Website success boils down to three pillars: website traffic, average order value, and conversion rates. Conversion rates are defined as the ratio of website visitors to conversions. Conversions usually manifest in the form of transactions or leads. Other conversions include:
High conversion rates can mean a single visitor performing more conversions or a larger percentage of website traffic that converts.
We can help you get more conversions to your site; plain and simple. We can turn anonymous web traffic into strong, life-long customers. Our conversion rate optimization methods combine science with art.
Science. We analyze hundreds of thousands of rows of data and compare them against industry benchmarks. We leverage this data to help us find weak points on the website and areas of improvement. Utilizing our business intelligence software and data modeling, we identify web pages that cause visitors to lose interest or create confusion. These bottlenecks are starting points for optimization.
Art. Knowing the “what” is half the battle. After discovering points of friction and bottlenecks, we determine how and where to make changes to the site. We design and develop effective solutions that increase conversions and conversion rates.
We have three main phases: Analysis, Optimization, and Validation
During the analysis phase, we mull over Google Analytics, Adobe SiteCatalyst, and other data sources. We cleanse the data to ensure good decisions are made based on reliable data. We are able to see red flags like high bounce rates, low average times on site, and low pages per session. We look for where the leaks in the conversion funnel are.
After we’ve thoroughly analyzed your site and have given you a report of our findings, we discuss goals that need to be met, value propositions, and additional calls to action to implement. From here we carefully measure and record our changes, A/B test, and make adjustments based on data with proven statistical significance.
Common experiments we perform during an A/B or multivariate test include:
All our hypotheses are tested using statistical significance. We do not rely on small sample sizes or intuition. Not all experiments improve conversion rates in a significant way. We analyze the data and once we can make a conclusion, we report on whether or not the changes were positive. From there we give you a detailed report of our findings, our hypothesis on why the experiment increased or decreased conversion rates, and then we make recommendations on the next A/B or multivariate test.