Pixoneye enables companies to completely understand their mobile customer and deliver in-app hyper-personalisation, by analysing customers mobile photo galleries using AI and computer vision.
By providing a real-time understanding of individual users - these unrivalled insights are used to provide tailored recommendations per user and enhance targeting capabilities for companies’ ads, offers and services.
Pixoneye has partnered with Tesco, Nestle and EasyJet, and have recently started working with a leading mobile handset manufacturer and an Israeli publisher. Our tech is award winning - we recently won best AI company 2017 and Digital Media Award 2016 at MWC’s 4YFN, the world’s largest start-up event.
What we do
Market Need: Every day, brands make decisions based on the same generic third-party data sources (search history, purchase history and location). This means that customers are poorly understood and targeted - IBM reports that only 22% of customers say brands understand them.
Personalisation is increasingly vital in today’s mobile world – 77% of Digital Natives expect their online experience to be personalised, yet 60% of Marketers say they struggle to personalise content in real-time.
How we do it:
Pixoneye embeds its technology (software development kit) into a client’s app which teaches the user’s mobile device to analyse the photo gallery into 150 characteristics – including age, gender right through to income level and hobbies. Pixoneye’s accuracy is the same as Google’s image classifier but is approximately 5 times smaller allowing the process to occur on the user’s mobile device.
Pixoneye aims to disrupt this market by providing clients with unrivalled proprietary data about their users. Pixoneye is the only company with the capabilities to analyse user's photo galleries on device - a rich untapped resource that can be used to fully understand your customer. The technology relies heavily on deep learning processes that have taken 2 years of research and development with some of the leading minds in computer vision.
The market is enormous for Pixoneye - we can help every company with an app who wants to understand their users and target them better. We aim to do this by providing unique insights into their customers and using this understanding in our best-in-market recommendation engine to provide next level product, content and ad recommendations.
Offer in-app personalisation by serving the most relevant content (offers, ads, and services) to the right customer, utilising machine learning. This can be done using our automatic recommendation engine or using the client defined clustering mechanism.
Recommend to your customers effectively - increase relevancy, engagement, conversion and ultimately revenue.
Proactively recommend content (offers, ads, and services) to customers based on patterns that start occurring in the photo galleries (such as moving house, having a child, going on holiday).
Banks, telcos and energy companies, for example, are interested in the moving home event trigger. Pixoneye can look for a pattern shift in the photo gallery (photos of empty rooms, floor plans, buildings and so on) which culminates in moving home or cancelling their line rental. When this pattern starts occurring in someone else’s photo gallery, the bank will know the customer is about to move home and notify them about new mortgage rates. The main benefit is to decrease churn and increase revenue.
Anticipate buying patterns - additional revenue and increased engagement
Detailed customer analytics per user to 150 characteristics, presented either through the
Pixoneye Client Dashboard or as an additional layer in the client's proprietary system
Know exactly who your customers are - build look-a-like audiences for user acquisition