Data modelling

Arkenford use data modelling to extend the life and value of your research.

Whether you need a better understanding of your customer base, or a better predictive framework to power your future strategy, we can develop a solution customised to your business.

Our approach to creating useful market models is a combination of economy, practicality and technical accuracy. Whenever we can we will use previously collected survey data and other sources of information to reduce the costs of primary research.

Examples of Arkenford's work include a range of customised audience prediction models for:

• the outdoor advertising industry (which have become definitive currencies for these sectors).
• global marketing strategies to drive new IPTV services
• predicting demand for Nintendo products

Our models extend the life of market research to allow you to examine future trends and 'what if' strategies.

TRAC

Arkenford's audience reporting solution for CBS' estate on the London Underground was called TRAC. It was entirely built using secondary data sources including the ongoing passenger surveys carried out by DLR and LUL. As a result, it was based on a vast database of regularly updated journey and passenger information and could be maintained without recourse to new primary research.

The system, accredited by POSTAR the outdoor industry joint committee, included an intuitive interface which could be used to construct packages of poster sites for specific clients or events, or to evaluate existing packages to test their effectiveness.

Game Developers Tool

We have used our gamer database games database to create a tool that allows developers to predict where yet to be completed titles will sit in the market, which games will be their greatest competitors and which groups are most likely to be interested in the game.

AdRail

Our solution for the surface rail network was called AdRail. It was developed using a range of data sources including ticket sales, station traffic counts, network and internal station routing algorithms and the National Travel Survey. The model provided data for the impact of the advertising estate in over 600 stations across the country for all kinds of rail users and station visitors.