Q4 Revenue Drivers: Conversion Optimization Strategies for Checkout (Part 1)
Published: August 29, 2017
Author: Kelly Whelan
Part 1: With Q4 just around the corner, how can online retailers maximize their efforts? They could just pump up spend, but without optimization they’re likely to see an expensive lag between increased spend and increased revenue.
This blog is the beginning of a two-part series that will summarize our “Q4 Revenue Drivers: Conversion Optimization Strategies for Checkout” white paper and cover tips for optimizing the checkout process. In this first post, we’ll cover the top 3 types of quantitative research used to determine what conversion blockers exist in your checkout process. For an in-depth look into each, you can download the full white paper here to get further insight and examples.
Quantitative analysis helps you figure out what users are doing. Different techniques allow you to isolate behavioral trends and find the highest-value pages and opportunities for focused optimization.
1. Analytics: The first type is analytics data, which you’ll use to gain a better understanding of user behavior at each stage of the process. By isolating the highest abandonment rate, you can focus your optimization efforts on fixing the key issues that are blocking users from converting. This takes the form of:
- Funnel abandonment: Isolating the pages and events that cause users to abandon before converting.
A high-level view of actions taken throughout the purchase process.
A more granular view of abandonment from cart to checkout.
- User pathing data: Discovering onsite behavioral trends. Finding out how users move through your site and what they engage with.
2. DMPs: A Data Management Platform can help you track abandonment rates across specific 3rd-party attributes, such as gender, income bracket, geo-location, etc. This helps you get a lot more granular about what actions specific customer segments are taking. Demographic breakdowns can change as you move down the funnel; using a DMP will help determine this.
3. Form Analytics: Analyzing form behavior is useful to determine whether specific fields are necessary, friction exists in the experience, or layout is causing users to abandon. What works best for your users? Single-page checkout? Accordion style? Form analytics can help you determine where the drop off is so you can test which method has the highest rate of conversion. As a quick rule of thumb: For high abandonment OR low motivation, reducing friction is key.
Once you’ve built a foundation of quantitative findings to understand what your users are doing, you’ll want to begin digging into why. This brings us to qualitative research, which we’ll cover in part 2 of this series.
For an in-depth look at these three methods of qualitative research , check out our full white paper, “Q4 Revenue Drivers: Conversion Optimization Strategies for Checkout”, or contact our CRO team to learn how we can help you get started.