Overview

Suppose you own a homeware retail chain. You want to display relevant, personalised digital content for each of your Customers on their channels of choice, e.g. your own website. nudgeML™ enables this by determining the most relevant recommendations using predictive Machine Learning, or ML, based on historical data. But it does much more. You decide the boundaries of 'personalisation' (e.g. a person, a household, a business, a retail region). You decide what is being predicted (e.g. relevant product category to display in hero banner on your website for a given Customer; likely future value for prioritising Customer audiences in outbound channels; likelihood of leaving for retention budgeting) so that you can drive Customer interactions that are relevant to the Customer and make business sense. You can set sensible contact frequencies. Plus make recommendations in real-time, even for visitors who only provide snippets of in-the-moment data.

All activities can be compared against controls to ensure accountability, allowing you to understand the incremental benefit that nudgeML brings to your business.

nudgeML is a cloud-based tool, providing a self-contained, secure single tenant client environment. It is fully configurable for users, data and strategy, enabling you to have your own unique solution to your unique problem, harnessing best practice. With guidance, you can become self-sufficient, or you may wish to blend expertise into your existing workforce, or perhaps you prefer a more 'lights out' approach - it's your choice.

1. Data in

nudgeML works off data, turning noise into refined meaning and relevant, timely Nudges. Data can be automatically or manually loaded up in bulk via the Cloud or, in some cases, in real time via event APIs.

2. Shaping your Customers

nudgeML organises the input data into meaningful groupings such that you gain insight about the entities that drive your business value. You can identify where the volumes and value lie by whatever grouping you desire, based on your business audience, from individuals and accounts up to retail regions. This then helps you define communication strategies that make mutual sense for your Customer base, and for you.

3. Missions

nudgeML allows you to define measurable objectives, called Missions. You're free to decide what they are as you'll know your business best, but we can help shape these for you in line with good practice. The aim here is to accelerate the Mission outcomes, courtesy of the tool. You'll then have visibility of incremental benefit at this meaningful level.

4. Feature Engineering & ML

nudgeML accelerates learnings through its Machine Learning. A variety of ML models are at your disposal to achieve your Missions. The easy-to-use interface facilitates this task, and provides the feedback needed to ensure that the model is sufficiently trained and adding value. This includes the display of causal data attributes to improve cause/effect understanding and assist with improving relevancy of any downstream personalised creatives. It can then be automated to re-learn as and when new data becomes available.

The success of modelling is driven by the quality of the data that it's fed. nudgeML provides auto-ML capability to rapidly create engineered features. From a few clicks, scores of valuable aggregated fields can be generated. This agility is essential to reduce time-to-market and allow a factory of repeatable, consistent modelling capability, all focused on your Mission.

5. Nudges & Data Out

nudgeML takes data insight and recommendations one step further by orchestrating the delivery of recommendations to the desired Customer touch points, such as email and websites. Contact frequencies can be defined to ensure that interactions are in line with Customer expectations. Content can be referenced to align with personalised recommendations. We collectively call these Nudges, as we aim to gently accelerate Customers' progress along mutually beneficial journeys, relating to the given Mission.

6. Success & Learning

nudgeML reports back on success or fail of Nudge activities in the context of your Missions using appropriate controls. Closed loop data ensures learnings are ongoing, and are acutely focused on your objectives, so you immediately know what is working and what is not, and can take action.