The data scientist: Retail’s new superhero

Once upon a time, a trip to the supermarket left nothing behind other than the enjoyable experience of chatting with the shopkeeper and a few spaces on the shelf.

These days, customers are regularly leaving behind a trail of detailed information. There’s their e-tag record from the toll roads driving to the store, the cell towers the mobile phone is connected to, the image of their car’s number plate captured coming in and out of the carpark and every item bought at the grocery store, as well as the loyalty card and debit credit used at the self-checkout.

Retailers are now swimming in an ocean of information and face the challenge of analysing the different sets of data and being able to properly understand it.

“It used to be very simple from a volume perspective for retailers, but nowadays they can get store-by-store-level data from their internal sources or even more granular level data, [from places] like a point of sale provider, card providers and EFTPOS data. If they’re looking at media data, they’re getting even more granular and both television, internet usage data,” explains data scientist Tom Doolan at IRI.

“Being able to align those data sets to get a meaningful picture of both of those own performance and their direct competitors is one of the biggest challenges.”

Enter data scientists, a new breed of analysts at IRI who can help retailers filter through the information required to intimately understand their customers’ behaviour and from there, make informed decisions around where the business goes next.

By using data profiling, data scientists can decipher transactional information, evaluate meta data, determine consistency and work out whether the data is “fit for purpose”.

Data scientists at IRI also use information gleaned from the business’s Shopper Panel, which is made up of more than 10,000 households around Australia. According to Doolan, each household is given an in-home scanner or app to help them collect all their purchasing behaviour, similar to what is used at self-checkouts.

“The average tenure [of each household] is at least three years, so we get a longitudinal view of what their purchasing behaviour is like and the data is projected to be representative of all households in Australia,” he explains.

“We can get an understanding not only of what they’re buying but who’s buying it, their repertoire of what they’re purchasing, the mix of brands as well as the motivation for that purchases.”

Doolan adds the Shopper Panel also helps IRI’s clients to understand where else their customers are shopping and what percentage of their grocery baskets have been purchased within their store.

The panel can also help retailers with new product development. For example, a retailer can view the gluten-free shoppers on the panel, look across the categories and consider the gaps in their current product range.

The data can also be used to assist retailers in the process of rationalising within a category, adds Doolan. A retailer may incorporate the shopper data in their decision-making process in regards to potentially getting rid of item. They might look at the sales and think it best to delete the product, but when they view the shopper data, although the item isn’t making many sales, there is nowhere else for shoppers to buy that particular item.

Indeed, without the help of data scientists, retailers are only be able to scratch the surface of the information they could glean from their customers and potentially miss out on great opportunities for their business.

If you’re interested in learning more about IRI’s data scientists, please click here.

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