ShareLinkedInTwitterFacebook
Subscribe

Footfall Data & Analytics

Leading COOs use predictive analytics to streamline operations – do you?

Written by Tony Loxton
Apr 7

What if there was a way to predict the future? I’m not talking about seeking the counsel of an incense-toting, Kaftan-wearing seer, but rather, gaining insight via big data that enables you to adapt your operations alongside changes in your supply chain and consumer demand. Put simply, predictive analytics involves harnessing data to equip your operations to meet your consumers’ needs anytime, anywhere. 

Predictive analytics is all about pre-empting consumer behaviour.

This blog from Tibco summaries the practice: “predictive analytics uses statistical modeling and data mining to study recent and historical data, allowing for more accurate forecasting”. In other words, a method that essentially makes big data actionable in day-to-day retail operations. Analysing data, patterns and trends in customer behaviour and identifying product performance can then inform decisions across all aspects of a business – from in-store promotions and inventory, to supply chain management and staffing.

The retailers who’re driving demand and meeting their customer’s needs are those who’ve implemented predictive analytics across their organization. 

By harvesting and then combining data about consumer sentiment and product performance – from multiple sources – they’re able to not only predict, but influence consumer buying behaviour. In turn, they’re that much better at streamlining and optimising their operations in order to deliver upon consumer needs. Consumers are willingly offering up an endless well of data across various sources such as social media, customer loyalty programs, online purchases and the like. When combined with data about your inventory, in-store traffic counters and CRM, for example, you’re able to make data-driven decision to prepare for anticipated behaviour.

When consumer data is coupled with data about your inventory, via the use of RFID (radio frequency identification), for example, you’re able to refine all aspects of your operation.

On their own, operational and shopper data are valuable. When combined and analysed in relation to each other, they’re veritable operations gold. Abel Garcia, director of IT from Levi Strauss, Latin America emphasised the importance of real-time inventory data in predictive analytics in this blog from Apparel: “Technology as an enabler, on its own, doesn’t really do anything. You must effectively integrate RFID into a store’s operations for it to be useful.” RFID is only one way to successfully conduct predictive analytics, but Garcia’s sentiment applies to all data-gathering technology – unless you’re constantly analysing and comparing data from multiple sources, the practice is moot.

As well as better planning for future behaviour, predictive analytics allows retailers to tailor their offering to the individual.

In a market of endless choice, customer experience is fast replacing price as the number one differentiator between brands. This Forbes article points out the fact that: “According to a CEI Survey, 86% of buyers will pay more for a better customer experience. But only 1% of customers feel that vendors consistently meet their expectations.” Predictive analytics plays a pivotal role in providing great customer service and experience. For example, if you’re in the business of selling gas barbeques, and you’re able to tell when a customer bought which model, you’ll be able to send them a coupon or time-sensitive discount around the time that they’ll need a refill gas canister. Or, if you know that there’s a torrential downpour forecast for the next week, you’ll be able to move and strategically place stock of umbrellas and wellies. While these are two very basic examples of how predictive analytics can amplify your offering, they illustrate the fact that if you’re not gathering enough data from enough sources, you’ll have hard time keeping up with competitors who do.

Blix software enables retailers to analyse their in-store foot traffic in order to gain an accurate picture of their customer behaviour and store performance. Find out about Blix Traffic here.

Image credit: 9rules.com

Learn more about Blix Traffic for retail

You might be interested in these