How to avoid being duped on audience data
Davor Vilusic, Programmatic and Media Operations Director, carsales.com.au and Joint Managing Director, Audience360, explains why you should be vigilant with your targeting.
An advertiser’s intrinsic understanding of its target audience underpins most successful campaigns. It’s a critical understanding that helps define an insight, strategy or channel selection, and which ultimately helps address a marketing challenge.
But the promise of reaching the right audience at the right time is not only clichéd but widely understood as a given. It’s one of the reasons why advertisers default to supposedly targeted and personalised digital channels. The reality is your highly targeted digital media investment is likely not reaching the intended audience. It sounds counterproductive, inefficient and to an extent, deceptive doesn’t it?
According to Nielsen, demographics – the most common form of targeting – is on average delivered at 50% accuracy and is as low as 21% across the 25-34 group1. Based on those stats, it raises questions around how personalized your media investment is. So why is this generally overlooked? Well, because in most instances audience data is perceived as “free”. However, whether disclosed or not, the advertiser is almost certainly paying.
So what are some ways to help ensure audience targeting is what it says on the tin?
Decouple media and data
Decoupling media (inventory) and data (audience targeting) when you transact is one way to gain greater control over investments and understand quality at a more holistic level. This ensures the advertiser has full visibility and understanding of the cost associated with inventory and audience overlay, and of course, the right information to understand if price and value are aligned.
Understand data authenticity
As marketers, we need to be more accountable for the data we’re using – particularly its authenticity – because it’s directly linked to audience quality and accuracy. At its core, targeting means reaching the right audience, so you should have confidence you’re reaching them – not an illusion you are.
The essential components to determine data authenticity and accuracy include understanding where the information comes from, how it’s captured, how recent it is and what signals underpin those audience segments. Demand transparency from your partners so you can make the right decisions.
Locally, the industry and the IAB Data Council are trying to address this through the DataLabel.org initiative, which uses a similar approach to easy to understand ingredient labels on packaged food. The standards will demand data providers submit and regularly update a minimum set of details that will inform segment quality, addressing details such as type, source, recency, provenance and segmentation criteria.
Work with brands that compliment your owned data
There is an abundance of audience data that’s widely available and highly accessible, but in most instances, apart from the audience segment name, it doesn’t provide adequate levels of transparency. Collaborating with brands and leaders in your category and working with them directly on defining your audiences is an effective way to reach the right eyeballs. It lets you do this with confidence around quality and scale – without the need to implement look-a-like methods, which similarly provide little transparency in how they look-a-like.
Ultimately these partners can not only provide confidence in reaching your target audience but also identify those you don’t want to reach and close the loop with measurement beyond media metrics.
So, I challenge you to say ‘No’ to things that sound too good to be true. Say ‘No’ to things that rely on a black box that manufacturers unicorns. Instead, demand the logical level of transparency that enables you to make the right decisions.
Do you think most marketers do this? What else should advertisers look for?
(Source: 1Nielsen DAR Benchmarks, June 2016)