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Let us run your experiments

We live in times of data-driven marketing. Lost are the times where marketing is exclusively throwing money at things and hope for a favorable outcome. The modern-day marketer has a scientific approach and relies on data. And the best way to remove uncertainty and guts to all marketing or design decisions for websites, ads—anything online actually, is A/B Testing.

Split Testing

Why is it important to run experiments?

Even when you have great insights from data and user research, it is still difficult to predict how users will behave when you roll out changes. Testing takes the guesswork out of the process and allows you to be confident that you are making the right decisions.

Having a testing strategy at the heart of a conversion optimization program will increase the number of people converting and improve your key metrics. Basically, you can make your marketing spend work better for you. And instead of investing in more marketing, you can capitalize on the customers you already have by improving their online customer journey.

By basing your strategy on data, you’ll be agile but most importantly you’ll have concrete feedback on what works and what doesn’t. You’ll be better able to make business decisions and invest time and money in what your visitors actually want.

What is A/B testing (split-testing)?

A/B Testing is also known as split testing, which can be either exactly the same thing as A/B testing OR mean split URL testing. For a classic A/B Test, the 2 variations are on the same URL, whereas split URL testing where your changed variation is on a different URL (your visitor doesn’t see the difference of course).

A/B Testing Experiments

By split-testing, you determine the impact of content, design, and functionality changes to your website. By creating multiple versions of a web page and collecting data & statistics for a control group (usually A) and at least one variation (B), we can learn about how your ideas impact user behavior and ultimately your key goals and objectives.

But A/B testing needs work to get into and more work to practice. You’ll have to create a process, put a framework in place, learn a bit about statistics, set up and learn a new tool, make sure you’re actually getting accurate results. The results, however, can be fantastic.

We use Google Optimize 360 for split-testing

Google Optimize is an A/B testing and personalization product, which is a perfect solution for small and medium-sized businesses like yours that need powerful testing. Best of all, it is built right on top of Google Analytics, so you can start using your Analytics data to conduct A/B tests and improve conversions on your site right away.

  • There's a free version
  • Easy setup and familiar UI
  • Data sharing and integration across Google stack
  • Advanced audience targeting
  • Advanced reporting
  • Apply learnings faster
  • Visual editor, no need to touch code
  • Enterprise scalability
  • Additional experiment objectives
  • Complex multivariate tests
  • Serve dynamic, personalized content

Personalize your customer's experience

Google Optimize 360 allows you to create segmented customer experiences and then test those experiences to increase engagement, interactions, and conversion goals.

Whether it’s a custom-tailored message at checkout or a completely revamped homepage, Optimize shows you which variants engage and delight your customers and gives you the solutions you need to deliver them.

This level of personalization is made possible through Optimize 360’s open system and tight integration with Google Analytics 360. Another key differentiator is the superior user privacy, which enables precise remarketing without putting users’ personal data at risk.

We can also help you create and leverage existing customer segments in Google Analytics 360 for accurate targeting and delivery of personalized customer experiences for each of your target segments.

Implementing the winning experiments

Once an A/B or multivariate test experiment is completed, we can then start to carry out a post-test analysis to evaluate the results, draw conclusions, and decide on what action we need to take next. It is crucial that we only conclude experiments when we have sufficient data to draw valid conclusions. For a website test, this includes a minimum number of conversions, a minimum number of business cycles, and of course, statistical significance for our test goals.

A custom solution for your testing needs

Every business requires a tailored consulting approach to address specific challenges, opportunities, and goals. ReverseLlama uses a data-driven testing process to meet your unique needs and get the most out of your experiments.

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