Do you know what A/B testing statistics are?

It’s OK if you don’t. Most marketers and business don’t track conversions, let alone test their websites.

The thing is, you’re missing a huge opportunity to improve your conversion rates. Think of what a 1% improvement in your conversion rates will bring.

Read to find out how your business can benefit from A/B testing and how you can get started.

What is A/B Testing?

A/B testing is the process of testing various elements of a website, product page, landing page, or advertisement. You’re comparing two versions of them to see which one gets better results.

A/B testing is a tournament in a sense. You test two versions against each other, and the winner moves on to be tested against something else. That keeps going until you have a clear winner and your conversions are through the roof.

The reason why it’s important to do is that one small tweak can make a huge difference in the level of response that you get from people.

Most businesses don’t bother with this step because it can be time-consuming and it requires patience.

How to Track A/B Testing Statistics

Are you convinced that A/B testing is something that you should try? Here are some tips you can use to help you test your content.

Decide What to Test

The very first thing you need to do is to decide what needs testing. The most common elements that are tested are headlines, calls to action, images, copy, button color (usually on landing pages), offers.

This is a small sample of what you can test. With so much to choose from, where do you decide to start?

Look at your data analytics to decide. For example, let’s say that you want to test a landing page to see where you can make improvements. Are people staying on your landing page but not converting? You want to pinpoint the place where you’re losing your audience.

If you lose people immediately, it’s usually because the headline doesn’t resonate with your audience. You can start there to test.

Testing is Based on Assumptions

A/B testing is really based off of assumptions. You assume that the element that you’re testing is the issue.

You’re also making a lot of assumptions about your audience. You assume that they come across your content with a certain intent (educational, product research, make a purchase). You assume that they’ll behave a certain way and the problem that they want to solve by signing up.

You need to make sure that you note what those assumptions are as you decide what elements you’re going to test.

Track One Thing at a Time

The biggest mistake that people make when A/B testing is that they test several things at once. They’ll test several elements at once. They might test a call to action and a headline at the same time. They might test two completely different pages.

It’s great that they’re testing, but what happens when you look at your A/B testing statistics? You won’t be able to tell which elements are getting the best responses and which ones aren’t. You could be doing more harm than good.  

Collect Enough Data to Make a Smart Choice

Another common mistake that marketers will make is that they make decisions based on a small sample size. They’ll run a test for a day or two and then make decisions based on that statistical analysis.

The problem with that is that you’re working with a small sample size that isn’t indicative of what’s really going. Depending on the type of content you’re testing, you want to run the test for at least a couple of weeks before making a decision.

That means that you need to be able to generate enough traffic or impressions to gather enough data to make a smart choice.

Look at the Numbers that Really Matter

People tend to get distracted by vanity numbers, rather than the numbers that really move the revenue needle. For example, you might be impressed that your landing page or ad has thousands of impressions.

That’s great if you want to create brand awareness. Yet, if the purpose of your landing page or ad is to drive revenue, then you’ll want to look at another set of numbers. You’ll need to look at your click-through rate and conversion rate.

You want to go beyond impressions and followers. You want people to take action. The data that you find most important should be related to taking action.

Use the Right Tools

Your decisions are only to be as good as the data that you collect. Therefore, you want to make sure that you use the right tools to collect data.

First, you need to decide what you’re going to test. Then decide what data you’re going to rely on to determine the results.

There are many analytics tools out there that you can use. You want to choose the tools that align with your KPIs. You can use website analytics, test automation tools, or advertising analytic tools.

How to Make the Most Out of A/B Testing

A/B testing is one of the best ways to improve the ROI of your marketing. By continuously making small improvements over time, you’ll improve your conversion rates and your bottom line.

Testing requires patience, using the right A/B testing statistics, and the right tools to collect data. Then you can make smart, data-driven choices to move your business forward.

Want more great marketing tips? Take a look at this article on the future of digital marketing.

0 Shares:
You May Also Like
Read More

Introducing The Raspberry Pi 3 Model B

The much anticipated new version of the popular $35 mini-pc - The Raspberry Pi 3 Model B is here. The board made appearance at the FCC website revealing all details a few days ago and is now officially released by the foundation for ordering. Major new features include a new 64-bit ARM 8 1.2GHz Quad-core Broadcom BCM2837 CPU with on-board WiFi and Bluetooth Low Energy. Everything else remains the same, the maximum power draw has been upgraded to 2.5A@5V from 1.8A@5V to allow more power hungry USB devices without a need for a powered USB hub.

The Raspberry Pi 3 Model B

Raspberry Pi 3 Model B specifications :

  • Broadcom BCM2387 chipset, 1.2GHz Quad-Core ARM Cortex-A53
  • 1GB RAM
  • Dual Core VideoCore IV® Multimedia Co-Processor. Provides Open GL ES 2.0, hardware-accelerated OpenVG, and 1080p30 H.264 high-profile decode. Capable of 1Gpixel/s, 1.5Gtexel/s or 24GFLOPs with texture filtering and DMA infrastructure
  • 802.11 b/g/n Wireless LAN
  • Bluetooth 4.1 (Bluetooth Classic and LE)
  • 40 pin GPIO
  • 4x USB 2.0 ports
  • MicroSD card slot
  • CSI camera port
  • DSI display port
  • HDMI
  • 4 pole stereo and composite video port
  • New Switched power source up to 2.5A

This entry passed through the Full-Text RSS service - if this is your content and you're reading it on someone else's site, please read the FAQ at fivefilters.org/content-only/faq.php#publishers.