One of our customers - a roaster and distributor of specialty segment coffee - found himself in a similar situation. Limiting the operation of service premises, cafes and restaurants forced them to cancel their orders literally day by day, cutting of our customer’s crucial sales segment - a wholesale B2B distribution. The brand pop-up stores and showrooms were also closed - whole offline sales stopped.
Therefore, focusing on individual customer who purchases online, was a natural decision. However, a former website was addressed to B2B customers and concentrated on the objectives relating to the general presentation of the brand and it’s offer - that’s why some little improvements and modifications had to be carried out.
To discover elements, which need to be changed quickly, we implemented the HotJar analytical script on the platform, so that we could record behaviour of users while using the site. This, in turn allowed us to understand how customers interact with the website and to identify the most important directions for UI/UX remodelling.
Product analytics is a form of testing digital products - such as websites, e-commerce sites, applications and online platforms - and provides us deep insights into users behaviour. It allows to capture information and analyze data, which can help us to optimize the website in terms of UI/UX, marketing, sales and customer service. It also tells about users behaviors and experiences - without disturbing the flow and involving them in UX researches and tests.
Users behaviour is recorded in the background - an implemented script (Google Analytics, HotJar, Cux.io) collects data, such as cursor movements, opened pages, clicked areas, and visualizes them in a form of:
click maps: a map of user’s clicks
scroll maps: a visual of page scrolling, which illustrates how far the website visitor reached
recordings of individual visits - a record of a specific user's behaviour during his one visit on selected pages.
Product analytics can help us, if we want to understand how users interact with the website and to gain a data-based answer to questions such as:
how users explore areas of main page, product cards, catalogue and forms?
what attracts their attention and what they skip?
which page elements are challenging for them?
which content is more appealing?
why they buy less than we expected?
how to improve UI, specific functionality or user experience?
Answers to these questions have a great impact on business in the context of conversion optimization - but it’s role proves to be even more valuable when something unexpected happens.
The first observation concerned users behaviour in the context of the website and e-commerce structure. So far, customers entering the platform hit the general information site concerning the brand, offer and trainings - to enter the online store the user had to move on to another tab in main menu, which was redirecting him to e-commerce embedded on the subdomain.
Click maps have shown that currently over 85% of visitors go straight to the store. Therefore, the current solution was extending the time needed to finalize the transaction.
Scroll maps analysis allowed us to identify previously neglected spaces to highlight promotional offers and the newsletter, which in this particular situation gained an additional potential in building retail funnels.
And yet, curiously, one of the most interesting conclusions concerned customer segmentation - analysis of users behaviour within product’s category and product’s card in the context of whole strategy and historical data allowed us to distinguish an additional user group. The previous strategy was focused on conscious coffee-drinkers - perfectly oriented in the offer and technical details such as roasting parameters and characteristics of specific species and mixes. Indeed - you could see them in analytics - they knew exactly what they were coming for - their first action was moving to the search engine or a specific product to familiarize themselves with the information card and finalize the purchase.
However, there was also another, equally large group: they were navigating in a jumping, even a chaotic model, entering and leaving specific product pages. By observing their activity time, cursor movements, scrollings and clicks, we could conclude that visitors were analyzing information in product cards hesitantly, wandering the cursor over products descriptions, comparing specific products - probably trying to make the best choice. Often, such session was not ending with the purchase, but with closing all tabs. We named this group "aspiring coffee-drinkers” - already know the difference between high-quality specialty coffee and coffee from the market, appreciating quality; however, knowing not enough to make a conscious choice, they just felt lost.
It’s a very important conclusion, which provides a recommendation for better care of this customer segment: creating dedicated content, refining descriptions in more friendly way, and using slightly different products graphics.
Recommendations above allowed to implement strategic modifications, both in UI/UX and product communication, making the store more friendly and useful for customers, and as a result - improving the conversion.