How Superbalist succeeds in targeting its customers almost individually
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Listen to the audio below (or scroll down for a summary of it).
Superbalist is the largest online fashion retailer in South Africa.
It offers hundreds of brands with various payment options as well as effective delivery and returns.
Superbalist is known for quickly introducing new, on-trend ranges.
The company has a “programmatic” approach to marketing.
It does not merely target ads on Facebook and Google to reach a certain demographic but tries to reach specific customers within a particular context.
Programmatic targeting doesn’t care about demographics; it cares about behaviour.
The end-game is that you start targeting segments then sub-segments then, ultimately, one-to-one… We call it the ‘single customer view’… We are constantly endeavouring to store as many unique fields of data against a user as possible… Right now there’s a survey on Superbalist. It’s got about 45 000 respondents in the last 30 days…Luke Jedeikin, co-CEO - Superbalist (speaking at an "Absa Insights" event)
Superbalist then splits its data into three “silos”:
Transactional data (what, when and how much they’re buying, on what platform they’re buying, etc.)
Psychographic data (tastes, favourite influencer, media interests, etc.)
Superbalist uses machine learning to predict what its customers will buy, thereby going even further than one-one-one targeting using the “single customer view” it has.
…A segment might be a tiny part of our business today, but we can forecast if it will become a material part of it one day. Then we target and chase it down…Luke Jedeikin, co-CEO - Superbalist (speaking at an "Absa Insights" event)
[Watch] Luke Jedeikin explains in detail how Superbalists targets customers one-one-one and how it uses machine learning to forecast their future behaviour.
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