💡 Good to know: Want to measure the impact of your product finder on e.g. sales and conversion? Then check out this tutorial.
1. Analyze usage
The most important thing you want to know is how many customers use your product finder - and how they walk through product finder.
1. Go to the Analytics section.
2. On the Usage tab, you can see the most important statistics for a given time period (along with some fancy charts for the visually oriented!):
Sessions - The total number of times the product finder has been started.
Advice views - The total number of sessions that viewed the advice page (excluding sessions where no results were shown in the advice).
Empty advices - The total number of sessions where no results were shown in the advice. You will only see this information if 'empty' advices were actually shown.
Click-through - The total number of sessions that clicked on at least 1 product on the advice page.
Click-through rate - The ratio of Advice views to Click-through.
3. Use these insights to determine if your product finder results can be improved.
Together, these statistics show exactly how your customers walk through your product finder:
They start the product finder and click through the questions → Sessions
They view the advised products on the advice page→ Advice views.
They view one or more products in your shop → Click-through
Is the number of Advice views much lower than the number of Sessions? This may indicate that the product finder itself is relevant to your customers, but that your conversation needs some attention.
In that case - keep reading! ⬇️
2. Analyze your conversation
In addition to the key usage insights mentioned above, you can also see customer behavior at product finder.
1. Go to the Analytics section.
2. On the Conversation tab, you will see statistics on behavior within the selected time period:
Distribution of answers per question - This shows per question how many times each answer was selected....
Question drop-off - Here you can see at which questions customers left your product finder.
Below we discuss what this data shows about your product finder and your customers.
2.1. Distribution of answers per question
You will see these statistics for the selected time period:
Amount - The number of times an answer has been selected.
Ratio - The ratio of the number of times an answer was selected to the total number of answers selected for this question.
With this data, you can improve your conversation, enrich your customer profiles and perhaps even adjust your product offerings.
AN ANSWER IS MISSING FROM THE TABLE
If one of the answers is not shown in the table, no customer chose this answer in the selected period.
Now ask yourself:
Is that answer relevant to my target audience?
Does the answer represent a specific need of my customers?
If not: delete it or replace it with a more relevant answer.
Here you can see that customers of our (fake) webshop for hiking shoes are mainly interested in waterproof shoes and somewhat less in breathable shoes:
2.2. Question drop-off
You will see these statistics for the selected time period:
Total views - The number of times a question has been viewed.
Answered - The number of times a question has beenanswered.
Did not answer - The number of times a question was not answered (i.e., a customer left product finder while viewing that question).
Drop-off in % - The percentage of times a question was not answered relative to the number of times it was viewed.
💡 Good to know: this functionality was launched on July 21, 2021. Data prior to that date is not available.
With these insights, you can improve the conversation and ensure that more customers reach the advice page.
For our hiking boots web shop, for example, we might ask ourselves:
Are the questions "Who will be wearing these hiking shoes?" and "What kind of hikes will you go on? " perhaps too difficult to answer?
Do these questions address actual needs of our customers?
Are customers' situations or needs well represented by the answers? In other words, are any answers perhaps missing?
Does it help to add images to the question or answers? For example, in the question about the type of hike.
Or should we change the wording of questions?
With these types of questions, you can set up experiments and A/B tests that can help optimize your product finder.