Kiwis are expanding their engagement across different sized screens and media platforms for entertainment, information, commercial and communications activities; for marketers it's all about keeping up with - and in many cases, staying ahead of - these consumers.
Ad spend remains one of the biggest and most strategic resource allocation decisions that the management of any leading consumer marketing company has to make. $2.3b was spent in the advertising industry in 2013 (Advertising Standards Authority), the biggest figure since 2008. However, the speed of change in the world of media and advertising is creating new uncertainties in the executive suite. The good news is that rules have not changed and the questions to be answered remain the same: What do I need to spend in each medium to make sure I get the reach I want? How do I allocate that spend within each medium? And how do I know if it's working well enough? Similarly, the basic question for advertising effectiveness has not changed: the more your ideal audience you can reach, and the more intensely your advertising resonates with them, the stronger your brand lift or sales lift - or reaction. Essentially, reach x resonance = reaction.
We are in a shifting landscape with increasingly fragmented media. Accessing content now means different things to individual consumers, in addition to traditional media formats and devices there are now choices about accessing through smart TVs, computers, tablets, smartphones and so on. This technology driven explosion of marketing channels has made marketers task more elaborate, in terms of media planning for optimal reach and measuring advertising effectiveness across multiple platforms. How do you identify unduplicated reach? Or, if you want to increase frequency, what's the best way to create duplicated reach?
Looking ahead we see a number of new tools and technologies to use in advertising to help make smarter decisions.
Predictive modelling is mix modelling on steroids. Traditional mix modelling optimises allocation of marketing spend across media to generate maximum lift. But it has always been primarily historical: you analyse the previous campaign’s results and adjust accordingly. Now with the richness and depth of available data from Big Data – higher volume, and the computing power to process it, will allow you to run simulations to predict the output of any marketing mix scenario.
In the NZ market, we’ve used consumer-based reach planning for media campaigns but more recently, a rich array of buyer based reach planning (buyergraphics) have become available. Buyergraphics allow an advertiser to identify more precisely the segments that buy most heavily, understand the segments of buyer behaviour and understand what drives these segments in terms of attitudes and lifestyle. In turn, the advertiser can create a more targeted media campaigned to improve ROI.
This is not entirely new but what’s different today and being done abroad, is that real time data on consumer response on which to base optimisation decisions. Effectively, you can conduct real-time experiments to make the best possible decisions using your newest and most informed thinking every step of the way. In the past changing creative might have been based on a ‘wear out’ rule of thumb. An online campaign provides the opportunity to change direction and creative mid flight. The infrastructure behind the delivery of online ads allows your algorithm to measure performance by creative unit, site, exposure frequency and even audience type and make adjustments to change where your ad plays instantly.