’s popularity has made it the frame of reference for understanding how A/B testing should be utilized. But there’s more to the practice than that. In fact, while a large website might see a big return from adjusting something small like button color, for the vast majority of us, these small, incremental changes are not going to produce meaningful results.

A/B testing can force us to aim for miniscule improvements, but by focusing only on the incremental, we may be missing a much larger opportunity.

The Fix: Periodic radical testing.

A good rule of thumb? Periodically test radical changes to your page. (This practice has since been coined radical testing.) If you’re seeing weak conversion rates, then it’s probably a sign you should invest time in testing out a radical change rather than incremental changes.

Think of your testing efforts like a poker game, you’ll need to periodically bet big if you want to see a big return.

But before you run off preaching the accolades of radical testing, be aware that it has some drawbacks. First, it requires more upfront labor than A/B testing. Radical testing requires that you invest time drafting a major page redesign. Because of this time investment, I recommend only periodically conducting radical tests.

An additional pitfall to radical testing is that it makes it hard to pinpoint what factors are having the largest impact on your site. What radical testing does allow you to do is determine if a large page rehaul will impact your conversions, but it won’t allow you to pinpoint which individual changes might be driving these results — so keep that in mind before you get started.

These are a few of the most common A/B testing mistakes but there are many, many more. Share your thoughts below some of the missteps you’ve seen.

Getting started with something new can be pretty daunting. Heck, I’ve tried to learn the guitar at least four times by now. I may not know how to play a C chord, but I know it would have been easier to learn if I’d had a guide or teacher. 

For many marketers, getting started with inbound marketing can feel just as daunting as learning an unfamiliar skill, if not much more because their professional reputation is as stake.

To help, our latest ebook breaks down the who, what, when, where, and why of Getting Started with Inbound for Schools. You can expect to learn actionable tips for:

• Budgeting your time for inbound marketing
• Calculating the ROI of your inbound efforts
• Understanding your current marketing funnel
• Prioritizing the different tasks associated with inbound
• Building a foundation and setting benchmarks
• Starting your first content marketing campaign

Launching an inbound marketing program can seem a bit overwhelming at first. So many channels, so many metrics. There is a process to it all, and the more prepared you are, the more likely you are to be successful. 

You can download your complimentary copy of Getting Started with Inbound for Schools here >>

Like what you read? Feel free to share this ebook via Twitter with this Click to Tweet link.

It’s not often that you see the word “fun” and “algorithm” in the same sentence. (Okay, fine. Maybe you do, if you’re a marketing nerd like I am.) But think about this: Google has really been around for over two decades. With a history like that, there’s got to be at least some compelling trivia, right?

Believe it or not, algorithms are really cool. I mean, they get us our search results, after all.But how does Google’s algorithm work? And how has it evolved over the course of so many years?

We thought you might ask that, so we put together some fun facts about Google’s algorithm, and how it’s shaped the way we search today.

What the Heck Is an Algorithm, Anyway?

To quote Google itself, “Algorithms are the computer processes and formulas that take your questions and turn them into answers.” They cut through its estimated “trillions” of web pages in existence to find the information you’re looking for.

Think about that for a second. “Trillions.” One trillion, numerically, looks like this:

1,000,000,000,000

Imagine if there were no algorithms, and we had to somehow sift through that amount of information ourselves. Luckily, Google has developed an algorithm that can read — at a pace few of us can begin to fathom — different signals from these pages that indicate how likely they are to answer your search query.

But it’s not just about the words on the page. Algorithms can also read how recent the content is, how likely it is to be spam, and how it pertains to your location.

As marketers, all of this stuff matters. Where and how your pages rank in Google can make or break your organic search traffic, so it’s important to understand how the algorithm works and how to ethically optimize for it. What’s more, it’s crucial to be adaptable — the Google algorithm has changed a lot over the years, and will continue to do so as it becomes even more user-friendly.

8 Fun Facts About Google’s Algorithm

1) Google’s overall algorithm has had one name since 2013: Hummingbird.

Source: Search Engine Land

If you do keep up with the changes to Google’s algorithm, you’ve probably seen some colorful names assigned to them — Panda, Penguin, and Pigeon to name a few.

However, those names have only been assigned to updates made to the overall algorithm itself — which today is called Hummingbird. It was formally announced in September 2013 and created to make search results more “precise and fast” like the bird itself, according to Search Engine Land [SEL].

SEL has one of the best analogies we’ve seen to describe the algorithm at-large — Hummingbird is a “recipe” with hundreds of “ingredients.” These ingredients are the different pieces that help the algorithm determine the quality of those trillions of pages, and how well any one of them might answer your search.

