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Retail (im)maturity and analytics systems

Data is currency in retail today, but it’s not enough to simply invest in solutions to store and analyse data. If retailers do not cultivate a data-driven mindset throughout their business, they might as well be making decisions blind.  

If there was any doubt about the need to go ‘all in’ on the use of data within modern business, then retail conglomerate Wesfarmers’ $230 million purchase of Catch Group –  now the country’s largest online retailer with over 1.5 million customers and 2 million SKUs – should remove any apprehension.

Wesfarmers wants to take advantage of Catch’s leading technology and data capabilities, which will be leveraged to grow and accelerate consumer-driven, omnichannel initiatives across its department stores Kmart and Target. If it’s good enough for one of Australia’s largest retail groups to focus on how it effectively uses data analytics, then other retail concerns should probably take notice.

“A major reason why businesses fail to fully capture the value out of their initiatives is that they fail to recognise that deriving value from data is a team sport,” says Poplin Data’s chief strategy officer Soohan Kim.

“That is, programs require tight collaboration across multiple functions, and organisations traditionally have not been good at doing this.” 

Poplin has been a key partner with Catch over the last two years, now counting a host of businesses including The Iconic,, CarsGuide and Fairfax as clients.

To derive value out of a data initiative, Kim says it generally takes IT to capture, store and organise data; analysts to explore and analyse data to create insights; management to interpret the insights and make data-based decisions; and finally for the business as a whole to action the decisions in a timely manner.

“Any weak link in this chain means that value won’t actually be created,” says Kim. “This includes when a business is great at deriving insights and making data-based decisions but may need some restructuring in order to execute effectively. Alternatively, if the data is not captured and stored effectively by IT, none of the downstream functions can be done. This is also why senior sponsorship is needed.”

New tech, old problems

Despite all the new technology and buzz around being data-driven, the goals of a business and the questions that executives ask remain the same. Businesses are wanting to understand customer behaviour and trying to personalise their services to best serve customer needs, yet still need to ask and answer the same old questions:

  • Who are our most valuable customers?
  • What are my most important products?
  • What are my best performing channels?
  • Who are my most effective employees?

Traditional retailing once revolved around local, owned-and-operated stores where the owner had direct face-to-face interaction with customers. Long-term, community-based relationships with customers and specialised stores, including butchers and grocers, dominated the shopping environment, and owners met and understood their customers’ needs.

Modern retail has since moved from store to super-sized organisations, with decision-making removed from front-lines and instead corporatised. Now, wandering and ever-changing customer-bases, one-stop shopping destinations and massive product selections are a stark contrast to traditional forms of business. As the decision-makers don’t interact with the customers directly, they lack the data to personalise their services.

More recently, retail has also moved to online, where the imperative is not only to personalise, but do so in real-time, says Kim.

And when it comes to data and analytics, Kim thinks we’re actually just trying to reproduce the personalised feel and experience of older forms of retailing. Except now, because of the changes in consumer behaviour, competitive landscape, business models, data and technology, businesses have to achieve this customer experience via different means.

Data and analytics is equally important across all types of retail firms, whether they be online or offline.

“The value-add that data and analytics can provide in pricing, logistics, merchandising and marketing are all tremendous, and has been proven by leading retailers,” says Kim.

“One point of difference it that granular data, especially customer behaviour data, is more accessible for e-commerce stores. For example, it is much easier to measure store visits and product views online, via web traffic and clickstream data, than it is offline, where you would need to capture foot traffic and try to measure where customers stopped to inspect products.”

Kim mentions that marketing attribution is still equally difficult, especially as a customer journey, more often than not, crosses over between offline and online, and perhaps multiple times.

Eyes on the future

IDC research has predicted the global datasphere will have grown from 33 zettabytes in 2018 to 175 by 2025 – with nearly 30 per cent of the world’s data requiring real-time processing.

Kim says data should be treated as a strategic asset and as a source of insight, not an administrative burden. 

“That means getting systems, technology and processes in place, right from the start, that ensure data is collected, stored and shared correctly. We [Poplin] view data as a communication stream and a shared service within a company — so that everyone has access to the data, the analysis, and the same systems.”

Kim adds that when point-of-sales systems and barcode scanners were introduced, it gave rise to business intelligence and transformed the retail industry entirely through the 1980s and 90s. 

“Big data and analytics technologies is the next evolution and will be just as transformative, and the businesses that are able to utilise these new technologies and techniques will be well-placed to capitalise on the new opportunities that will be created.”

Learn more about retailers now understanding how the different stages of analytics maturity can help get them to the next level at

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