Retail is being continually reimagined to attract and retain profitable customers. With new economic pressures and heightened customer expectations, there is limited leeway for mistakes. Businesses can no longer afford to risk costly and long-winded trial and error in the real world, especially when it comes to sustainability and waste.
There is, fortunately, a better way – using data and advanced analytics to rapidly test potential scenarios. Yet while retailers routinely capture all the data required to assess new business ideas, it is locked up in point solutions. In order to make sure retailers only adopt proven innovations, a smart, cloud-based model is needed that integrates cross-business data assets with analytics and visualisation tools.
Only by building a platform for continuous, data driven improvement, can retailers reduce the risk and cost of innovation, explains Andrew Bithell, Senior Account Manager, CTS.
Successful retailers are distinctive. Many retailers share core operational goals, such as driving sustainability, creating efficiencies, being more customer-centric, revenue growth and even reimagining store estates. But the way these goals are achieved will be what sets retailers apart and creates a competitive advantage.
One retailer may aim to reduce waste by looking at local demand patterns to provide hyper-personalised ranges in different stores. Another may need to prioritise supply chain optimisation to reduce the costs associated with transport delay. Whereas yet another will explore the value of turning high street stores into mini-fulfilment centres, encouraging customers to collect items in store to drive down delivery costs.
With so many areas of improvement and so many different potential models, how can retailers prioritise areas of change and implement their new plans without incurring significant risk? Where is the proof that the investment needed to turn a store into a distribution hub is going to pay off? Or that a commitment to sustainable operations will realise benefits in both reduced wastage and improved stakeholder perception? Innovation is vital but given the pressure on profitability, there is no room for expensive mistakes.
Unlocking Retail Intelligence
How can retailers innovate without incurring unacceptable cost or risk? To successfully achieve the ‘what next?’ requires not just innovative spirit but proof. Clearly such decisions have to be data led, and given the routine creation of billions of data points about customers and assets, retailers are better placed than many sectors to drive change. Yet while retailers are awash with information about products and stores from websites, mobile apps, warehouses, vehicles, fridges, even smart shelves, too much data is buried in siloed operational systems.
From EPOS to Merchandising to Supply Chain Management and Customer Personalisation, retailers have an array of powerful operational systems that are delivering new levels of efficiency and control. But each system has its own data set which leads to both duplication and inconsistency, making it
hard to create or trust a 360-degree view of the business. The processes used to integrate and store the same data across multiple applications – where that is even possible – add both cost and complexity.
Yet every single area of innovation and retail change demands a cross-business perspective. Let’s consider in store supermarket picking. Today, the process is far too reliant on the whim of individual pickers – something that can cause no end of issues, and may become particularly problematic in a time of short supplies.
If, for example, there are only 100 bottles of champagne left, should they be sold to the customers already in the store or those who have already ordered a bottle online? Or further prioritise those with a regular basket that always includes champagne?
It is important to combine ordering information, inventory – whether it is on the shelf, in the back or on route to the store – plus customer history and orders to ensure picking is optimised at all times, even during a global pandemic or Suez Canal blockage, for example. The result is not only better customer service but a far more consistent approach.
Point solutions cannot support retail innovation individually because they only have a partial fingerprint of the overall data required. Combining multiple, diverse datasets in an agile cloud environment provides an abstracted layer unconstrained by the usual feature availability and release management issues experienced with point solutions. This abstracted layer is therefore more flexible when considering testing and incorporating new hypotheses or capabilities. At the same time, the cost of such innovation is reduced and more transparent, enabling retailers to adopt a razor-sharp focus on ROI. Retailers need to use all the data they have, combine it, augment it and enrich it. This will help to rapidly understand just how and where innovation and retail reimagining should occur.
Combining cloud computing with the latest analytics tools completely transforms the innovation process by providing retailers with a way to quickly build intelligence that can be shared with both people and systems. With a single source of cross-business data, retailers can use advanced analytical capabilities to explore the potential of an array of business ideas. They can even take advantage of pre-built analytics recommendation engines to prompt innovative thinking. These enriched data sets can transform business understanding, uncover insights, add intelligence, visualise trends, group and segment customers – whatever a retailer requires to drive its unique business outcomes. For example, using Google’s Recommendation AI for personalised and real-time recommendations, Ikea delivered a 30% increase in click through rates and 400% rise in relevant content put in front of prospective customers.
With a fast, effective way to test a hypothesis, a retailer will never move a use case into production that doesn’t deliver business ROI. And this is just the start. By creating a framework to quickly and definitively measure whether ideas and hypotheses are going to deliver any value to the business, a retailer now has a methodology for continuous improvement. Indeed, this is an environment that allows retailers to deliver not just one use case after another, but multiple use cases simultaneously to create a truly data-driven business.
Retail reimagining is not just a priority but is also incredibly exciting. Innovative retailers are set to buck the economic trends as they evolve from store and category-based insight to a new level of granular insight that can look at an individual SKU, by store, by day. And whether the priority is increasing sales, decreasing waste, optimising the supply chain or enticing a new customer base with a phenomenal experience, granular data will transform the accuracy of both predictions and insights.
There is no doubt that the essence of retailing – attracting customers, converting them into customers and reducing cost of sale – and operational goals remain the same. But the ones that can unlock the value that lies in their data will thrive, while others fail. By building an ecosystem for change, retailers can capture and deliver unique retail success.