Courtney Connell, marketing director at Cosabella, explained to Ad Exchanger that all marketers have to do is enter top-level parameters – like geographies, channels and target audiences – into Albert, the name of the chosen AI engine, and then set a budget and KPIs around return on adspend.
"After that, [Albert] makes every single decision," Connell said, from identifying targets and keywords and allocating budgets between channels to controlling bids and executing buys.
The results cited make a seemingly incontrovertible case for machine learning. In the first three months of this operation, Cosabella reported a 336% increase in return on ad spend.
On Facebook alone, return on ad spend was up 565% within Albert's first month, while by the end of third month, Albert had increased conversions on the social media giant by 2,000%.
Further, revenues increased 155% in the last quarter of 2016 while the brand registered 1,500 more transactions year over year, 30% of which came from new customers.
"All of the big idea, strategy and campaign creative is happening in-house," Connell added, with her existing team supplying images and copy that Albert serves dynamically.
"He can mix and match [creative] however he pleases," she said. "He might start with an ad and if he sees that getting fatigued, he might roll out a new combination."
The next step will be to link Albert to Cosabella's CRM system to enable him to "model high- or low-value customers and adjust his budgets to spend more to attain a certain customer".
Connell also valued the AI engine's reporting abilities. "He [Albert] knows that he's shown someone a Facebook ad or if they click on a search ad and make a purchase. He gives you reports on assists versus actual sales so you can see how the channels work together to get the customer to make a purchase.
"There's nothing I miss about advertising agencies," she concluded.
Data sourced from Ad Exchanger; additional content by Warc staff