Ecommerce Personalisation with Business Logic

One-to-One Personalisation in Real Time

Meet Claire…

Claire is a brand-loyal customer who frequently shops at the same stores.

She loves to buy women’s fashion and homewares, and seeks inspiration by flicking through look books and reading articles and blogs. She also shops for her son, buying his at-home and school wardrobes from the same places she enjoys shopping herself.

Because Claire returns to the same online stores to shop, they know a lot about her likes and dislikes. They know which sizes she wears, which content she reads, what her favourite colours are and which brands she’s most likely to buy next. This information can be used to help Claire find the content, categories and products she is most likely to be inspired by.

The Filter harvests this data from the very first time a customer visits your store, building a Customer Taste Profile that can be used to form more intelligent personalised merchandising decisions on a one-to-one basis.

Claire’s Customer Taste Profile

Claire has been a loyal customer of your brand for 2 years and within that time she has made 10 separate purchases across several categories.

Lead Categories Claire Has Shopped In

  • Women
  • Home
  • Kids
  • Gifts
  • Sale
Products Claire Has Bought

  • Women – T-Shirts, Knitwear, Jeans, Tops, Dresses, Skirts, Accessories, Jewellery, Perfume, Cosmetics & Handbags
  • Home – Furniture, Soft Furnishings
  • Children – School Uniforms (boys), Tops (boys), Jeans (boys), Coats (boys) Bags & Accessories (boys), Shoes (boys)
  • Gifts – Candles
Claire Prefers

  • Black,  Brown, Yellow, Red, White, Cream, Blue and Grey
  • Women’s sizes – S/M, S, 8, 10
  • Women’s shoe sizes – UK 6 and EU 39
  • Children’s sizes – age 7-8 and age 9-10
  • Children’s shoes sizes – UK 2, UK 3 and UK 4
  • Home Sizes – Kingsize, Single
Claire’s Favourite Brands

  • OPI
  • Liberty
  • Alexander Wang
  • Escentric Molecules
  • Alexander McQueen
  • Sophie Hulme

Our software cross references strategies with your customer’s purchase history to help it make the most relevant merchandising decisions in real time. API calls between the software and your customer data determine which strategies are most important to each individual customer and adapts the website journey to better suit their needs.

Claire’s Personal Shopper

A shop assistant will ask customers questions to help them find the best products, but your website doesn’t have to. Our suite automates the perfect blend of visual navs, promotions, recommendations and prioritised product feeds to appeal to each individual customer. The balance between historic user data and live on-site activity gives you a highly-relevant personalised customer experience (CX) that can be further adapted to fit your sales cycle, inventory and other business rules.

For Claire, this means showing her the products that complement her previous purchases, consumables that she may be ready to re-purchase and new products from her favourite brands as a priority. As she interacts with content and products, the site adapts with click-led merchandising that reflects her on-site journey.

For more prominent discovery, our in-account Product Finder takes the best merchandising decisions for Claire and transforms them into a visually-enticing product edit that encourages engagement with new and previously viewed products.

Liberty London’s ‘My Edit’ creates a personalised look book

Add Your Business Rules

Ecommerce personalisation markets the right products to the right customers but it’s less adept at making business-based decisions. The Filter’s solution goes beyond best practice personalisation by bringing your full sales strategy to the forefront of decision making.

Adapt priorities using stock levels, profit margins, like-for-like product performance, shelf life, customer lifetime value or spend, marketing activity, promotions and more. The Filter balances your inventory, existing strategies and business needs with a personally optimized user journey to create merchandising campaigns that adapt in real-time as your priorities change.

Chosen for me


Machine learning creates an accurate shopping profile for each customer to form the basis of personalised CX strategies.

Cross media recommendations

CROSS MEDIA Personalisation

Use a mixture of content, products, categories and other visual navigational items to inspire and convert.

People also…


Crowd logic assists in finding similar products, best sellers and similar behavioural patterns to refine strategies.

Override and fine-tune


Perfect personalised strategies with sophisticated rule sets that account for your business needs.

Items I have…


Use a customer’s past purchases to inspire product selections and improve accuracy by incorporating child variant preferences.

Complete control


Automate campaigns with limiters, tuners and pre-set dates that alter priorities throughout the life of the strategy.

Want to Learn More?

with your questions or to arrange a demo.

The Filter Suite:

Download Whitepapers

Tech Guide to Personalisation
Personalised Communication for E-Commerce Success
E-Commerce Personalisation & Discovery
The shopping journey