12th August 2019 - 3 Min Read Time

PureClarity AI: The Foundation of Ecommerce Personalisation

One of the questions we are often asked is how the Artificial Intelligence (AI) from PureClarity works.

Below is a simple guide that explains how it works and how it is used to provide your online customers with a highly personalized online shopping experience.

AI and Big Data Technology

PureClarity is built on AI and Big Data technology. It collects data about every one of your visitors, tracking their interactions with you onsite and offsite to build up a picture of their behaviour, their dislikes, likes, interests and habits.


How PureClarity Works

Identify and Target Different Customer Segments

This information is then used to present relevant and personalized results onsite and offsite. PureClarity also analyses this mass of data for every interaction and everyone on your site to see if there are any hidden customer segment based behaviours you should be exploiting, e.g. “Camera Lovers.” With PureClarity you have at your fingertips the ability to drill down into this data; you can time slice and segment the information to get a deeper understanding of your website performance.

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Real-time Performance

PureClarity works in real time using a hybrid AI model to dynamically learn and adapt to new information and new behavior and trends. As visitors arrive on your site, PureClarity will change the recommended products and strategies based on their behaviour in that very visit. PureClarity will show recommendations that worked on other visitors to maximise the chances of them seeing relevant results and buying on that visit.

Works With All Data Amounts

PureClarity optimises the recommendation algorithm based on how much data is available. For sites without much data, PureClarity makes the most of the sparse data by implementing a content-based filtering recommendation system, which has really incredible results for some of our clients already – check out JewelStreet to learn more about that.

Effective Cross-Sells and Upsells

With more data, PureClarity uses a collaborative filtering algorithm, which means that the large amounts of data are analysed to find the optimal cross-sells and upsells based on what your customers are looking at and buying right now. To see some of our stellar results from this kind of client, such as our client ZyroFisher.

No Duplication of Content

The AI will never show two of the same strategies on the same page, and will work to minimize product duplication on the same page. Visitors can enjoy relevant, specific product recommendations without seeing any of the same content, guaranteed to increase your average order value and conversion rate – like for our client Green-tech.

Optimised A/B Testing

PureClarity’s AI engine does A/B testing in the background, testing which strategy works best. If your customers respond best to cross-sells, PureClarity will favor those algorithms. If they prefer strategies which show more of the products that are popular on your site in real-time, PureClarity leans more towards that. Every recommender is optimized to be right for the customer, the page it’s on, and the overall trends on the site.

The Engine also uses deep pattern mining AI techniques to find hidden segments and use predictive behaviour to present the most relevant results to individuals.

Overlay with Enriched Personalised Marketing Campaigns

The AI can be combined with enriched personalisation to enhance the user’s experience; creating segments to present promotions and products, categories and brands to specifically targeted users.

In short, what this all means is that your visitors are going to experience a completely personalised recommendation strategy that changes in real time as PureClarity collects more information about them, always optimised to maximise your conversion and average order value.

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