Conventionally, quiz experiences use filters to select a subset of SKUs that might be relevant or a category that the user is directed to. Whilst some shoppers find this useful, most expect more personal recommendations.
Our combination of powerful filtering and artificial intelligence means that the recommendations are the best products for that customer's unique situation. Rather than redirecting to a category with hundreds of SKUs, BOON's recommendation engine picks out the best cross-category ideas and presents them to the customer.
Our psychology-based question design also creates a far more engaging overall experience and enables a deeper understanding of the customer's desires, and the interaction on the recommendations listing page is loved by shoppers.
We use psychology research during the design stage of the questions for two main reasons.
First, it helps create far more interesting and engaging experiences for customers. By asking questions other than the standards (e.g. relationship, event, budget, interests), shoppers are surprised and excited, and ultimately have a more enjoyable experience.
Second, our artificial intelligence is unique on the market today. Rather than learning links between SKUs, the AI finds and learns associations between SKUs and personality traits. This makes it the world's best system for recommending gifts and products for anonymous users. Our psychology research allows BOON to understand each customer's personality and attributes on a much deeper level and therefore give better recommendations.
During onboarding, clients provide a data feed with as much item data, attributes and categories as possible. We need this for multiple reasons; to efficiently run filtering, present recommendations to users online and make recommendations using the AI.
Conventionally, artificial intelligence or machine learning algorithms require a huge amount of data to learn links between inputs (shopper attributes) and outputs (SKUs). Algorithms that require example 'answers' (correct links between inputs and outputs) are called 'supervised' algorithms. However, another class of algorithms, 'unsupervised' AI, can generate understanding without any example answers.
We make use of these unsupervised algorithms to create an accurate and complex understanding of each SKU. Our psychology research allows us to procedurally calculate associations between personality attributes and the SKUs' information so that excellent, personal recommendations can be generated without any user feedback.
As users provide feedback these associations are updated to ensure that they are as accurate and up-to-date as possible. Whilst we cannot share the precise inner workings of our proprietary algorithms, if you'd like to know more, you are welcome to ask us and our team will be happy to help.
Our pricing model is flexible to accommodate different clients, priorities and budgets. In general, new clients pay an onboarding fee for the design and setup of their custom experience before monthly payments during a trial period (normally around 3 months). After a successful trial, monthly payments at a new rate (based on the performance of the trial) are agreed upon.
Costs are discussed on an individual basis and depend on the quantity of SKUs, expected usage, diversity of product types and use-case of BOON.
We've strived to have as little impact on page load speed as possible. BOON always loads asynchronously to avoid delaying page rendering.
We offer multiple options to optimise the loading speed and priority for the integration. Loading BOON can be prioritised if it is an integral part of a page. Otherwise, it will be loaded with a low priority and will have minimal impact on page load speed.
Whilst BOON can be used for any retail sector, it is best for those with products that are not purely functional (not utilitarian). In utilitarian sectors (e.g. DIY goods), recommendations would be mostly based on filters using BOON's powerful filtering engine. On the other hand, hedonic sectors (those with aesthetic or desire-driven products) will be able to make use of our proprietary AI recommendations in conjunction with filters to ensure highly accurate recommendations.
Aside from this suggestion, BOON is excellent for all sectors including gifting, luxury, jewellery, homeware and many more. Ask us if you'd like to know if BOON is right for you.
Almost every aspect of the experience is customisable, from the colours, fonts and option sizes to the imagery, tone, content and even the text on buttons. You can make BOON seamless with your existing website.
We give you the flexibility to place the experience wherever you'd like. With two integration modes (inline and modal), BOON can be launched as an overlay with the click of an inline or floating button, it can be the centrepiece of your homepage or its very own page. Or, a combination of those options.
Users see the experience on your website so they don't navigate away.
The Console is a work-in-progress project that will be the hub for retailers to design, evaluate and update their question experiences. So far, clients can view overview analytics, update major experience content, customise experience styling and manage their account.
During onboarding, we will research your customer base and your catalogue to design a first draft of the questions. These will be presented to you and your team for feedback before changes are made for approval. You are invited to have as much or as little input in the process as suits you.
It typically takes between 4 and 8 weeks to complete onboarding.
You can view full details about integrating BOON in the documentation.
BOON's users never need to sign in, provide an email, their name or accurate age. There's nothing more annoying than completing a quiz to be asked for your contact details to be sent your results. Our recommendations are shown immediately, in-line with the experience.
By answering the questions, shoppers are empowered to control their data. They only provide information knowingly and understand what it's used for.
Most people don't know the extent to which they are surreptitiously tracked online and the power of that data and we don't think they should have to. We are working to make sure that online users get control of their data and still receive excellent personalisation.
Along with usage and performance analytics, we use aggregated, anonymous question responses and user feedback to deliver valuable insights for our clients.
This data is made available on the Console, through weekly overview emails, occasional in-depth reports and integration with Google Analytics. Additionally, BOON aim's to respond to any specific requests for insights from our clients rapidly.
You can find more information about Google Analytics integration on the documentation.