2) Google makes changes to its algorithm roughly 500 times per year.

Source: pyxle

SEO community Moz states that Google makes between 500-600 changes to its algorithm annually, most of which are so minor that the public doesn’t usually hear about them.

Even without those minor changes, however, Moz has recorded no less than 140 updates to the Google algorithm since 2000.

Because the list was fairly dense, I enlisted the help of a colleague to count the items accurately. In splitting it up into two sections — the eight years before and after 2008, respectively — we noticed something interesting. The first eight years only listed 25 updates of note, whereas the latter had 115.

So why have there been so many more updates in the recent years? It could have something to do with the massive increase in users. But it could also be about changes to the way we search. For one, we’re searching on our phones a lot more — 51% percent of digital media is consumed via mobile — which has led to more than one crackdown by Google on pages that aren’t optimized for such platforms.  

We’re also starting to see an uptick in voice search. And while there currently aren’t precise formulas to plan or rank for those kinds of searches, we imagine that Google will start changing its algorithm for them — after all, it’s seen a 3400% increase in voice queries since 2008.

Like we said — understanding the algorithm requires agility. It’s only going to continue to change, so in order to maintain good search standing, marketers should learn to adapt.

3) One of the original goals was to cut through spammy content from advertisers.

Source: Stanford InfoLab

Google’s “history in depth” dates back roughly 20 years — in 1997, co-founders Larry Page and Sergey Brin were working on their first search engine, which they then called BackRub.

Then, in 1998, the pair published a paper at Stanford titled “The Anatomy of a Large-Scale Hypertextual Web Search Engine.” That’s where we see one of the first mentions of PageRank, which is the technology that Google continues to use to help rank search results.

But there’s one thing in the admittedly dense text that really stood out. At the time of writing the paper, Page and Brin noted, “the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users.”

We can’t help but geek out over the fact that Google remains loyal to that thesis. When I previously interviewed my colleague Marcus Andrews about the algorithm, he told me, “Google is very focused on the user.”

In fact, you could say that’s why Google has continued to make so many changes to the algorithm. It’s finding new ways to get the best content to users.

Just have a look at the search engine’s “Steps to a Google-friendly site” — one of the first things listed is to “provide high-quality content on your pages.” Eighteen years later, Google is working toward the original vision of its founders.

4) PageRank was named after Google co-founder Larry Page.

Source: Stanford InfoLab

When the name “PageRank” is assigned to the technology that helps Google rank pages, it seems fairly intuitive. But it was actually named after one of Google’s co-founders, Larry Page, whose young mug can be found to the right in the image above.

PageRank itself has quite a history. While its technology was in many ways beneficial, it was also very confusing, even to some expert SEOs. That’s why SEL published the in depth article, “What Is Google PageRank?” — very few people understood it.

Google says that PageRank is what “looks at links between pages to determine their relevance.” But SEL says it’s more like a voting system, in which inbound links to a given page count as votes toward its authority. So, the more votes, the more authority. The clincher? Anyone could view a site’s PageRank.

In spring of 2016, Google announced that while it would still be using PageRank technology to internally adjust its algorithm, the public would no longer be able to able to view any of its data. For some, that was happy news, according to SEL and its “retrospective on how [PageRank] ruined the web.” Apparently, PageRank’s emphasis on being linked to created a lot of annoying, borderline spammy behavior — like links becoming available for purchase.

Today, the technology for ranking has become more discerning, thanks in large part to MozRank, which is a “link popularity score.” To learn more about using MozRank for SEO and tracking competition, check out our HubSpot Academy guide here.

5) There’s a Google Dance — but it’s not what it sounds like.

Source: Search Engine Land

Our inner marketing nerds wish that “The Google” was actually a physical dance move. In actuality, though, Google Dance was actually the name applied to the sudden changes to its rankings, back when the algorithm used to majorly change every month.

Marketing Land credits forum WebmasterWorld for originating the term, and also for assigning different geographically-inspired names to each dance, like “Boston” in February 2003 and “Florida” later that year. But Florida, it seems, was the last dance — or the last salient one, anyway. That’s when Google stopped making major updates to its algorithm every month, and instead started making the general under-the-radar adjustments it does today.

But to keep track of these changes, especially the minor ones, it can help to keep an eye on the MozCast Google Weather Report. It assigns a temperature that indicates how much the algorithm has changed since the previous day — the higher and stormier the conditions, the greater the shift to Google’s rankings.

