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Lookalike modelling: the ad industry technique demystified | Media Network | The Guardian

“Through the DIGICOM platform, we were able to generate north of HK$600,000 in revenue and 1600+ sales at a ROAS of 10+ during one single quarter; through programmatic advertising and creative targeting Strategy” This is the compliment from our client on programmatic advertising, Hong Kong Rugby Union.

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Programmatic Advertising is good at generating both brand awareness and conversions. The prevailing trend among traditional and digital marketers are to understand the operation / execution sides and nuts and bolts of the for realistic planning strategy, better communication with vendors or inhouse execution of marketing campaigns for faster market response and better safeguard of your audience big data.

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This is a very complex process, demanding rigorous methodology and huge amounts of computational power, but the end result is hugely advantageous: find people who behave in the same way as your customers, but who haven’t bought your product yet.

 

So what does a lookalike model actually look like? Say a washing machine manufacturer is having a sale and wants to encourage online purchases. We’d place a pixel on the sale confirmation page and analyse the behaviour that purchasers have undertaken elsewhere on the web (completely anonymously, of course). This group is analysed in order to reveal online behaviours that rank most highly amongst people with a propensity to buy washing machines.

 

Lookalike modelling is critical in programmatic buying – it’s the methodology advertisers use to define the users they’re after on ad exchanges. Yet there’s a distinct lack of transparency about how it’s done, consequently, it’s an area often least understood by buyers and owners.

 

This is particularly true in media planning and buying where technology and automation (aka ‘programmatic buying’) is burgeoning. So, I’ll aim to demystify the science behind one crucial approach in this field – the ‘lookalike’ model.

 

Marketers are bombarded with a bewildering amount of technology and science purporting to help them advertise more effectively. Whilst many of these may help there’s little doubt it’s harder for marketers to ‘look under the hood’ to assess whether these really deliver the right audiences they claim to.

 

 

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