Programmai > Predictive Marketing Platform > Core Features > Profiles

Over the coming weeks and months, I’ll be revealing our Predictive Marketing Platform.

We’ve worked extremely hard to build a product that allows a team of marketers to deliver key marketing messages to consumers that drive business outcomes, when both the time and opportunity are optimal.

Before we take a deep dive, let me share why we’re doing this.

Marketing & Advertising is commonly plagued with inefficiency and lacking in customer-centricity, our team has experienced this pain first-hand.

Retailers spend the majority of their budget on consumers who’ve recently been to site, which can bloat expenses and vary in its incrementality to the bottom line — they often use one or two data points to make decisions around targeting, and have fallen victim to optimising for last-click return.

Consumers are not treated as individuals, with unique behaviour, but grouped into recency segments for targeting. They see ads towards the end of their purchase journey, for example, and dislike/distrust the experience enough to install ad-blocking software.

We’ve addressed this and hope to excite you with the predictive data points we offer, and the power they possess to drive radical change for your business.

The Platform currently has three Core Features, with more to come this year.

The first Core Feature is Profiles, and this is where it all starts.

We connect directly to your first-party data sources, no implementation or tagging required.

Unlike traditional customer profiling, we’re not telling you what you already know about your consumer, but rather, we’re using Deep Learning to understand what’s happened historically in order to predict what is likely to happen in the future.

It’s extremely difficult to visualise this, but the image below attempts to add a bit of colour.

— complex interaction of all customer features or values when predicting an outcome

— position and colour of dot denote importance and relevance per customer

This process takes some time and is challenging. Retailers may share common goals but when it comes to their business, product and consumer, the ability to adapt and customise while retaining accuracy is crucial. Too cookie-cutter and you forego performance; too customised and you forego scalability.

The revolution in AI means we can harness insights from vastly complex interactions in your data. We aim to distil this complexity into actionable scores. We’ll discover how powerful this can be in the next chapter in this series.

Coming up next, Predictions, the second Core Feature of our Platform.

Stay tuned.