For e-commerce businesses, increasing conversion rates is the biggest key to increasing revenue. And the best way to boost conversion rates is to perform research on your customers’ online behaviour and how they navigate your website.

There are two broad categories of customer research: quantitative and qualitative. Each kind of research has its place so it’s important to understand the differences between the two.

Multiple choice vs. open-ended questions

Quantitative research is gathered mainly from asking customers multiple choice or ranking questions. For example, you might ask customers to rate their experience on your site with 1 being Excellent and 5 being Poor. In contrast, qualitative research is gathered by asking customers a series of open-ended questions they must write out the answers to.

The biggest benefit of quantitative research is that it is faster and cheaper to gather responses and analyse the data. Customers are also more likely to respond to quantitative questions, since answering them takes less time, so you’ll have more data to work with.

However, there are limitations to the value of quantitative research. The biggest drawback is that it can be easy for human bias to creep into how the questions and answers are presented. By only giving customers a narrow choice of responses, you’re just validating what they already believe to be true.

Qualitative research generates better data

Qualitative research avoids this problem by allowing customers to answer questions however they want and tell you what’s really important to them. It is the best way to gather true information and learn new things about your customers’ online behaviour that can help you increase conversion rates. As a result, the data generated by qualitative research tends to be more valuable and insightful than data generated by quantitative research.

Not surprisingly, customer response rates are usually lower with qualitative research because it takes longer and requires more effort for customers to answer the questions. This tends to make qualitative research more expensive and time-consuming than quantitative research. It also takes longer and costs more to analyse the results of qualitative research. But as they say, you usually get what you pay for.

The good news is that advancements in machine learning tools are making it easier and less expensive to gather and analyse the results of qualitative research. With machine learning, you can analyse a thousand qualitative survey responses in a few hours instead of a few days.

How to perform qualitative research

Most qualitative research studies are performed by asking customers a series of up to 10 or so open-ended questions after they have made a purchase. For example:

• How was your shopping experience on our website?

• What did you most enjoy about shopping on our website?

• Did anything almost stop you from completing your purchase? If so, please describe.

• Why did you purchase from our site instead of one of our competitors?

You can take qualitative research further by bringing customers onsite to ask them questions in a focus group setting and observe their online behaviour in person. For example, if they place an item in their shopping cart but then abandon it, you can ask them why and what would it take for them to complete their purchase.

Qualitative research in action

Here are a few examples of how we helped clients solve problems and boost conversion rates by performing qualitative research:

• An online merchandise retailer was experiencing a high volume of shopping cart abandonment so we asked customers a series of open-ended questions to find out why. Our qualitative research determined that many customers were unhappy with delivery pricing. When the client lowered the delivery price, the conversion rate increased by 94%, which led to a revenue increase of £1 million pounds per year.

• An online health and beauty retailer was also experiencing a high level of shopping cart abandonment. They couldn’t understand why. We initiated a pop to ask users a question when they showed behaviour that indicated they were hesitating or about to leave, we got them to tell us what was happening. Users explained that the brand was giving away free samples at checkout but not the specific samples the customers wanted. As a result users were actually postponing purchases and shopping elsewhere to find the samples they wanted.

This was a new insight to the cosmetics brand and highlighted the negative effect that can come from the power of free. After this discovery, they increased the priority of ensuring they have adequate stock levels of samples for their most popular products.

• An online site for buying and selling cars was losing customers at a key stage in the selling journey. There were no obvious UX issues on the page to explain the drop. We used an open text survey to gather feedback from the users who exited at that stage to understand what was happening. We uncovered that when the site gave them an estimated value for their vehicle, customers felt it was too low. We call this the endowment effect, when we value something more because it belongs to us.

Based on the insight, we worked with the client to increase the estimated value which was quoted. Aligning with the users expectations result in an uplift of over 9% in customers who completed their vehicle listing.

Determine your goals and budget

A number of different factors will dictate whether quantitative or qualitative research is appropriate for your situation, including your goals and budget. Give this some careful thought before embarking on your next customer research project.

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