Sep 20 2012

Audience Efficiency: Why you can’t beat the model


Audience Efficiency: Why you can’t beat the model

This discussion on audience efficiency is also complete. We’ve shared key findings about 3rd party data, looked at variations between industries and brands and finally, at why audience overlap matters. In the fifth and final part of this series, we’ll look at why, in terms of combining lift and reach, “you can’t beat the model”.

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Aug 31 2012

Audience Efficiency: Why Overlap Matters


Audience Efficiency: Why Overlap Matters

Earlier on this blog and through admonsters, we’ve introduced the idea of audience efficiency, shared key findings about 3rd party data and spoken about the variations between industries and brands. In the fourth part of this audience efficiency series, I want to look at some of the limitations of this methodology primarily because overlap matters.

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Aug 15 2012

Audience Efficiency: Variations Between Industries and Brands


Audience Efficiency: Variations Between Industries and Brands

We introduced the notion of audience efficiency earlier in the year at AdMonsters London Ops and followed this up by sharing some key-findings about 3rd party data from more than 200 client studies. Now, we’ve moved on to look at audience efficiency across industries and brands as not all audience efficiencies are equal.

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Aug 15 2012

Efficacité publicitaire : Variations entre Industries et Marques


Efficacité publicitaire : Variations entre Industries et Marques

Nous avons présenté la notion d’efficacité publicitaire plus tôt cette année à AdMonsters London Ops et l’avons suivie en donnant quelques ssolutions clés concernant les third party data effectuées dans plus de 200 études clients.. Actuellement, nous observons l’efficacité publicitaire des industries et des marques sachant que chaque efficacité publicitaire est différente des autres.

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May 15 2012

How to use different audience types in online advertising campaign planning


How to use different audience types in online advertising campaign planning

I am often asked how the different audience types (such as retargeting, in-market, interest and offline socio-demographic or purchase data, etc) fit together for campaign planning and what we should recommend to clients. Either through our Insights Services or Deep Dive (our audience discovery application), we are able to show clients the most statistically relevant audiences for their campaign and answer that question quantatively. But is there a simple framework to think about this before you delve into the numbers? We think so.

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