Don’t be sad — earlier this year, Google hosted an event at the SMX West conference called “Google Dance” to celebrate “an annual gathering for search marketers.” 

6) There isn’t *really* a reason behind the names for updates.

Source: Wade Creative Network

I would really love to think that there’s an adorable story behind assigning the name “Penguin” to an algorithm update. But according to Moz, there isn’t really a formal naming method.

Similar to the names for Google’s “dance moves,” WebmasterWorld users also named most of the other updates — “Boston,” because it was announced at SES Boston, and others in the same way that hurricanes are named, though it’s rumored that “Dominic” came from a Boston pizza place. 

Moz also reports that some of the self-named algorithm updates, like “Caffeine,” “Panda” and “Vince” came from Google itself, and that the latter two were named after Google engineers. 

7) Algorithms are also getting smarter for image searches.

Source: Forbes

Recently, Google announced the debut of the Pixel, its newest smartphone. Among its brag-worthy features? “The highest rated smartphone camera. Ever.”

Part of what makes the camera so great are its “its world-class software algorithms,” said Google camera product lead, Isaac Reynolds. That can be attributed to Pixel’s HDR+ algorithm, which helps users capture the best quality photos, despite lighting or movement conditions.

What does that have to do with Google’s search algorithm? Well, nothing directly. But it does show even more progress toward the quest to yield the best content for users, including images. In the realm of visual searches, it’s all about the Cloud Vision API — the technology that allows Google to analyze and determine the content of images.

Late in 2015, Google made that API accessible to the public, which allows geeks like myself to play with it and see how it reads the content of their own photos. Naturally, I had to take it for a spin, first with an image of my dog:

Next, I tried it with this nice photo of HubSpot’s blogging team: 

Whoa. How did it know that I had, in fact, uploaded a photo of a black dog? And how did it know that the second photo was of a team experiencing joy?  

It’s that sneaky, remarkable algorithm, which has been programmed — we predict using tons of existing images with various facial expressions, objects, landmarks, and more — to detect and recognize the elements and objects within an image.

Cool, huh? Give it a try here.

8) There’s a human side — the “search evaluators.”

Source: Google

Google enlists the work of human beings to evaluate the quality of search results. Each year, there are roughly 40,000 of these “precision evaluations,” as Google calls them, in which search evaluators determine the quality of results for different searches .

There’s a 146-page document that explains the guidelines used by search evaluators when rating results. It seems to be largely intended for people who are interested in becoming evaluators. But upon exploring the guidelines, the information might also help developers and marketers determine what constitutes search quality.

Different sections of it can even be useful to people who are just getting started with SEO. Have a look at the “Your Money or Your Life” section, which goes into evaluating a page’s potential implications for a user’s health and finances, for example. Some of the criteria might look like common sense, but it also provides some unique insights on how to keep your content accountable, especially if you’re giving advice.

There are also three different sections each dedicated to the highest, lowest, and medium quality pages. Again, what might seem like common sense can actually serve as valuable information to marketers — for example, if a page is deemed to have a “true lack of purpose,” it will be classified as “lowest quality.”

That’s something to keep in mind as you develop and manage your content. Have a read, and see if anything on your pages needs to change.

Have Fun With Search

So, there you have it — algorithms can be fun, after all, especially when you get to play with photo recognition API.

But with a history as rich as the one belonging to Google’s algorithm, there’s sure to be some interesting trivia, and just a splash of drama along the way.

We can’t wait to see what’s next. And, as always, we’re here to keep you posted.

What are your favorite pieces of the Google algorithm history? Let us know in the comments.

 

According to the Bureau of Labor Statistics, people working an average 8.8 hour workday are actually only productive for about three hours.

So where is all that wasted time going?

According to the Bureau of Labor Statistics study, the four most popular unproductive activities were the following:

1. Reading news websites – 1 hour 5 min
2. Checking social media – 44 min
3. Discussing non-work-related things with coworkers – 40 min
4. Searching for new jobs – 26 min

Given this data, it’s more important than ever before for teams to make the most of their productive hours.

We’ve compiled a list of seemingly innocuous phrases that could be secretly sabotaging your team’s productivity. Read on to learn what to avoid, and what to say instead.

6 Phrases That Secretly Sabotage Productivity

1) “I need that by the end of the day.”

When you tell a colleague that you need an asset by the end of the day, you’re essentially asking them to drop everything else they’re currently working on to focus instead on completing your task. This could potentially throw off their whole day, and lead to a problematic backlog they’ll need to scramble to unearth themselves from. 

