Higher conversion rates by predicting visitor propensity to buy
The customer journey is about so much more than marketing, and you want to make sure that once you do have attention, you make best use of it, responding to potential customer behaviours in ways which work best for them and for you.
Today it is possible to do so much more than just eyeball some analytics reports and try to work out what is working and what is not. Patterns of visitor and customer behaviour can be detected and linked to purchase behaviour using machine leanring, so that you can objectively optimise that journey in real time.
Imagine if you knew exactly what each image, link and feature of your site or app contributed to purchase or goal fulfilment, for every customer. This is what you can acheive with a custom algorithm trained on your data. So much more than a ‘funnel’ your custom model can detect patterns which predict what each visitor will do next, so you can adapt and personalise your response for maximum effect.
Predict if your potential customers will convert... before they actually do!
Your new customers and site visitors will behave much the same as the ones who arrived in the past. Their online patterns will vary between casual browsers, purchase researchers and intent buyers – you can train a machine learning model to distinguish these patterns, and learn how to respond in measurable ways to increase sales.
Target low propensity visitors for sales uplift
Since you can see who is more likely to convert, you can devise ‘buy now’ stategies to pick up the borderline cases and close those less certain sales.
Precisely identify how UX features drive sales
Each feature and UX design helps or hinders sales. A valuable outcome of conversion prediction are ROI per feature reports so you can see what elements of the site to focus on, supporting UX designers with data driven insight.
Discover what customer characteristics drive sales
Customer characteristics, as represented by GDPR compliant data about customer segments, locations, device use, repeat purchase patterns and product interests, can all be linked to sales through this type of model. Find out what matters to act for sales growth.
Very high levels of objective accuracy
Your models will be cross validated on blind data for objective technical metrics of predictive accuracy. There will be no doubt about how well you can predict and respond to your customer journeys.
Transparent decision rule models for easy application
These are not black box machine learning algorithms, but real algorithmic models you can examine and even tweak rule by rule, produced by an ML process. Not just insights here: these models can be deployed in live production environments whatever your tech stack.
Is this for you?
- Conversion Geni is a custom machine learning model which predicts whether online visitors will convert (buy something, or take a certain action).
- It is trained exclusively on your first party analytics data, predicting based on visitor data and patterns of behaviour.
- It can be combined with Click Geni for end to end customer journey optimisation.
- We work in close consultation with your marketing and analytics experts.
- We offer free workshops around customer journey challenges, for brands who may be interested.
- Interested to know more? Contact us: email@example.com