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Fashion retailer, Karen Millen is using personalised retargeting to drive campaign conversion and sales online

Fashion retailer, Karen Millen is using personalised retargeting to drive campaign conversion and sales online

Karen Millen websitePersonalised retargeting from provider myThings optimises ads according to the users’ prior shopping experience and targets visitors after they leave the retailer’s website, turning lost prospects into buyers.

 

Emma Bonar, Karen Millen e-commerce manager told Retail Technology magazine (Nov/Dec 2010) that the myThings cost per action (CPA) business model had proved a success since it was implemented in April.

 

The CPA business model results in myThings serving fewer, more targeted ads because serving too many ads will annoy users, resulting in lost revenue for the publishers and brand damage for the retailing advertisers. And myThings provides users with a control option courtesy of the opt-out link featured in every single ad.

 

Sensitive to customer's brand passion

 

“We have to be quite careful about our customers’ passion for the brand, where they can see advertising to them as quite a personal thing,” said Bonar. “But it feels like it’s been converting well and we’ve had no negative feedback. I also like the fact that I can change creative on the fly.”

 

Though online advertising has long provided the promise of unlimited targeting opportunities in order to most effectively match the user’s needs, in reality, most online display ad campaigns are limited to three or four creative implementations.

 

With the same sophistication of a search engine marketing campaign, where thousands of key words are optimised across hundreds of ad texts, myThings recently also introduced its Adaptive Banner technology to the UK. Adaptive Banner is designed to enable the implementation of an unlimited number of personalised retargeted creative implementations, resulting in a significant increase in conversions versus other retargeting solution providers.

 

The myThings’ proprietary machine-learning technology monitors ad performance per publisher, placement, days or time of day, frequency, and adapts the creative variations in order to maximise conversions.