AI Product Recommendations

Real AI-based personalised products recommendation

Product recommendations allow users to discover new products. If they decide not to purchase the product they are viewing, the recommendations fuel their curiosity and make them want to discover more.

Quarticon: only real AI models: such as those on YouTube, Netflix or Facebook. Elsewhere: content filtering and the most popular. The difference: up to 3x in conversion.

Real, customizable Predictive AI models for ecommerce, not just simple rules

How Quarticon stands out

Only true predictive AI algorithms

What difference does it make? Well, up to 3.5 times higher conversions compared to simple rules from the competition. Don’t be fooled by random product selection and presentation of the most popular ones under the guise of Selected for you.

Adjustable to the most difficult tasks

Our recommendations can be fine-tuned very precisely, allowing for a variety of scenarios in different industries. It’s not just one strategy, such as cross-selling. It’s dozens of cross-selling strategies individually tailored to your needs by our team of experts.

Own CDN

Our own CDN for images allows for faster loading of customer pages (reducing the load on customers’ own resources) and faster delivery of content to the user. Our systems prepare and deliver photos in dozens of different sizes – the most suitable for the user interface.

Real analytics

We say that this is probably the most accurate analytics in the world. This is because we do not engage in ‘Analytics Fraud’, which involves attributing other transactions to ourselves. We do not rely on Google Analytics for our analytics, which facilitates ‘Analytics Fraud’. We provide a true picture of the effectiveness of our product recommendations. Ask us for details.

We do not rely on 3rd party cookies

Our solution is cookieless. Resources are not blocked by most adblockers or search engines themselves. This, of course, allows for higher conversions. In the most difficult cookie blocking environments (not to be confused with respecting user privacy, of course), we still deliver recommendations to users, while others come up empty-handed.

1p implementation

For even higher conversions and faster content delivery by browsers, we have launched a globally unique 1p implementation. All scripts and content are delivered from the customer’s domain. And conversions? Twice as high as before. Take care of your conversions with our 1p implementation.

No templates

We don’t need templates. With each implementation, we recreate the appearance of elements from the client’s website. Our recommendation frames do not differ in appearance from the elements on the website.

Enrichment with CRM and offline data

For faster model training, the collected data can be supplemented with archival data, which will increase the effectiveness of recommendations from the very first day of their use. Similarly, we supplement information about logged-in customers, increasing the effectiveness of recommendations.

Free support

We constantly monitor and adjust recommendations to the needs of our customers, even after their implementation.

Benefits for your team

Personalisation in every channel

Product recommendations in every channel, from product carousels on websites, pop-ups, emails, push notifications, text messages and social media messages. Each place is different, and so are the recommended products, depending on the user’s stage in the purchasing journey.

Types of recommendations

Each recommendation strategy can be tailored to individual needs in dozens of ways. We start, of course, with the basic types of AI recommendations: Selected for you, similar products, cross-selling, up-selling. Of course, abandoned basket, bestsellers, popular, trending, and recently viewed products are also available.

What metrics are we improving?

First and foremost, we are increasing conversions and clicks on product pages. We are increasing sales, the total number of transactions, and the value of the shopping basket. We report this in our statistics. But let’s also remember that we increase the efficiency of shops by solving key challenges and optimising important elements. We reduce bounce rates and present products that engage users. We help reduce the number of abandoned baskets. In this way, we also influence the overall user experience and their satisfaction with the shop.

AI recommendations vs. SEO and sales from media channels

Of course, real AI recommendations increase user session length, thereby reducing the bounce rate. Everyone knows how this affects SEO 😉 The same applies to SEM and media channels. Genuine AI recommendations, by optimising user paths, result in a higher effective CPC (eCPC), which leads to lower costs on Google and other CPC and CPS-based media (such as affiliate programmes). It’s time to finally take care of conversions!

Autonomous decisions, not tedious analytics

The autonomy of our system is what sets us apart from CDP. We want our recommendations to be completely autonomous, without placing unnecessary burdens on users in the form of tedious data analysis and model building. Our recommendations adjust themselves and learn with each subsequent page view, click, and transaction recorded by our system. All in all, if you are not a telecom or a bank, there is no point in ‘loading up’ on CDP. Take advantage of our autonomous solution!

The only recommendations that work without cookies, with Firefox ETP and with ad blockers

It works with

Experience

Try our Product Recommendations

Just reach out to us, okay?

When it comes to e-commerce and product recommendations, no one knows it better than we do. Neither e-commerce platforms, nor marketing automation systems, nor CDP systems. And certainly not analytical systems. With the right tools, you can completely revolutionise your business, achieve success and gain an edge over the competition.

The AI solutions we offer to personalise the shopping experience and increase sales are incredible. We’re talking about optimising everything and increasing sales like never before. Add fully autonomous decisions and targeting to your marketing.

Fill out this form and make your shop great again – really great.

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FAQ

Why implement personalised AI Product Recommendations?

The primary goals of implementing AI-based product recommendations are to sell, sell and sell again. With every movement of the user, we know better and better which product he/she will be interested in and which he/she will put in his basket. We even know this earlier than the user himself. Recommendations improve also overall shopping experience by consistently providing personalised suggestions for the most relevant products.

Can I adjust product recommendation models to my needs?

Absolutely! You can customize personalised product recommendations to suit your preferences. This level of customization ensures that the tool reflect a your specific interests and needs, enhancing the overall shopping experience.

What data is utilized for personalised product recommendations?

Personalised product recommendations are created using a range of Big Data, including behavioral data (such as anonymous purchases, views, and clicks, browsed products, time spent) and content data (like item metadata). The system can also tailor product suggestions based on a user’s browsing history.

Can personalised product recommendations improve search engine optimization (SEO)?

By offering relevant product suggestions, personalised product recommendations can boost user engagement and enhance the browsing experience, leading to higher user retention and lower bounce rate. Since engagement and user experience are crucial factors in SEO rankings, these recommendations may indirectly contribute to improving your website’s SEO.

Are all product recommendations the same?

Many entities provide product recommendations, but this does not mean that they are valuable recommendations based on machine learning. Finding connections between products requires significant resources and computing power. Most providers, such as shopping platforms, marketing automation systems, and CDP systems, simply provide simple rules – best sellers or recently viewed items. These are not real recommendations! Even random product displays achieve better responsiveness than many simple rules.