New: Audience Research meets Big Data

A new IPA report, "The Big Opportunity - Audience Research meets Big Data" is published today (20th June 2013) and considers how the industry can make best use of Big Data. Free to download from this page.

27/06/2013

Big Data is currently dominating research discussion. With server data, social media, rich customer databases and Return Path Data, Big Data provides an exciting opportunity to take media research to the next level. ‘Big Data’ is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

The trend to larger data sets is due to the additional information derivable from a single large set of related data, rather than separate smaller sets with the same total amount of data, allowing correlations to be found to spot business trends and determine quality of research.

A new IPA report, being published on 20th June 2013 – The Big Opportunity-Audience Research meets Big Data – discusses Big Data specifically in the context of audience measurement. It offers the industry a balanced view of how to make the most effective use of these new data sets as well as looking at the implications for agencies, advertisers, media owners and industry media currencies.

This report makes clear that in the context of media research and audience measurement, Big Data constitutes a revolution in terms of the accountability it provides and the skill sets demanded of the people producing it.

The Big Picture:

• Big Data – from servers, ISPs, customer databases, social media or Return Path Data – can greatly enhance industry currencies.

• However, the growing availability of Big Data does not remove the need for independent and transparent audience-centric data that gives a bigger contextual picture of the market as a whole functioning as a jumping off point into proprietary datasets.

• Survey data, such as that produced by TouchPoints, can enhance Big Data sets and vice versa.

• One of the key strengths of Big Data is its granularity – the census nature of the data delivers a closer look at online consumer behaviour and media usage than ever before.

• The ability to make small things clearer - the granularity of small data - is a game changer in an increasingly fragmented world.

Big Data – The strengths:

• Big Data provides highly granular passive measurement of behaviour , at low cost and at speed: ‘volume, velocity, variety and veracity’

• Big Data, because it is collected passively, is potentially of a more granular and in-depth nature both in terms of the amount and detail of information a respondent is willing/able to give compared to a recall interview.

• Allows far more detailed measurement of long tail digital consumption.

• Opportunity for instant – or close to it – feedback on behaviour/consumption

• Data collected as a side product of behaviour– ‘Digital Exhaust’ – can be far cheaper than a bespoke survey

• Server or Return Path Data, if correctly filtered and verified provides a passive measure of exposure. Overlaid with purchase data, the ability to see how one form of behaviour – media exposure – has influenced consumption – is a quantum leap for media planning and ROI.

Big Data – The weaknesses:

• The vast majority of Big Data sources measure devices not people

• Typically, the size of the data set will be in inverse proportion to the amount of demographics appended.

• Some supporters of Big Data argue that the ‘what’ is all that is needed and that statistically analyzing the ‘what’ will indicate the ‘why’ – motivations – through correlations and pattern recognition. But, this approach can run the risk of seeing correlations or patterns that aren’t there.

• Big Data typically measures the final act – many media campaigns are as much about changing attitudes and consideration as short term purchase. Thus, there is always a need for attitudinal data to compliment audience measurement as opposed to just purchase behaviour data.

• It is dangerous to assume that big automatically means beautiful, that the most important characteristic of a sample is simply its size.

• Big Data sets tend to be proprietary which means that they can often be difficult and costly to access

• If Big Data is seen as ‘oil’ then it still needs refining – you wouldn’t put crude oil in your car!

About Industry Surveys:

• Industry surveys are the agreed media trading currency which means, as a result, they are transparent in methodologies, giving reassurance as to the quality and representativeness of the data.

• They have balanced representative samples – sometimes small, but perfectly formed!

• Data is available to all – which is not the case for Big Data – which, whilst cheaper to produce is usually commercially owned and therefore, less transparent.

• As they are survey based, the industry surveys do have extensive demographics at an individual level. Demographics are rarely available in Big Data – which amplifies the continuing need for industry surveys.

• Industry surveys provide detailed feedback on the performance of a particular piece of advertising or content but also on the wider context.

• The key challenge for Big Data in this instance is that it can typically represent a part of the picture, but not the whole.

Summary:

Survey data can be enriched by incorporating Big Data to allow more granular measurement, which will provide a total market context for that Big Data. Meanwhile, demographics are another way in which survey data can enrich and enhance Big Data. It could be argued that without detailed demographics many Big Data sets aren’t able to provide the full picture in living colour. However, one thing the IPA report makes clear is that the market research industry is going to change.

Says Richard Marks, the author of the IPA report; “Greater in-house research and analytical skills will be needed to guide the selection and interpretation of the data sets available - the client analyst as personal shopper, ensuring budgets are allocated to the most relevant and reliable datasets. Meanwhile the balance of research agency expertise will adjust to incorporate a higher degree of data curation as opposed to just data creation. In order to maximize the opportunities presented by both Big Data and industry audience services, the skilled data purchaser and user - the ‘data shopper’ - needs to be asking the right questions”.

To download the full report for free, click here



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