CTS thought leadership
The retail landscape in 2023
Throughout 2023 (and beyond), inflation is predicted to affect all aspects of retail. The first week of the year saw shop prices hit a record high by surging to 8%, according to the latest figures from the BRC-Nielsen Shop Price Index. Now more than ever, retailers must support its customer base while also safeguarding margins. But, as consumer sentiment falls and customers are focused on searching for value, how best can retailers achieve this?
Fortunately, these two objectives are not dependent upon each other. By exploring the power of cloud-based analytics, Machine Learning (ML) and Artificial Intelligence (AI), granular insights will enable retailers to construct innovative strategies to decrease costs and enhance the consumer experience. Customers can be aided in their online product search, irrespective of ambiguous search terms or spelling mistakes. Through this, the $trillions lost to abandoned baskets every year is reduced whilst simultaneously developing a better shopping experience.
CTS Sales Team Lead, Andrew Bithell, outlines how this technology is aiding retailers to leverage the full potential of their data resources and driving the necessary innovation for decreasing costs while managing evolving consumer demands.
Understanding Different Circumstances
Shopping behaviours are being impacted by the rising cost of living crisis, and although it’s always been a priority for retailers to understand and act upon changes in customer behaviour, present day consumer activity is more nuanced than ever. A substantial difference between product types remains as prices continue to rise, forcing some retailers – and some categories – to be up against far tougher trading landscapes than others.
Accessing granular insight into different customer groups’ experiences (ideally at SKU level) is crucial, particularly with current pressures. How can retailers supply the best value to shoppers whilst avoiding sacrificing the standard of experience? What is the best approach for organisations to reduce costs and safeguard margins whilst retaining customers? What more can be done to attract and satisfy a customer base struggling to make buying choices?
Almost all retailers already have access to the data that can provide such crucial information. Yet, isolated data provokes siloed decisions being made without considering context generated from a whole data overview. If the retailer strategically reduces the price of their day to day essentials, will customers continue to purchase the high margin luxury version? Does the opportunity stand to capture the sustainability conscious buyer with improved value on eco-friendly items? This is where retail is being transformed by cloud technology, enabling companies to run sophisticated analytics across several data sets to fuel crucial innovation that will both decrease costs and boost experiences.
Eliminate Lost Opportunities with AI
Arguably, the biggest question is where to start. Cart abandonment remains one of the top priorities for this year. Despite the figures presenting a range from 56% to 81%, recent data from the Baymard Institute revealed the average cart abandonment rate to be just under 70%. This figure is even higher for mobile users, who have an abandonment rate of 85%, which raises concerns when considering that the amount of digital buyers using smartphones to shop this year will continue to rise.
Ecommerce retailers have remained extremely proactive in leveraging data to improve the standard of the checkout process and minimise inconvenient glitches during payment. So how else can the online experience be improved and what can be done to eradicate the forecasted $4 trillion worth of merchandise estimated to be abandoned in digital carts in 2023 alone?
Improving the process of navigating customers to their desired products is a significant opportunity. Likelihood to purchase can be boosted through minimising clicks, which is the key to reducing frustration. Customers can quickly be taken to the wrong products thanks to spelling errors and misunderstood voice search, deeming them more likely to abandon everything already in their cart. Natural Language Processing (NLP) is enabling AI to play a key role in this, spotting standard spelling mistakes and automatically directing the buyer to the desired product. By guiding them through the process quicker and more efficiently, the amount of abandoned baskets will be reduced and the buyer experience will be improved, generating retention and loyalty.
Upgrading Experiences through Collaboration
An additional substantial retail expense is returns, with free returns costing UK retailers approximately £7bn a year. Abandoned carts are also contributed to by returns policies, with an estimated 67% of consumers abandoning virtual baskets if the returns policy does not meet expectations.
Retailers must adopt a new approach. A range of solutions have been tried, such as implementing fees to discourage ‘wardrobers’ and ‘bracketers’. However, the problem is not merely the cost of returns, but also the standard of the refund process and the impact of this on customer perception. Why are consumers so often expected to print their own return labels, when so few people have a home printer these days? After being forced to spend ages in line at the Post Office to return an order, how likely is a customer to return to the brand, whether the return was free or paid for?
Omnichannel retailers have made it easier for shoppers to buy online, pick up and return in store. However, customer time and effort is still required throughout the process. A lot of consumers opt for a supermarket delivery once a week, so what is stopping retailers from taking inspiration from the Nespresso approach (collecting used capsules for recycling upon delivery of new products) and at the same time provide a returns service?
The ideal approach has already been established: ensuring optimised delivery models, capturing information with hand held devices, rapidly assessing, in granular detail, the effect on customer behaviour and the company’s environmental goals with powerful cloud-based analytics. The outcome will not only develop an improved returns process for consumers, increasing their odds of repurchasing from the brand, but delivery companies could limit empty miles, boosting their environmental credentials and decreasing expenses.
Conclusion
Fortunately, the British Retail Consortium remains optimistic about the outlook for the end of the year and beyond, suggesting improvements within the market. However, customers are seeking trusted retailers now, with expectations of value and a better experience that helps them within the next few rough months. Retailers need to recognise and act upon this opportunity to utilise cloud-based analytics to transform customer and cross business understanding. This data can enable them to provide value to consumers through enhanced shopping experiences and optimised pricing that will ensure retailers are best placed to leverage opportunities as the market recovers.
