The use of artificial intelligence (AI) within retail has undoubtedly grown, not just for large market-leading retailers, but for retailers of all shapes and sizes across many sectors. Yet, despite the progress that has been made, some retailers have not yet recognised the true potential of AI.
It is these retailers that need to ask themselves: what do we want to achieve with AI? What can AI really deliver – and what will this mean for our customers? Retailers need to leverage AI to its full potential – from the warehouse to the store – in order to deliver a consistent customer experience every time.
Adding value with AI
Online, in store, in the warehouse, the opportunities to leverage AI and machine learning (ML) to improve retail operations are compelling – no wonder research predicts that retailers will spend $15.3 billion on AI by 2025, $8 billion more than initially forecasted by the end of 2022. However, before AI can be truly effective in the sector, the challenges of data quality and quantity must first be addressed.
Data is essential to both effective AI and ML, but often in the rush to embrace innovation, it is easy to overlook the associated data challenges and end up with something that neither improves ROI nor the customer experience. Even with the volumes of data currently captured by many retailers, they often still struggle with processing enough quality data, to take full advantage of the benefits AI can deliver.
What the new DCMS National Data Strategy means for businesses
Take, for example, an amazing AI solution in store that gathers information about a customer – such as hair colour/type and skin tone, size and style – to recommend products, from hair styling to make-up, fashion to accessories.
This could be a real differentiator for customers, especially in the new age of minimal contact and social distancing. But unless every recommendation made by the solution is available to buy in store at that very moment, or if not, easily sourced and delivered to the customer’s destination of choice, using AI in this way does not provide a truly compelling and satisfying customer experience that is enduring and repeatably delivers on the bottom line.
In today’s highly competitive retail environment, with the future of many high street stores still uncertain, getting the customer experience right every time is now more important than ever before. In a post-Coronavirus retail landscape, it is vital that brands of all sizes understand the full end-to-end benefits that AI applications can bring.
With so much competition for online spend, customers will happily drift from brand to brand within the overloaded omni-channel marketplace if products can be delivered more quickly or cheaply elsewhere, making the customer experience of paramount importance. In practice, this means making sure stock is where it is needed, at the right time and delivering an efficient warehouse and distribution centre operation that can fulfil orders to either a store or a customer’s front door whilst still meeting social distancing requirements at every step of the way.
The key drivers of digital transformation in retail
Reacting to change
Retailers that have embraced AI in the warehouse are already driving tangible improvements in efficiency and accuracy. By combining order history data with AI and ML to better understand the characteristics of order trends (including direct to consumer ecommerce orders), retailers can streamline the pick, pack and ship processes. This insight into ecommerce order profiles over a certain day, week or month also provides better visibility on products or quantities ordered, which is extremely useful when managing or predicting a sudden influx of orders.
In fact, more than the back to school rush or an unexpected April heatwave, the huge spike in ecommerce orders seen once stores closed their doors at the end of March shows that retailers need to be prepared for new, unplanned demand peaks to emerge at any time.
The challenges of e-commerce: The internal blame game costing retailers thousands
Additionally, utilising AI in the warehouse enables employee schedules to be reorganised (to adhere to social distancing measures) and resources (man and machine) integrated and redeployed, all the while allowing orders to be seamlessly prioritised and new delivery options rolled out.
The retail industry is robust and pragmatic. Time and again it has shown its capacity to embrace innovation, rise to meet challenges and embrace new technology. Just like during the late ’80s and early ’90s, when some businesses considered investment in computers as part of their future growth and development plans, retailers who can rationalise value through specific AI investment to areas like customer experience or supply chain, will find themselves surging ahead of their competition.
Much like the proliferation of the internet over the last 30 years and the inevitability of digitalisation in this last decade, AI is a matter of when, not if, for retailers and the broader business community. At the end of the day, it comes down to a simple question – can you afford not to invest in AI?