FormFlow

━━ Case Study

Demand modelling the future

Predictive modelling harnesses the knowledge within your customer data to forecast future behaviour.

You’ll better connect specific messages with receptive audiences, even tailor product development to meet untapped markets. 

Disciplines 

Data Science

Predicative Modelling

Demand Modelling

The Challenge

Geelong based start-up FormFlow developed a revolutionary bending process for corrugated sheeting. But there was a chink in their go-to-market plan: they didn’t know their customers.

This threw up questions that laddered all the way back to the factory floor: who is the market, what are the drivers of demand and how should FormFlow apply their technology? 

The Solution

Arthur St worked with search data and Google analytics to build FormFlow’s audiences. These data sources, together with data analysis tools, built out the the predictive model.

A number of hypotheses were developed and run through the model, with a number of variables and factors switched in and out to improve accuracy.

The Result

The predictive modelling gave shape to FormFlows future market activity.

This window into the future directed FormFlow’s digital marketing and manufacturing resource: which space within the building industry they targeted and with which product. 

Arthur St conceived and executed highly targeted digital campaigns.

Together with a coordinated earned media push, this generated 300+ leads per month, with a cost per lead of just 80 cents.