How to analyse the shopping behaviour on your website: 5 easy steps

Sometimes, ecommerce business owners give shopping behaviour analysis a miss, examining only separate indicators such as conversion rate or bounce rate. However, being aware of how your customers transfer between each stage of your purchase funnel may help you provide prudent solutions, improve user experience, and increase website performance at no additional cost.

We should admit that shopping behaviour analysis is not about modelling a loyal customer behavioural portrait. Vice versa, this approach allows you to identify the hurdles users who rarely come to your website meet with, and reasons why they leave purchasing nothing. The main objective of consumer shopping behaviour analysis is to decrease the ratio of the number of total sessions and sessions with transactions by improving the website performance at each stage of the purchase funnel.

Note: These insights are useful for any-scale ecommerce business, but for websites with over 10,000 transactions per month this is a must. If you do not have enough knowledge of how Google Analytics works, this would be a perfect idea to involve experts who do or contact our Promodo analytics specialists with a vast experience in examining such statistics.

The typical way to analyse your customer behaviour is to use your Google Analytics account. However, some data isn’t available here, and you will need to benefit from other services.

Step 1. Check the percentage of users who win through your purchasing funnel

Selecting Conversions > E-commerce > Shopping Behaviour in your Google Analytics account, you will find the statistics over how many users move through the whole consumer path of your purchasing funnel. There are five graphs with numbers of visitors who have completed a specific action. All these are obviously arranged in descending order:

  • All Sessions
  • Sessions with product views
  • Sessions with Add to Basket
  • Sessions with Check-Out
  • Sessions with Transactions

The average percentage of sessions with transactions in the UK ecommerce market is 4.31%. In case your conversion rate is under 1% — you must analyse your customer behaviour deeply.

For instance, you noticed a significant number of users who had viewed your product page. 70% of these users added items to their shopping carts, but only 0.5% completed a purchase. In this case, you need to analyse the actions which are required during checkouts, such as registration, phone number confirmation, or billing address. According to the recent Baymard report, these are the common reasons why a client abandons a site during checkout.

reasons for abandonments during checkout 2018

You can check your assumption in the Checkout behaviour tab in the Google analytics account to define what page to put under a microscope.  

Checkout behaviour analysis

Step 2. Examine each marketing channel according to your funnel segment

After reviewing the overall situation, you can create additional ecommerce segments to examine the consumer shopping behaviour within each. Segmentation will help you make selective research, reveal pain points and track how the situation will change after A/B tests.

How to do this? In the same tab Conversions > Ecommerce > Shopping behavior click the graph and create a cognominal segment you want to analyse. For example, it may be sessions with basket abandonment.

segmentation shopping behaviour

Now besides a number of abandonments, you can check out such data as:

  • In what browser and from what device these users visited your website;
  • What ad campaign they came from;
  • Their location;
  • Source & medium:
  • Were these users logged in;
  • What keyword they used to find your website.

The created segment appears over the entire analytics account, making it possible to check various insights within a segment. Thus, in the “Channel Overview”, you can track the digital marketing channels, that led these users or examine the full audience report.

Please remember, this feature is available with each stage of the purchase funnel, and you can analyse buyer sessions with no-basket addition, check-out abandonment and sessions with transactions simultaneously.

Step 3. Explore landing and exit pages within a specific segment

Based on the foregoing ecommerce segments you created according to your weak areas, examine which pages on your website are landing and which are exit within each group of sessions. This step will help you understand the exact pages which require improvements and more detailed analysis.

In the following example, we can see that 44% of sessions are interrupted on the payment and info pages, which reveals possible problems with payment methods. Probably, that page also contains a link to the info page where terms and conditions are insufficient and do not meet the consumer expectations.

exit pages google analytics

4. Scan the problem pages with a heatmap

Heatmap for ecommerce is a fantastic extra solution for tracking shopping behaviour on specific webpages. Entirely, there are four types of heatmap:

    • Hover map or mouse movement tracking;
    • Click maps;
    • Attention heatmaps (demonstrates how long a user was on your website page and on what blocks they spend the most time);
    • Scroll map (reveal how far your users scrolled down a specific page)

The report looks like your website page with highlighted with different coloured areas where orange and red are the most active among visitors. Unfortunately, Google Analytics doesn’t have this data, however, you can use other free popular heatmap tools for ecommerce, such as Crazy Egg, Hotjar, or Smartlook.

heatmap online store

4. Check what users search for on your website

A more common question for businesses is how users browse Google. Instead, some visitors who liked your website design/ attractive price / convenient delivery terms/ useful content and so on try to find the product they need directly on your website.

You may check this data within a specific segment or view general statistics. Site search within consumer shopping behaviour analysis will help you understand the needs of your audience, improve assortment and perhaps discover a new focus. And maybe it will help you set up a successful remarketing campaign targeted on users who searched for a popular specific product in your online store.

5. Inspect the sequence of interactions and time lag

To assemble the whole picture of online shopping behaviour, especially if your digital marketing strategy is omnichannel, check what and how many actions led users to a conversion, following Conversions > Multi-Channel Funnel > Top Conversion paths in the Google Analytics account.

In the Time Lag tab, you can find the information on how many days it took for a buyer from the first interaction with your website to the conversion. Being aware of this average number you can improve, as an example, you trigger emails or launch time-limited offers for users who came to your website three times a day.

And finally, check the number of interactions, needed to convert a visitor into a customer in the “Path Length” tab.

Final thoughts

Analysing online shopping behaviour on your ecommerce website is like Self-actualisation in Maslow’s hierarchy of needs, which is the top of the pyramid. To take care of this, you need to satisfy the basic needs first. However, insights on shopping behaviour allow us to stand back and look at our business through our customer’s eyes. And to solve local issues instead of just investing more and more budget each time to attract users via CPC ads. In the ecommerce world, all channels of attracting customers are good, that’s true. But the whole system needs to work in harmony and balance.

Analysing consumer shopping behaviour on your website, certainly, use funnel segmentation to examine each segment separately. This will allow you to identify problem areas and apply the most effective solutions to improve them. 

Do not hesitate to use heatmaps. First of all, because they look awesome, and secondly, they are extremely informative for customer experience enhancement.

The one way to check your assumption is to conduct A/B test. We wouldn’t recommend you change your problem pages completely. Try to make minor changes and track the results. 

Contact our Promodo digital marketing experts if you need any help with ecommerce analytics.

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