Improving Customer Data Insights With AI & Online Product Configurators

March 8, 2022
 Min Read

The way customers shop can be erratic at the best of times, with a variety of elements coming into play. The current economic climate and state of public finances being the two most notable for retailers. As a general rule, retailers experience an influx in sales seasonally and after payday - but shopping is a 24/7, 365 days a year activity regardless, thanks to online and brand flexibility.

3D configurators allow customers the freedom to choose the design of an item to suit their taste, which immediately improves experience. However, at this point the customer isn’t aware of what’s going on behind the scenes. Although brands may have had to change the way they hold customer data thanks to GDPR, they are still well within their rights to analyse how their sites are used and identify behavioural patterns.

AI facilitates this process, tracking it step by step and feeding the results into CRM systems for future use. These customer data insights are invaluable to brands, allowing them to offer the kind of products people are searching for, refine their buyer personas and increase profit by getting ahead of their competitors.

In order for AI to do its job and collate valuable data insight, brands need to have a variety of touch points available to link to their ecommerce platform. Examples of touchpoints include form data, app interactions, surveys and call centres. This streaming data feeds into customer profiling, covering their interests, preferences and protecting their loyalty. The final step is paramount, where customers are engaged with in real-time to nurture and make them feel valued.

This engagement can take many forms, including web chat, email follow up, third party reviews and mobile app notifications. Whilst product configurators are designed to give the customer the chance to be unique and set the trend, they are also helpful in gathering insights to improve and build brand identity. Where AI is concerned, customer journeys are already mapped out, it’s just a question of how they are used, where we, as customers, are clicking and whether or not we convert.

For example, it may seem that if a customer is consistently using your site to compare prices and not actually purchasing your product(s), that person is unlikely to be positive data to feed into your buyer personas. But, if competitive prices aren’t available and it’s a persona you’d like to attract, AI plays a helpful part in identifying how you could adjust pricing or the customer journey to achieve that.

AI is so valuable because it runs in the background, a busy customer shopping online or logging into the app won’t be acutely aware of the process, but it is secretly shaping the future of retail more efficiently than the average human can. A large dataset offers the brand options and advocates for continued learning about their customers, not just as people but as part of a changing retail marketplace.

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