Q&A with Martyn Bentley, Commercial Director UK, Audience Project

We caught up with Martyn Bentley, Commercial Director UK for Audience Project, ahead of his participation at the Audience Analytics & Insights Conference this October.

AAI: Why is it that more data can lead to fewer insights?

MB: The quality of data output is completely aligned with the quality and to some degree the quantity of data that comes in. If the data quality is too low, then more data does not help, and you will just spend more time trying to understand it and still get crap out.

Additionally, greater amounts of data could lead to worse output, as it will place greater demands on the skill of the data scientist crunching the data.

AAI: Where should analytic & insight teams sit within the business structure?

MB: Close to the money! Just look at how technology and data are giving sports-stars the edge – it’s never been more important in helping business perform at its full potential. 

AAI: Why is it important to break down the silos between data teams and insight teams?

MB: I think it is important so that the data that is supplied to the insight team, will actually be useful to them and solve problems they set out to solve. 

It is, in the end, two sides of the same coin and is 100% a team effort; data teams have the capabilities to crunch the data – Insights teams have the capabilities to structure the data.

AAI: As an industry are we losing the art of interpreting human motivation?

MB: There is a danger of reducing human motivation to sale-able data packages. Human motivation is, I think, well understood at some points in the advertising chain (perhaps at the creative agencies) – but it’s often not aligned with how audiences are sold and targeted – e.g. the creative teams and their insight partners build complex audience personas, which are not targetable in digital other than by proxy data sets. It’s a disconnect that could be reduced by more through-the-chain collaboration.

At AudienceProject and other reputable data companies, human motivation is interpreted through the (machine-led) study of behavioural data – this is then fused with deterministic data, to grow accurate segments – and we also safety-check the segment’s but using a proportion of the deterministic seed to ensure we are hitting the correctly motivated people.

AAI: GDPR should mean cleaner better data – has it?

MB: I think it’s too early to say. What it has done is got the market thinking about cleaner better data and best practice… which can only be a good thing.

AAI: If AI and machine learning could deliver one improved solution to help your understanding and targeting of your audience, what would it be?

MB: True cross-platform measurement! Enhanced cross-media planning and attribution is a highly desired outcome for everyone in the market. Whether AI could definitely solve it remains to be seen – because the data inputs also need to be very high quality, standards need to be agreed between stakeholders and some very large platforms don’t even allow measurement!

I doubt AI can solve this perfectly but it may be able to be deployed to improve the estimates in the interim.

AAI: Blockchain, could it be the answer to all advertisers’ problems, 100% accurate behavioural data or just the next new shiny thing?

MB: Shiny thing in its present form and capabilities. It has some highly interesting potential and as a technology can provide some of the answers to the problems of the industry, but not all. 

AAI: What’s the biggest single challenge that impedes the successful integration of behavioural and survey data?

MB: Ensuring that the behavioural data is high quality, and transparent – and if possible the mix-level (or dilution of the deterministic data set) of the two types of data should be stated.  Otherwise behavioural data can be used fast and loose by players looking to create scale at the expense of accuracy.

AAI: Why is it important for brands and their agencies to be able to compare online and offline audience and advertising data more effectively?

MB: Because understanding cross-channel attribution is an important key to media effectiveness and thus lowering the cost of sale/increasing margin. It will reduce wastage.  It’s that simple.

AAI: Can you sum up the holy grail of total advertising attribution in one sentence?

MB: The holy grail is to be able to understand the consumer’s need states and motivations, and influence them, cross-channel, in the most efficient way possible.

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