A/B Testing: Hotjar vs FigPii

 

What’s A/B Testing?

A/B testing is a very simple concept that can be broken into two stages: creating a hypothesis and presenting different versions of the page to visitors. 

The first stage is where most marketers fail, but I’ll get to that later.

If you present multiple versions of something on your sites, such as a form or an image, you can track which one performs better than the other. 

If the changes result in more people converting (e.g., filling out your form), then your new variation will become permanent and continue to run on 100% of users who land on that page until further notice. 

It’s called ‘continuous deployment’. You don’t have to release updates just for aesthetic purposes! If no one likes it, it gets tossed.

You can also use various types of testing to look at conversions, but I’ll focus on the most obvious one: A/B Testing. 

This is where you have two versions of a page that are exactly the same except for one variable (e.g., headline, form placement).

The Basic Example

Let’s say you run an eCommerce site and want to sell more products. 

You know that buying online has three main factors that influence people into making the purchase: price, convenience, and trust. 

That means if “trust” is important to your customers, they might not buy from you because they don’t believe in your company enough yet. 

So how could you solve this? Test out some headlines!

Hypothesis: “If we test 10 different headlines which highlight our trustworthiness, we’ll convert more visitors into customers”. 

I know this is a little silly, but it’s just an example. 

In reality, you could probably tell by your analytics data that trust is a major issue for people who aren’t buying from you.

Stage 1 – Creating Your Hypothesis

Your first step is to write a hypothesis. Here’s what ours looks like:

Our Hypothesis: “If we test 10 different headlines which highlight our trustworthiness, we’ll convert more visitors into customers”.

This really isn’t too complicated, but it does have a few parts that need to be explained. 

First of all, you must know who your audience is and what they’re looking for when they land on your page. In this case, I’m assuming our customer wants to buy from us because they’re interested in our product and affordability.

Second of all, you need to know why your customer needs whatever it is that you’re selling. 

In this case, a buyer probably wants an affordable product with great customer service. 

We know this because we do something very few eCommerce sites offer: live chat on our site.

Thirdly, you need to think about the questions your buyer would have when looking to purchase from you. 

In our example, a customer might be wondering how we’ll provide them with quality customer service if they have a problem.

Fourth, you need to make a statement about what you’re testing. 

In this case, we want to test ten different headlines that focus on our reliability and customer service. 

Lastly, you need to understand why each element of your hypothesis is important. 

That means if we don’t test all three factors (price, convenience, trust), then we might not be able to draw any conclusions at the end.

Stage 2 – Creating Your Test

Now that you’ve thought about the benefits and needs of your product and audience, it’s time to create a few headlines. 

As we’ve just mentioned, we need something that shows we’re trustworthy and easy to buy from. So let’s try:

“We’ll treat you like family!”

“We work hard to provide quality products and customer service.” 

“Free shipping with no minimums. Ever. – We love our customers.”

Those all sound a little cheesy, but they do relate directly to why people buy from eCommerce sites: price, convenience, and trust.

Stage 3 – Running The Test!

Now, we need to choose at least one control and one variant. 

The control is the original version of your site that you’ve been running for a while (maybe even years). 

The variant is the new headline that you’re testing against the original.

You’ll need to create a plan of how exactly you’re going to test your headlines. 

Here’s what ours looks like:

We’ll run our experiment for four weeks and see which headline drives more conversions per week (conversions equal purchases or some other form of action taken on our site, like scrolling down a page).  

To make it easy on us, we can compare points in total and not the headline that got the most points. 

For example: price and convenience will both be worth 3 points each, while trust is only worth 2. 

If we get ten conversions on price and five on convenience, we’ll take this as a win for price because of its difference in total converted (15 compared to 10).  

As such, we can make our decision based on total points rather than who won each individual “round” (a week) at the end of four weeks. 

We also need to make sure our page is 100% equal except for our headline, which is about 50/50 with a difference in one element between it and the original. 

This means everything from the color scheme to the order of bullets needs to be exactly.

Stage 4 – Analyzing The Results

Once you’ve run your test for a significant amount of time, it’s time to see if your results are conclusive. 

Remember what your goal was at the beginning? 

To find out if headlines that highlight our trustworthiness will convert more visitors into customers.

Hopefully, it’s obvious that you’ll then want to check both pages to see how many people bought from each one and then compare those numbers with one another! 

If “trustworthy” wins, great! Write some new variations using the same headline but with different benefits or needs highlighted for future tests. If “easy-to-use” wins, write those headlines down as potential options as well!

Your only job now is to keep testing, optimizing, and improving your site until you begin to find the perfect headline which will convert the most visitors into customers.

Stage 5 – Implementing Your Solution

Once you’ve found a variable that works, make sure you use it on your site going forward! 

However, don’t get too attached to the headlines you’ve already used if they aren’t converting. It might be time to do some more testing and see what happens when new variables are introduced into the mix.

That’s all there is to it! 

Really, that’s all it takes when you’re just starting with A/B testing: finding an interesting idea and then running with it until you find something that works!

Now let’s jump into the comparison.

A/B Testing Hotjar vs FigPii

 

Now, what makes FigPii different is that it offers you an all-in-one solution for your needs.

Hotjar looks nicer, but using multiple platforms to track different analytics is a recipe for disaster.

You have 1000 visitors to your website, and you are tracking them via GA; you go to Hotjar and see their heatmaps and session recording, and lastly, you go for FigPii to see how’s your A/B test going.

What you’ll see is that the numbers each tool sends back are different!

Because each tool has its metrics and algorithms to track specific analytics, they’re not the same.

That would throw you off because you’d have different sets of data, all from various sources.

FIgPii integrates with GA to provide the best possible data for our users.

If you’re interested in A/B testing, maybe check FigPii out. If you’re happy with Hotjar and not looking to switch, that’s fine; you need to keep in mind that you need to do some adjusting.

But we offer a 14-days free trial, so we welcome you to try things out and see how it goes.

Maybe try both tools for a short period of time and see which tool/s stack enables you to choose right and increase your conversion rates!

Because FigPii and Hotjar both care about their users’ conversion rates and hope to make it better!