Australia’s retail sector continues to face competition from online, overseas retailers, while consumers are increasingly digitally savvy. Retailers can use data analytics to deliver insights that will help them overcome these challenges, encouraging customer loyalty and increased spend.

Teradata has identified five ways that data analytics will influence the retail sector in 2015:

1. The rise of omni-channel retailing

Online channels have become incredibly popular but that doesn’t mean consumers always prefer to buy online. An omni-channel approach means creating a shopping experience that lets customers interact with the retailer in a variety of ways, seamlessly. For example, a customer may begin researching a product online, seek more information via a mobile app, and then complete their purchase in a bricks-and-mortar store. Facilitating this process in a frictionless manner is likely to result in increased sales and customer loyalty.

To achieve this, many retailers need to go back to basics to ensure that their supply chain is reliable and well-managed. Stock levels and delivery times displayed on the retailer’s website must be accurate to ensure a high-quality customer experience.

Geoff Andrews, ANZ general manager retail, Teradata said, “Organisations must continue to monitor and fine-tune their omni-channel approach. The marketplace and customer requirements are always changing, as is the technology and data used to inform the channels. Retailers must adjust as necessary to ensure the customer experience is consistent.”

2. Using analytics to personalise the shopping experience

Big data combined with strong analytics means businesses can see exactly where their profits come from, for example, online or in-store. This shows retailers where they should invest the most time and effort with marketing campaigns.

Traditional reporting and business intelligence tools enabled retailers to personalise the shopping experience to a degree. Big data analytics takes it to the next level, letting retailers see exactly how to target potential customers in a way that will resonate with them and encourage them to purchase.

Geoff Andrews, said, “Consumers expect a high level of personalisation. Basing special offers and targeted communications on previous customer behaviour is a reliable way to increase revenue.”

3. Increasing the focus on loyalty

There is a focus on customer loyalty as evidenced by the increasing of chief loyalty officers that report to the CEO. The role’s purpose is two-fold: to improve customer loyalty through programs and promotions; and to protect the customer by making sure their data remains secure and their privacy is respected.

Geoff Andrews said, “There is heightened sensitivity around customer-centricity and businesses must respect their customers’ data and privacy. Consumers are well-informed about privacy issues, making it harder for organisations to win and maintain customer loyalty and trust. Organisations that breach the consumer’s trust, lose.”

4. Optimising the effectiveness of promotions

As a general rule of thumb, only approximately 15 per cent of promotions are successful and marketers only know which 15 per cent that was after the event. The ultimate aim for retail marketers is to understand in advance what will work and drive business. This means marketers must rely less on instinct when trying to predict the future and more on historical facts. Collecting and analysing data about past consumer behaviour will generate insights that enable more accurate predictions about which promotions are likely to work and when.  

Geoff Andrews said, “There is no magic bullet that lets retail marketers predict the future. Instead, they must be disciplined and consistent about repeating the analytics process regularly. This is the only way to continually improve the accuracy of the insights and the quality of decision-making.”

5. Optimising inventory

Retailers have always had to find the balance between holding too much inventory, which incurs costs, and holding too little, which can result in lost sales. Using big data insights to forecast planning and replenishment means retailers can find this balance more consistently. Inventory is a retailer’s largest asset, and it requires constant attention and optimisation to ensure capital is expended in the right products, at the right time, and in the right quantities.

Geoff Andrews said, “If a retailer introduces a new product or marketing campaign, they need to be prepared to fulfil the orders that come through as a result. This means using data related to past campaigns, similar products and other buyer behaviour to more accurately plan for the anticipated demand.”