Dynamic Recommendations

We’re banning the black box AI, welcome to transparency


We’ve banned the black box algorithm! Why? Because every brand needs transparency and control when it comes to product discovery.

We serve millions of dynamic recommendations every day. Serving up products and content that is hyper-relevant to each individual for that specific time, with that specific profile and for that particular use-case.

Dynamic recommendations update in real-time based on each shopper’s available information and on-site behaviour. This way we ensure the recommended products and content are as relevant as possible for each individual.

We can serve up products or content based on similar or complementary searches, best sellers, as well as cross- and upselling. A/B test algorithms provide the best recommendations and use merchandising rules to complement the test results.

Let’s face it, AI can make sense of millions of purchases and content experiences offering up shoppers something that is relevant and inspiring. Data doesn’t lie. Leave it to the machines, but stay in control.


Hyper-relevant recommendations from day one

Benefit from ready-to-use pre-trained algorithms right out of the box, ready to assist you with personalised recommendations. This provides you with a quick start. Our algorithms enable a fast return on investment with an ongoing opportunity to train them further based on brand values and experience.

Inspire at every shopper touchpoint

Never miss an opportunity to engage ever again. Encourage shoppers to view more products and increase their likelihood of converting through product and content recommendations across the home, category, product detail and basket pages.

Extend the online shopping experience and bring them back to your website with personalised re-engagement campaigns.


Harness upselling and cross-selling

Ease product discovery by displaying similar recommendations on product detail pages. This increases average order value (AOV) and drives additional purchases through alternative or complementary products offered on the basket page.

Boost sales by driving attention to high converting products

Increase the likelihood of conversion using our discovery algorithms, including Most Popular, Best Sellers and New Collections.


Build loyalty and increase lifetime value

Provide a seamless shopping experience and increase repeat purchases by letting shoppers pick up where they left off, with recommendations based on browsing history. Re-engage shoppers and follow up on any abandoned purchases with personalised recommendations based on their last visit. This level of engagement cements loyalty.

We offer a wide variety of recommendations


Personalised recommendations

Show the most relevant products to each shopper every time. Recommend products that match the shopper’s intent. This is based on real-time personalised browsing behaviour.

Our customers have seen significant results from applying our personalisation algorithms:

  • 80% of the turnover now generated via 20% of the products that have personalised recommendations applied
  • 21% boost to adds-to-basket from personalised recommendations

Make popular products stand out

Inspire shoppers with popular items among like-minded individuals, including Trending, Most Popular and Others Also Liked.


Suggest something visually similar

Help your shoppers find the right product for them by recommending visually similar alternatives to the product displayed. You’ll maximise conversions and never miss a sale due to out-of-stock items again!

Forever New achieved amazing results by utilising our visually similar recommendations:

  • 135% increase in conversions
  • 21% increase in average order value
  • 45% reduction in page bounce rate
  • 30% reduction in page exit rate

Shoppers don’t forget brands who educate and inspire

The right content matters. We help you tailor content to the shopper’s interests and intent. Dynamically adapt and personalise recommendations to each shopper’s preferences, category affinity and real-time intent.

Read how SanteDiscount achieved a 3x rise in click-through rate RPM (Revenue for 1000 impressions) by utilising content recommendations.

Read the case study

Want to learn more?

Email is still alive, so is its potential

Send personalised emails that are adapted to each shopper’s profile and calculated based on their behaviour. Utilise email personalisation to offer each shopper highly targeted content. Capitalise on key consumer milestones such as birthdays or follow-up after a visit or cart abandonment to re-engage. Don’t miss a chance to engage.

By utilising highly personalised emails, you are able to provide customers with the exact information that inspires them, interests them and ultimately motivates them to respond. In this way you will be able to build stronger more valuable relationships that lead to higher conversion rates and improved commercial performance.


Open rates by up to

70 %


5 times

5 times


Customer satisfaction by

70 %

Our customers’ results speak for themselves

  • 17.6% increase in conversion directly from recommendations
  • 40% increase in click-through rates directly from recommendations
  • 21% increase in average basket value
  • 26% overall increase in email click-through rates
  • 30% increase in click-through rate from recommendations as a result of re-engagement activity

“Visually similar recommendations have helped us present products that meet our shoppers’ requirements without compromising on the original style of the product that attracted them in the first place. It has also encouraged seamless product discovery and inspiration with shoppers now purchasing new but similar styles and products across our vast product range.”

Rachel Tigel Senior Ecommerce Manager, Forever New

“Attraqt’s ability to effectively manage personalised content recommendations the same way it manages product recommendations – and doing so without any constraints – is what made their solution superior and won us over.”

Loic Lagarde CEO, Santédiscount

Ready to see our platform in action?