Learn how mobile can drive significant improvements in your B2B commerce KPIs.
Office Depot finds itself among the top 10 retailers in a landmark Baymard Institute study on e-commerce search; this after RealDecoy helps Office Depot migrate to a more modern e-commerce platform—in under 6 months.
After engaging with RealDecoy and pulling in site search conversions at two times the industry average, Lands’ End also then empowers its small merchandizing team to better manage a complex product catalog.
Receiving a 26% increase in customer searches after engaging with RealDecoy, America’s largest food industry redistributor also finds 80% of new business being influenced by searches for new products.
With improvements to user interaction, design and overall search experience for David’s Bridal, RealDecoy helps the world’s largest bridal retailer make significant increases in conversions.
At its most basic level, the testing phase is the easiest to understand: your customers experience two versions of the same page, and
you see which one performs better.
In classic A/B Testing, some visitors see version A, others see version B, and the difference in the conversion rates is assessed.
Here are the activities typically followed:
Design, test, gain insights. Then take these insights to develop new hypotheses, design, test, and gain more new insights. Conversion
rate optimization is an ongoing cycle toward continuous improvement.
Based on newly developed theories informed by data, next steps involve changes to the form and function of your website.
These steps typically involve the following activities:
With these activities completed, will your site offer a smooth and frictionless experience to customers? The only way to know is to
test—which is the next phase.
To understand customer intent, you need to know what your customers are looking for—and why. Understanding intent is like having a
flashlight pointing the way in the dark.
We start by understanding your business and determining your objectives. Then we collect data. From this data, we gain insights,
prioritize problem areas, and develop theories for testing.
Here’s an overview of our typical data collection activity: