sub(x) makes using AI-based Machine Learning for customer acquisition a reality for any size of business.
Collecting and transforming data, then presenting it in a usable format is costly and time consuming. sub(x) marketing tools automatically transform raw data from user behaviour into an algorithm-friendly format.
Teams have to hypothesise about what will have the largest impact and prioritise a long list of to-do’s. We augment team capabilities by automating expert data scientist and data engineering functions.
Instead of focusing on what feature or channel “converts” better sub(x) looks for significance and causality of all marketing decisions then automatically orchestrates responses to subtle otherwise hidden signals.
We do an audit of your website and payment journey to understand all the marketing assets you currently use, from price offers to lead capture. This includes making suggestions of what else you can do.
We replace and enhance these marketing assets, instantly transforming every user interaction into a common data format that makes it possible to analyse and optimise.
Once we transform your data our existing model is used to make complex decisions and create custom AI-driven interactions and journey sequences that adaptively improve their performance over time.Explore Machine Learning
Our universal model can easily segment possible customers using a much wider variety of data.
Selecting the next best action or offer for each customer is an ideal use case for Machine Learning.
Our model uses complex data to determine exactly what variables generate the best outcomes.
ML-assisted forecasting can deliver up-to-the minute data for accurate predictions.
Underpinned by our universal data structure that learns about everything you create, our single design canvas is used for every personalised marketing action, from price offers to lead capture and abandon basket prompts.
Our Machine Learning model will select the right marketing asset type, in the right sequence to show to the right person, at the right time. This includes selecting animation, position and size, leaving you free to focus on the right messaging for each audience segment.
Our carefully designed approach means you can implement a Machine Learning strategy without the need for significant web resources and execute at a fraction of the cost of hiring a data scientist and engineer.
Since we partnered with sub(x) the team has continued to innovate and re-define how the customer acquisition works.
Explore innovative strategies and reduce operational and technical overhead by making deploying product, answering data questions, and optimising ROI quick and easy.
A data driven approach scales easily to your entire customer base — no more missing or incomplete data, simply scale, refresh and automate.
Focusing on your first-party data to serve relevant experiences and form more transparent relationships reduces reliance on third-party data.
Only specific characteristics that relate to your offering and brand will reflect in nuanced customer behaviour with corresponding signal strengths.
Usable in many other machine learning problems like clustering, predictions and recommendation systems across you business.