As web marketers seek new ways to boost conversion rates and improve their mobile visitors' site experience, interest in mobile content optimization is on a feverish rise. But those unfamiliar with the tools and techniques are often unclear about where to start, or how to ensure success. In this article, we'll discuss:

A clear explanation of how to utilize , and how it differs from another common type of testing: A/B testing.

"How mobile multivariate testing and analytics provide a foundation for continuous improvement of your mobile web analytics and marketing initiatives.

"An overview of five common mistakes to avoid when planning and running mobile multivariate tests.

What is Mobile Multivariate Testing?

Common methods for running controlled experiments on mobile web pages range from simple A/B testing to sophisticated multivariate testing, also known as multivariable testing. In A/B testing, one or more new versions of a page or single site element compete against an existing control version. For example, two versions of a headline might compete against an existing headline. Mobile multivariate testing, on the other hand, is like running many A/B tests concurrently, where there are multiple elements being tested at the same time. For example, two alternate product images, plus two alternate headlines, plus two alternate product copy text, for a total of 27 possible combinations (including the original control versions). What's important to understand about mobile multivariate testing is that it not only shows you which combination of elements generate more sales or pull more leads, but it reveals which individual elements influence visitor behavioral vs. those that do not. For example, did variations in product image influence visitor behavior more, less, or the same as the copy? Understanding how each site element causes visitors to interact with your mobile site is the essence of a test-learn-repeat process that marketers can use to synthesize new ideas and continually improve their mobile site's ability to achieve and exceed their marketing goals.

Mobile Multivariate Testing as a Process for Continuous Improvement

The process of mobile reveals not only what works and should be implemented, but also what doesn't work and should be avoided. Every new idea, whether content, functionality or campaign related, should be put to the test to determine if it helps or hurts the visitor experience. While some new ideas lift conversions, others fail - sometimes significantly. But even with these failures, there is definable knowledge gained over what to avoid the next time. The ability to test a new idea and look before you leap is an unmistakable advantage that breaks the constraints on mobile marketing innovation. Only once a solid testing capability is in place, and the impact of any site change able to be quantified, can mobile marketers truly optimize their mobile site's effectiveness.

What are Common Errors to Avoid When Optimizing Mobile Content?

There are five types of mistakes that are easy to make when running mobile multivariate tests:

1.Improper factoring caused by poor or no isolation of individual test changes; for example, changing a headlines text, font color, and font size, all at the same time as a mobile A/B test instead of a multivariate test. Why is this problematic? Because its difficult or impossible to isolate the impact of each individual change i.e., was it the font color and/or the text that caused the visitor to behave differently?

2.Running a test too short/long. Stopping a mobile multivariate test early because you think you have a winner increases the risk for statistically invalid data, and may increase time bias from events and/or conversion cycles. Running a test too long increases the risk of wasting time waiting for marginal results and consumes test sample that could be applied towards another test.

3.Tracking or analyzing wrong Key Performance Indicators (KPI's). For example, measuring a KPI that is too far upstream (in a conversion funnel) from the ultimate goal, or measuring only one KPI when there are multiple indicators and/or goals that matter. There's also the risk that a measured KPI improves, but at the expense of another (untracked) KPI, or that the measured KPI is actually a bad predictor of the ultimate goal.

4.Not using or visitor segmentation. This means optimizing your mobile site or campaign for anyone and everyone by not targeting tests to include good visitors (and exclude bad visitors) and not segmenting the results. Why is this problematic? Because not all visitors are the same theyre at different stages of the buying/customer cycle, using different mobile devices, and some may be mistakenly in the wrong site altogether.

5.Not taking action on results! This could range from not making the winning changes to your mobile site or not taking what youve learned and running another test (iterative test-learn-repeat). The risk here is that there is no momentum gained, no ongoing strategy applied, no realization of test results, and worst of all underwhelming ROI.

How can Multivariate Testing Optimize my Mobile Web Marketing?

Multivariate testing can yield some spectacular results in enhancing mobile marketing effectiveness. For example, we worked with a well known online auction house to perform a series of multivariate test campaigns to understand which elements were most influential in bidding conversion. The team tested variations in elements such as mobile page layout and messaging, individual item landing pages, and calls-to-action. They made test variations in critical elements on their site, such as creative elements, event promotions, image sizes, copy, navigation and page layouts, without the need to make a single change to the underlying catalog auction system. These changes resulted in:

"429% increase in bidding activity

"83% increase in catalog browsing activity

"166% increase in individual item views

"590% increase in opt-in registrations

If you are looking optimize your mobile marketing, multivariate testing can and should be part of your arsenal of analytics and optimization tools.