A product configurator collects several types of data from users, including session behaviour, product preference selections, configuration choices, and, in some cases, personal contact details. The exact data collected depends on how the configurator is set up and what business goals it serves. This article walks through the most common data types, how they are tracked, and how businesses can put that data to work.
What types of data does a product configurator collect?
A product configurator typically collects three broad categories of data: behavioural data (how users interact with the tool), preference data (which product options they select), and personal data (if users submit a quote request, save a configuration, or complete a purchase). The combination of these data types gives manufacturers and retailers a detailed picture of customer intent.
Behavioural data captures things like time spent on each configuration step, which options were explored, and where users dropped off. Preference data records the specific choices made, such as material, colour, size, or finish. Personal data only enters the picture when a user actively provides it, for example, by entering their name and email to save or share a configuration.
Together, these data streams go well beyond what a standard product page can offer, giving businesses insight not just into what customers bought but into what they considered before deciding.
How does a configurator track user behaviour during a session?
A product configurator tracks user behaviour by logging every interaction within the configuration session. This includes which steps were visited, how long a user spent on each one, which options were selected and then changed, and whether the session ended in a completed configuration or an abandoned one. This data is captured in real time, without requiring any input from the user.
Most modern configurators record this at the session level, meaning each visit generates a structured log of actions. These logs can reveal patterns such as which configuration steps cause the most hesitation, which combinations are most frequently explored, and at what point users tend to leave without completing the process.
This kind of 3D product configurator analytics is particularly valuable for identifying friction points in the buying journey. If a large share of users consistently abandon the configurator at the fabric selection step, that is a clear signal to review how those options are presented, whether visually or in terms of the number of choices available.
What product preference data can manufacturers learn from configurator usage?
Manufacturers can learn which product variants, materials, colours, and combinations are most popular among their customers. Configurator usage data reveals real demand patterns across the full product range, not just the options that end up in completed orders. This includes configurations that were explored but never purchased, which can signal unmet demand or pricing barriers.
Over time, this preference data becomes a strategic asset. It can inform decisions about which variants to stock, which combinations to feature in marketing materials, and which options might be worth discontinuing. For manufacturers with complex, highly customisable products, this level of insight is difficult to obtain through any other channel.
For example, if a sofa configurator shows that a particular fabric colour is frequently selected but rarely converted into an order, that could indicate a price sensitivity issue or a visual presentation problem worth investigating. Aggregated across thousands of sessions, these patterns become reliable signals rather than anecdotal observations.
Does a product configurator store personal data about customers?
A product configurator only stores personal data when a user actively provides it. Anonymous browsing and configuration sessions generate behavioural and preference data without capturing any personally identifiable information. Personal data such as name, email address, or delivery details is only collected if the user submits a quote request, creates an account, or proceeds to checkout.
This distinction matters for configurator privacy compliance. Under regulations like the GDPR, businesses must be transparent about what personal data is collected, why it is collected, and how long it is retained. A well-implemented configurator separates anonymous session analytics from personally identifiable records and handles each according to the appropriate legal basis.
It is worth noting that even anonymised preference and behavioural data can be subject to cookie and tracking regulations depending on how it is collected and stored. Businesses should ensure their configurator setup is reviewed against applicable privacy requirements and that their privacy policy accurately reflects the data collected through the tool.
How is configurator data shared with CRM, ERP, and other systems?
Configurator data is typically shared with CRM, ERP, and other business systems through API integrations or data export functions. When a user completes a configuration or submits a quote request, the output, including the selected options, pricing, and any personal details provided, can be passed automatically to the relevant downstream system. This eliminates manual data entry and ensures sales teams work with accurate, up-to-date information.
CRM integration
When configurator sessions are linked to a user account or a submitted quote, the resulting data can be pushed to a CRM platform. This gives sales teams visibility into what a prospect configured, when they did it, and how far they progressed, enabling more informed and personalised follow-up conversations.
ERP and order management integration
For manufacturers, the most critical integration is with ERP systems. A completed configuration that feeds directly into an ERP ensures that the bill of materials, pricing rules, and production requirements are all aligned from the moment an order is placed. This reduces errors, speeds up order processing, and removes the need for manual translation between what the customer chose and what the factory produces.
Beyond CRM and ERP, configurator data can also feed into PIM systems, marketing automation platforms, and analytics dashboards, making it a central data source across the entire commercial operation.
How can businesses use configurator data to increase conversions?
Businesses can use configurator data to increase conversions by identifying where users drop off, which options generate the most engagement, and which configurations are most likely to result in a completed order. Acting on these insights allows teams to optimise the configuration flow, improve the visual presentation of high-demand variants, and tailor follow-up communications to what individual users actually explored.
Practical applications include:
- Streamlining configuration steps where session data shows high abandonment rates
- Featuring the most-configured combinations in product listings and marketing campaigns
- Triggering automated follow-up emails when a saved configuration is not converted within a set period
- Using preference data to personalise product recommendations for returning visitors
- Identifying underperforming options and reviewing whether they need better visuals, clearer descriptions, or pricing adjustments
The key is treating product configurator user data as an ongoing feedback loop rather than a one-time report. Businesses that review configurator analytics regularly and adjust their setup accordingly consistently see improvements in conversion rates, average order values, and customer satisfaction over time.
How iONE360 helps you get more from configurator data
We built iONE360 to do more than let customers choose a fabric or a finish. Our platform captures rich product configurator data collection across every session, giving you actionable insight into how customers engage with your product range across all channels and touchpoints.
Here is what that looks like in practice:
- Session analytics: Track which configuration steps generate the most engagement and where users drop off, so you can continuously refine the buying experience
- Preference reporting: See which product combinations, materials, and variants are most popular across your full catalogue, not just the ones that convert
- System integration: Connect configurator output directly to your CRM, ERP, or PIM through our API, eliminating manual handoffs and keeping your data consistent across platforms
- Privacy-ready architecture: Our platform is designed with GDPR compliance in mind, separating anonymous behavioural data from personally identifiable records
- Scalability: Whether you have hundreds or millions of product variants, our visual product configurator handles the complexity without compromising performance or data quality
If you want to turn your configurator into a genuine source of commercial intelligence, we would be glad to show you how iONE360 works in practice. Get in touch with our team to arrange a demo tailored to your product range and business systems.