CRO research and analysis. How do we find out WHERE and WHY you’re losing money?

The key to every successful optimization is good research and analysis, which lets us identify conversion problems and growth opportunities.

Without research and a diagnosis – without naming the problem – that problem is hard to beat. It’s like a doctor treating you before diagnosing the illness. You wouldn’t want to be treated that way, would you?

Your website (and its conversion) doesn’t handle treatment without a diagnosis any better. So before we start changing (treating) your website, we run research – quantitative and qualitative.

From that research we learn:

• which parts of the site have the most conversion problems,
• where the biggest opportunities to lift conversion are,
• what pushes users to convert and what holds them back
• what information customers are missing while they’re on the site,
• what fears and doubts they have before buying (or completing another conversion),
• what needs adding to the site to increase clarity, cut friction and distraction, improve value communication and raise credibility.

What research do we run?

We pick the research methods individually for each store, depending on the specifics of the business, the current data, and the problems and opportunities we’ve already identified.

We focus on work that answers the most important questions at a given moment (“why are so many users not adding a product to the cart?”, for instance). Put differently, we run the research that will bring the most value to your business at that moment.

Business interview

At the very start of the engagement we run business workshops to better understand your business and your customers – their motivations, problems, needs and decision-making factors. We gather all of that information in a separate file, which later helps us empathize with your customers and optimize the site.

Google Analytics analysis (or another quantitative analysis tool)

We get familiar with the key data. We look at how users behave on different pages, devices and browsers. We identify the landing pages with the most traffic and check their bounce rate. We determine where on the purchase path a lot of users drop out and where you may be losing the most money. And much, much more.

GA analysis gives us context for further research and helps us plan our work. For instance: if only 40% of users move from the cart to the first checkout step, there’s probably a problem here and it’s worth analyzing that page more closely, because you may be losing a lot of money. We then look at further reports in Google Analytics. Analysis using GA is above all the art of asking good questions and looking for the answers.

Sample reports we analyze in GA:

• Checkout Funnel Report
• Goal Flow Report
• Bounce and exit rate on the highest-traffic pages
• Bounce and exit rate on the most important page types
• Segment analysis
• Content Grouping – bounce rate, exit rate, CR
• Navigation summary – the most important pages
• Site search analysis
• Device analysis – CR, bounce rate, exit rate
• Product category analysis
• and much more

Sample observations and conclusions we can draw from Google Analytics analysis:

Example 1.

Observation: Only 40% of users move from the cart to the first checkout step

Conclusion: There may be conversion killers in the cart, and it’s worth analyzing that page more closely. In most cases the optimal result is 60-70% of users moving from the cart to the first checkout step. If your store’s figure is 40%, there’s clearly room for growth here. A closer analysis of the cart, followed by optimizing it, should be an absolute priority.

Example 2.

Observation: Conversion among users on Opera is significantly lower than among users on other browsers – Internet Explorer or Chrome, say

Conclusion: That could mean your store has technical problems on Opera, and it’s worth looking into it more closely. Perhaps your store is very slow in Opera, or the checkout isn’t working as it should. It’s worth looking at further Google Analytics reports at this point to answer those questions.

Example 3.

Observation: the Goal Flow report shows a great many people going back from checkout to the cart.

Conclusion: Something is clearly wrong. Maybe visitors have questions or doubts on the checkout page and that’s why they go back to the cart. Maybe they want to verify their order because the checkout page has no order summary. There could be many reasons. Google Analytics may not give us a definitive answer for why this is happening, but this report clearly shows us there’s a serious problem with the checkout and that you’re losing a lot of money there. So we know it’s worth looking at this more closely first and eliminating the conversion killers in the checkout as fast as possible.

Example 4.

Observation: One of the most visited pages (40,000 users a month, say) has a bounce rate as high as 90% (90% of users who land on this page leave and abandon further browsing).

Conclusion: If one of your highest-traffic pages has a bounce rate that high, it’s definitely worth a closer look. In a situation like that it’s worth building a few extra Google Analytics reports to check whether one traffic source or several are behind the high bounce rate. Maybe you’re paying a lot of money to drive traffic to that page and should pause that spending. Maybe the page is exceptionally slow. Or maybe it displays badly on mobile.

Google Analytics analysis is about asking the right questions and learning more. What matters, though, is that you probably won’t find every answer in Google Analytics alone. Google Analytics can give you a clue, but you may need other research methods to really find out why people are abandoning that page en masse.

Expert review

A purchase path analysis involves one of our specialists going through the store’s most important pages and detecting the potential problems that may be lowering conversion.

What matters here is that this analysis requires a structured approach. At Digispot we use our own methodology for analyzing online stores, built on the 7K Model.

Here are the factors we take into account when analyzing a store’s purchase path:

1. Clarity
2. Value communication
3. Friction
4. Distractors
5. Fit
6. Credibility
7. Motivators (psychology)

Heatmap analysis

We observe how users behave – what they click, what they don’t, how far they scroll and so on. Heatmap analysis lets us see which page elements engage users the most and which get ignored.

