Introducing a New Baymard Research Focus: Quantitative Insights

Today, we’re announcing that we’ll be devoting more of our research resources towards generating and analyzing quantitative data by providing our customers with a new research product: Quantitative Insights.

With Quantitative Insights, Baymard is providing a fuller picture of ecommerce user behavior.

Quantitative Insights supplement and support the findings produced through our large-scale UX testing by presenting user habits and preferences across a variety of ecommerce UX topics.

In addition, Quantitative Insights may be more approachable for certain audiences — for example, product or sales managers — who may be less interested in the level of detail included in our UX Guidelines.

What Are Quantitative Insights?

Quantitative Insights are visual, survey-backed data that highlight user habits and preferences across key areas of the ecommerce user experience, from general online shopping preferences to loyalty program expectations.

Each insight is derived from large-scale usability surveys and quantitative research projects, providing a fast, scannable way to understand critical user behaviors.

The insights may be standalone snapshots of data — for example, the reasons why users abandon checkouts, the most used customer account features in ecommerce, etc.

Or the insights may be providing information on a series of related quantitative research questions centered on a particular theme — for example, our Loyalty theme findings rely heavily on quantitative data.

We also released 2 industry-specific Quantitative Insights studies of the Electronics & Office and Jewelry & Watches industries.

Each of these studies provides multiple Quantitative Insights that address the most crucial questions their industry faces when it comes to the end user experience.

How Should I Use Quantitative Insights?

With Quantitative Insights, our goal is to help you with the following 3 aspects of ecommerce UX:

1. Strengthen stakeholder alignment. Over the years we’ve received feedback from our customers that Baymard guidelines can be difficult for key stakeholders to unpack. With quantitative insights, you’ll have a new way to back your UX recommendations with trusted UX insights that can help drive objective decision-making.

2. Design smarter A/B tests. Quantitative insights provide clear and actionable data and analysis, which will help guide meaningful test hypotheses and offer a way to faster, more efficient A/B test design.

3. Discover new insights that match your UX challenges. By providing large-scale survey data on common ecommerce UX questions, quantitative insights will speak directly to your UX focus, from comparing design or product directions to uncovering new improvement opportunities.

Additionally, many Quantitative Insights include an “Actionable Insights” section, which goes beyond simply reporting data.

Instead, “Actionable Insights” will help to get you started by providing guidance on how to apply the results in your own work — for example, that users considering loyalty programs need one key perk to be encouraged to sign up.

How Are Quantitative Insights Different from Guidelines?

Quantitative insights differ from qualitative insights not only in how they’re produced (in general, via large-scale surveys) but also in how they’re best applied.

Our quantitative insights offer snapshots of users’ perspective on various aspects of the ecommerce user experience.

As such, they’re less prescriptive than our guidelines based on qualitative observations of user behavior.

Rather, quantitative insights are more directional and offer a broader, high-level view of aspects of the user experience.

For example, a typical Baymard guideline will walk you through the issues experienced by users in testing, solutions observed in testing or identified elsewhere, and provide a “checklist” of design changes necessary to fix the observed issue.

On the other hand, a Quantitative Insight will present responses to a specific UX question — for example, “How do users save products they aren’t ready to purchase?” — without requiring there be a UX issue or solution that needs to be addressed.

In short, Quantitative Insights are focused on the “Why users do or think what they do”, compared to UX Guidelines, which are focused on the “How to design [X] specific element or feature to best support users’ needs”.

How Are Quantitative Insights Generated?

Quantitative Insights are generated by large-scale surveys of ecommerce users.

While the approach differs depending on the research topic, in general our respondents are regular ecommerce shoppers with experience shopping in a particular ecommerce product vertical (if the study is industry centered).

To take one example, the quantitative portion of our Loyalty study consisted of an online survey of 2,003 US adults, quota‑balanced to US Census benchmarks.

Respondents were required to shop online at least once a month and confirm membership in at least one loyalty program.

Individuals who were unsure of their membership status or who actively avoided such programs were screened out.

For other studies, we adjust our respondent-selection criteria to match the desired respondent characteristics, but the fundamental process remains the same, ensuring we generate high-quality responses from the most relevant ecommerce users.

Expanding Ecommerce UX Research through Quantitative Insights

At Baymard, the bulk of our research has always been 1-1 qualitative user testing: observing (in person or remotely) as participants navigate and use ecommerce sites.

The qualitative data we’ve gathered has been the foundation on which our 700+ guidelines have been written.

Today, with Quantitative Insights, we’re providing you with additional, complementary UX research data that offers even more guidance on how to better design the ecommerce user experience.

Getting access: all our Quantitative Insights are available today within Baymard. (If you already have access through an account, open the Quantitative Insights page).