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Top tips: Big Data in a mobile world- Shop floor decision making

Retailers are embracing big data, yet there is limited connection between these innovative ideas and the real time experience in each store. Despite clear changes in behaviour and attitudes, the retailer is still second guessing the customer’s expectations.  Matthew Napleton, Marketing Director at Zizo. Explains why retailers need to get real-time data onto the shop floor and into the hands of the decision makers that can make a real difference to both bottom line profitability and customer experience.

Retailers are embracing every aspect of technology innovation in the drive to engage customers in a fast changing environment – from harnessing big data to improve the price/product/placement effectiveness to new in-store experiences that leverage social media. Yet there is limited connection between these innovative ideas and the real time experience in each store.

Instead, from the introduction of iPads to the creation of planograms, retail strategy is implemented from head office, in advance: despite clear changes in behaviour and attitudes, the retailer is still second guessing the customer’s expectations.

Retailers need to get real-time data onto the shop floor and into the hands of the decision makers that can make a real difference to both bottom line profitability and customer experience. As Matthew Napleton, Marketing Director, Zizo confirms, the ability to provide online, actionable analytics via mobile devices into the actual retail environment is transformational.

Customer Experience

When it comes to innovation, retailers are leading way. From stock-free stores to the use of iPads to allow customers to gain validation regarding product choices from Facebook reviews and Tweets, the focus is on creating a unique retail experience. But with consumer behaviour changing faster than at any time in the history of retail, are these innovations simply tinkering at the edge of the customer experience?

The problem with all of these ideas is that they are created at head office and implemented ubiquitously across the retail estate. There is no local input and no way for managers on the shop floor to change activity based on actual customer behaviour in real time. So while customers are offered the chance to check stock via an iPad in store, managers are still wandering around with stacks of paper, Excel spreadsheets and planograms based on information created at head office the day before, or perhaps several days ago.

The limitations of this model are extensive. Why are product promotions treated exactly the same in each store, when performance will differ widely between stores? And it is why it’s still possible for a problem with the pricing system to go unnoticed for over 24 hours – even when Twitter is awash with comments about a £10 case of beer promotion going through the tills at £1? Even when the store was selling out as a result?

Information Constraint

Despite the innovative ideas, most retailers are fundamentally constrained by the continued reliance on relational database (RDBMS) technology that delivers decent operational analytics but nothing more. Instead, retailers rely on an annual exercise of more complex basket analysis to determine store performance by product, by layout, and local demographics. The result? In store activity is based on last year’s performance, not today’s customer behaviour.

This is clearly not sufficient in an era of fast changing consumer behaviour. From showrooming and click & collect to new food buying habits and brand loyalty, consumers are fundamentally changing the way they interact with retailers. Retailers need to change – and fast. That means not only gaining an insight into these critical issues at head office but empowering those on the shop floor to respond in real time. And that means working from the same, single data source – not providing marketing, sales and operations with separate data warehouses; and moving beyond aggregate data to true online analytics that combines both structured and unstructured data sources.

Real-Time Performance

With 15 minute updates on key issues such as product sales, margins, performance against sales targets that day, social media sentiment, even weather forecasts, a department manager can make decisions that deliver serious bottom line value. For example, if a promotion is performing really well – based on up to date figures on both sales and margin – the product manager can decide to extend the promotion for another hour or two. If the sun comes out on what has been a wet summer’s day, the food department manager may order an additional 2,000 prawn sandwiches, rather than roast beef, to exploit the proven shopping habits on hot days.

Alternatively, if menswear is still 2% below its daily sales target at 5pm on a Friday, the General Manager can be on the shop floor, looking at the performance dashboards on a tablet and responding immediately: getting all available staff into that department, actively engaging with customers and undertaking the intense selling that can change profitability in just a few hours of trading. By close, the department has met its sales target. Given the marginality of the retail environment, multiply this up by hundreds of stores and the value of well-targeted activity can make the difference between a good week and a bad one.

Essentially, by mobilising those on the shop floor, decisions regarding the store layout, product performance, the impact of promotions, marketing and TV campaigns are being reviewed and considered continuously – at store level, by the individuals in a position to make the decisions that can make a difference. The more granular the information and the more frequently it is updated, the more successful each manager, each store and each retailer is going to be.

Engaging the Customer

Clearly operational analytics is really important – retailers need to ensure the right products are at the right price, on the right shelf and at the right time. But in this market, retailers need also to improve customer engagement: and the only way to do that is to ensure every part of the business is working together and that includes the shop floor.

Improving the customer experience is not just about innovative concepts. It is about changing the mix of what is in store – not based on yesterdays performance or some annual analysis of store performance and demographics, but as a reflection of actual customer behaviour both in that store and online, via social media, in real-time.

Delivering insight to people on the shop floor will enable them to make the decisions that will truly change the way customers experience that retail environment. By harnessing big data and providing relevant, trusted and up to date information via mobile to the shop floor, retailers move beyond playfully innovative ideas and take the next step in delivering a truly responsive and innovative customer experience.

By Matthew Napleton
Marketing Director
Zizo

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