Traditional web analytics allows analysing customer paths to a fairly limited extent – the extremely important aspects of emotions and experiences are completely ignored. Data collected by e.g. Google Analytics will not allow to distinguish the customers who happily view the website with the intention of making a final purchase in a brick and mortar store from users frustrated with uncomfortable navigation, struggling with an inaccurate search engine, who most likely not only won’t buy anything but will also share negative feedback with their friends. Similar limitations, due to the lack of knowledge about the context of visits, have the effect on analyses of conversion analysis and purchase funnels.
Path analysis tool offered by YourCX enables combining such data with information about the purposes, intentions, emotions and experiences of users. Such approach allows, for example, for advanced segmentation of history of visits by specific types of users (Detractors, Promoters or Passives, as specified in NPS question), by purposes of visits, the reasons for leaving the website or by specific technical problems. Such grouping enables optimization of conversion and verification of the hypotheses resulting from analyses of the remaining data. It also provides an useful knowledge about users’ behaviours, which allows e.g. for more effective management of advertising budget.
Segmentation of the paths, e.g. by purposes of visiting the website, and subsequent listing of those users who have not completed their goals, allows defining the critical points that lead to the loss of consumers searching for particular products, customer service support or information about the services. YourCX system records also information about duration of the entire visits and how long particular pages are viewed, allowing you to identify the pages where the users spend more than standard time. Longer viewing of a particular webpage does not necessarily mean anything wrong, that’s why the context is important and it can be read by segmenting the paths by positive, neutral and negative experiences.
Supplementing the context
Declarative data (survey results) and additional customer parameters, such as the type of user/subscriber account, allow for creating more accurate profiles of online users. Previous studies have shown that the logged-in users who know and enjoy the website like to spend a lot of time on it. They like visiting a lot of pages and adding a lot of products to their shopping cart, not necessarily with the intention of purchasing them immediately. Having a broader context related not only to the consumers’ declared emotions but also to their relationships with the brand, allows more useful conclusions to be drawn from the collected data.
An example conversion analysis in investigating the purchase abandonment process shows clearly what factors have the most significant impact on the final purchase decision:
|Reasons for abandonment of purchase process||Purchases|
|Declaration of willingness to continue shopping||28%|
|Too high product price||13%|
|Change of decision||11%|
|Finding another, better offer||8%|
|No option of collection from brick and mortar store||5%|
|Too high delivery cost||5%|
|Too long delivery time||4%|
|Willingness to make a purchase in a traditional store||2%|
Delivery terms appear to be decisive in many cases, although the lowest conversion rate level is noted for the users who wish to make a purchase at a traditional shop. Those data confirm the conclusions of other YourCX studies – offline purchase-oriented users (who drop off their carts because of that) are the group with the lowest conversion rate
Verification of hypotheses
Analyses of user paths and conversion funnels are useful for verifying the hypotheses. The mentioned reluctance to buy online that is characteristic to those users who visit an online store solely for the purpose of getting acquainted with the offer can be confirmed, for example, in studies aimed at acquiring consumer purchase preferences. Below is an example – online purchase declaration along with the % of purchases completed:
|Likelihood to purchase online in the future||Purchases|
|Users who declare that they:|
|will purchase for sure||8%|
|will likely purchase||6%|
|do not know whether they will purchase||3%|
|will definitely not purchase||3%|
|won’t likely purchase||0.8%|
|prefer purchasing in a traditional store||0.3%|
Tracking one or more paths
The path analysis tool allows both multi-track tracing (including all available filters and segmentation) and creating a single user history. Data can then be approached both „in bulk” (identification of abnormal behaviours and critical points) and individually (verification of hypotheses, creation of new study scenarios). Binding the YourCX data with individual parameters and customer segments allows even identification of particular users (e.g. through user IDs when they are logged-in).
„Dropping out” users
Users who “drop out” from a shopping funnel at one of its levels can be investigated by backward path analysis. Finding out the exact reasons for their conscious decision to not achieve the purpose of visiting a website is therefore both a matter of processing declarative data (left by the users in the survey questionnaires) and other technical data collected during a particular and other visits. The hypotheses resulting from analysis of aggregated quantitative and qualitative data are therefore easily verifiable. In addition to analysing paths forward and backward, it is also possible to display the paths between two specific nodes (e.g. between a product page and a cart) or the paths passing through a specific node (e.g. a newsletter sign up page).
Preparation to path analysis
YourCX offers the solutions to maximize the analytical functionality of the paths. That involves proper preparation of the website, based mainly on the description of subpages of the website with a simple parameter, for their efficient grouping. That makes it easier to analyse the traffic of users who, after entering the homepage, go straight to the search engine and switch between search results and product pages. Those paths are then analysed based on the subpage type, not just on the unique URL.
Identification of all conversion paths (through forward and backward analyses) ultimately allows to create advanced sales pipelines. The size of each subsequent sales stage can be determined and additional analyses of “dropping out” users, tailored to the context of a particular stage of purchasing process, allow for effective sales optimization. Such approach enables identification of key areas that require additional efforts to be taken to increase satisfaction and stop the abandoning users.
YourCX complements web analytics with a context relating to intentions and emotions. Contact us and learn more about our innovative solutions for analysis of paths and conversion rate!