That helps us understand how to improve the page’s layout and design to make it more intuitive and user-friendly.

Form analysis

Using a specialized analytics tool, we find out how users flow between the form’s fields, how much time they spend on each field, and where they most often abandon the form.

Session recording analysis

We sit down to this with a specific goal (confirming a potential problem identified in other research, say). If you don’t know what you’re looking for while watching recordings, you’ll probably waste a lot of time.

A conversation with customer support and/or chat message analysis

The people in customer support are a treasure trove of knowledge. They talk to customers every day and hear what doesn’t work on our site. So they have a wealth of information about the problems visitors run into.

We write down every recurring worry, doubt and uncertainty. We look at the questions users ask. If we start answering those questions directly on the site (as far as that’s possible), we’ll certainly lift the store’s conversion and reduce the load on the customer support team at the same time.

In one store we came across a situation where several customers a day reported that they couldn’t find the place on the site to enter a discount code. The problem was common enough that customer support had actually prepared instructions on how to find that field… Yet nobody ever decided that instead of forcing customers to write emails, they could simply make the field more visible on the site. Over what seems like a trifle, the store was losing a pile of money. Not everyone who ran into trouble entering a code got in touch with support, after all. A large share of potential buyers simply abandoned the purchase.

Customer surveys

In some cases it’s worth running a survey. Surveys tell us what customers’ motivations, problems and frustrations are.

We ask specific, open questions (for instance: “Think back to the last time you… Did you run into any problems?”, “If you could instantly change or add 3 things to our site, what would they be?)

User Testing

User testing lets us observe how real users work with a website. Think of it as “Hotjar session recordings on steroids”.

It differs from plain session recordings in that we decide what tasks the tester carries out on the site and we see their face while they do it (which lets us spot, for instance, where and when a grimace appears). During the session, users think out loud about what they’re doing, thinking and not understanding, and we can ask them about their experience, feelings and problems, which gives us a deeper insight into their needs and how they use the site.

With user testing we can learn:

• how users actually navigate the site,
• how they search for information,
• what their first impression is when they land on the site,
• where they get lost,
• what they like and don’t like,
• whether there are any unexpected ways of using the site,
• what feelings specific copy and headlines trigger,
• what they need to hear or read to convert.

What kinds of user testing do we run on websites? Here are a few:

• a usability test of the whole conversion path or a specific landing page
• a test of the marketing message and key copy — you can learn whether the site’s overall messaging (or specific content) is clear and appealing
• preference testing – in a preference test, users compare different versions of a page, feature, interface or other element and tell you which variant they prefer and why
• 5-second tests – users describe their first impressions after visiting a page and what they remember from it; you learn whether the page clearly communicates what can be done on it
• tree testing – lets you test how users navigate a category tree and how easily they find information on the site.

We recruit testers ourselves (if your target audience is business owners in a specific industry, say, we look for them in topical Facebook or LinkedIn groups) or we use specialized platforms that help with user recruitment.

User testing (a usability study of the purchase path), step by step:

1. We gather hypotheses and set a goal. Before we even write the tasks for testers, we specify what we want to study and learn. User testing aims to:
   1. give us a better understanding of user behavior on the site
   2. confirm or reject hypotheses we formed during earlier research
   3. uncover new UX and conversion problems that hadn’t been noticed before.
2. We recruit 5-10 userswho represent the target audience (most usability tests are run with a group of 5-10 users; usually 5 people is enough to identify around 80% of the most important problems).
3. We prepare a script for the tests, with tasks and questions for users.
4. We run the tests. During the tests we observe how participants use the site. We pay attention to their reactions, facial expressions, emotions and any problems they run into. Besides observing their behavior, we ask participants specific questions to find out what’s giving them trouble.
5. We analyze the results. We look for patterns and recurring problems among users. That lets us identify the areas to improve.
6. We ship changes or run further validation. Based on the information gathered, we run further validation (an A/B test, say) or ship changes right away.

Other research methods

• An exit intent poll for visitors
• A thank-you page poll
• A feedback button
• A thank-you page poll
• Review mining
• Card sorting
• Literature and A/B test databases
• Desk research – analyzing existing data (a market report, for instance)

Next steps

• We catalog every observation, finding and growth opportunity from the research in Notion and prioritize them.
• We form hypotheses (“Change X will contribute to Y, which will grow Z”). Through research we find out where and why you may be losing money, and we build ideas for how to raise sales in your business. In the next steps we check whether those ideas are good and have a positive effect on your conversion.
• We verify the hypotheses, using A/B tests, say – we build wireframes, ship the test and analyze the results. You get strong evidence on whether the designed changes lift conversion or not.
• We ship the winning changes.
• We repeat the process – continuously improving your website.