Before you set an end of the day deadline, ask yourself: Do we really need this done by the end of the day? Is this a realistic time line? What else does this person have on their plate right now? Try to consider the project’s bottom line. Is not getting this component done by the end of the day really more problematic than pushing back this person’s entire schedule to get it done?

If this phrase pops up regularly in your office, it could be an indicator that your team needs to rethink the way you communicate around project goals and deadlines. A shared work calendar or other project management tool can help your team be more aware of what others are currently working on, and keep everyone on track with a shared time line of the project’s progress.

2) “The project is 75% done.”

This might seem like a productive way to assess the progress of a project, but providing a percentage isn’t the most accurate or helpful way to communicate how the project is really moving along. You might have roughly 75% of a project’s tasks complete, but does this really provide the best picture of where you currently stand? Not all tasks are created equal, and that last 25% could actually take longer and require more effort than the first 75%.

Instead of throwing around a percentage of completed work, communicate your progress more holistically: “Here’s what we’ve done so far, and here is what still needs to be done.” It’s a simple shift, but it gives your clients a much more precise, honest picture of where the work currently stands. It also helps your team more accurately understand the project’s progress.

3) “I’m not sure that’s the best approach.”

Challenging your colleagues’ opinions in a respectful, productive way has been proven to lead to more meaningful discussions and creative solutions. But if you’re going to dissent, make sure you can back it up — or you may just end up stalling progress instead.

Expressing mild dissent or uncertainty without clearly explaining why or offering viable alternatives doesn’t bring anything actionable to the table. It doesn’t give your team a place to start examining potential issues or brainstorming better solutions, since you haven’t really explained the perceived problem in the first place.

Yes, sometimes your gut just tells you something is off — but citing your gut doesn’t give your team anything tangible to go on. Challenge yourself to dig deeper into your own opinions and express the reasons behind them with firm certainty.

4) “Could you finalize the final final version?”

How many designers does it take to approve the final version of a project? In some cases, way too many. The approval process at some agencies is essentially a poorly-planned obstacle course — unstructured, time-consuming, and more than a little exhausting.

Without a formal approval process in place, projects can get stuck in a seemingly endless cycle of revisions and tweaks, resulting in several “final” versions of the same thing. Not only is this a major pain for your team, but it can delay the project and frustrate the client.

If you find yourself sorting through folders all titled with variations of “final_final_16”, it may be time to rethink the way your team finalizes projects. Take the time to agree on a straightforward approval pipeline at your agency, and stick to it. Remember: Abandoning perfectionism is the key to growing your business and producing better work.

5) “Let’s take this offline.”

This commonly used phrase frequently finds itself on management jargon blacklists, but it still manages to sneak its way into everyday office conversations.

“Let’s take this offline” is basically a thinly-veiled way to say, “I don’t want to talk about this right now — let’s deal with it later.” Sometimes, it’s perfectly acceptable and efficient to table a topic until later. Maybe the current setting isn’t appropriate, or there are more pressing matters to attend to.

But this phrase becomes problematic when it’s used to keep putting off more challenging conversations. It always seems easier to tackle the harder stuff later, but it only puts undue pressure on your team to get more done in a shorter period of time.

If you absolutely need to put something pressing on the back burner, don’t just push it away without explicitly planning a time and place to discuss it later. “Let’s talk about this at our morning meeting tomorrow,” is a lot better in the long run than, “Let’s avoid this as long as possible.”

6) “We need to think bigger / better / outside of the box.”

Thinking bigger and better sounds undeniably awesome, but it’s a practically meaningless sentiment. Some variation of this phrase usually gets thrown around at creative brainstorm meetings in an attempt to encourage divergent ideas, but it’s unlikely to spur creative insights or force your team to consider new points of view. Unfortunately, creativity doesn’t have an ON switch.

As an alternative, consider a quick creative exercise to get your team warmed up. Lisa Bodell, the author of Kill the Company, suggests playing “Kill a Stupid Rule” — a team game designed to jump start creativity.

The rules are pretty simple. Give your team 10 minutes to answer the following question: “If you could get rid of any rule, either kill it or change it, what rule would you choose and why?” Have them write their answers on sticky notes. When the time is up, have everyone stick their rule on a whiteboard with two axises: Ease of implementation on the Y axis, and degree of impact on the X axis. Like this:

Bodell recommends having a discussion with your team after all the rules are placed on the grid — Are there any rules you can cut on the spot? If so, do it. It will make your team see you’re willing to get rid of processes that hinder creativity.

For more ideas, check out these science-backed methods for improving creativity.

Are there any phrases that hinder productivity in your office? Share with us in the comments.