With the rise of retail eCommerce, technological trends are creating a significant impact on the industry
While global industries across all sectors have used some advanced technological tools and software programs, the retail sector has recently turned to several technological support systems.
The Gulf Co-operation Council (GCC) is the tenth most favourable retail destination, especially the UAE, Saudi Arabia, and Qatar. In Saudi Arabia, over 45 per cent of the consumers are choosing to shop online more frequently, according to a Statista survey.
The GCC retail sector is predicted to grow over $550 billion by 2030 and might further accelerate due to the retail eCommerce trend and the rise of digital technology. Recognising the potential in the Middle East, Mothercare has shifted its focus from the UK market to the Middle East.
According to Juniper Research, the retail industry has invested significant funds in Artificial Intelligence (AI), and the spending is estimated to reach over $7 billion by 2022. Statistics show that most AI and Machine Learning (ML) solutions adopted by retailers are changing customer demands and behaviour.
Here are our top 6 picks of retail technology trends.
Stocking Up Merch with Algorithms
Using customer behaviour insights and predictive analysis, retailers can now decide what items need to be stocked and what needs to be displayed for maximum visibility. Called algorithmic merchandising optimisation, this technology can help determine the price, maximise sales, margin, and inventory, while satisfying all customer needs. It evaluates the performance touchpoints of items and customer segments. The insights help retailers make informed decisions.
Tata services offer algorithmic merchandising optimisation. TCS Optumera, an AI-powered retail optimisation suite, helps optimise merchandising and supply chain decisions in an integrated method. According to Optumera, retailers have experienced a three to five per cent increase in sales, a 50 per cent reduction in time spent, and 20 to 30 per cent in cost reduction.
Additionally, Sephora Middle East re-organised its demand forecasting methods by using demand planning tools and several algorithms. The integration of algorithmic intelligence allowed them to reduce 25 per cent in supply chain costs and maintain a 95 per cent product availability on the shelf.
This was a crucial piece of technology because operational costs due to the current economic situation have forced retailers to re-strategise merchandise assortment and pricing. Having inventory in all store locations can drive a massive hole in the pocket. The retailing technology could enhance planning assortments, promotions, and pricing.
Before a full-fledged adoption, experts recommend an in-depth analysis to recognise performance gaps and identify new opportunities from stock downs, expired inventory, and markdowns. Also, a thorough understanding of how near-real-time datasets work with AI-led approaches can help.
Also Read: Technology Trends Impacting The Future
Getting Personal with Data Science
Data Science and ML can be successful drivers of personalisation in the retail industry. Customising with insights from customer suggestions, the technology uses purchase data to create shopping profiles that can help enhance the process. This technology trend is crucial to today’s social and e-commerce retail industry as it can drive greater ROI and customer experience (CX).
Consider Dubai-based retail chain Aswaaq. They have established 21 stores in the GCC region and have leveraged indoor mapping and product location navigation systems. This enhances their CX and also provides their customers with real-time promotional offers.
Another example is a cloud analytics company Algonomy (earlier Manthan) that provides a platform called Customer360. Using predictive, descriptive, and prescriptive algorithms, they help brands gather and analyse campaign, loyalty and transaction data from both conventional and digital mediums.
Chatbots are also becoming increasingly valuable for retailers as they can create efficient recommendations, website navigation, order tracking, and communicate with customers. Natural language processing (NLP)-driven chatbots have been leveraged by several e-commerce brands for better, personalised experiences.
Brick and mortar stores also immensely benefit from this technology trend. For instance, RFID technologies and Bluetooth Low Energy utilise a limited power to create consumer data collection for personalisation experiences.
Also Read: How Chatbots Can Enhance Customer Experience Using NLP
‘Add One to the Cart, Please’
Forrester reported that over 90 per cent of customers changed their behaviour as they were forced to avoid physical retail stores due to the pandemic. Since 2020, many retail companies have invested in virtual stores and live videos. Such engagement technologies and conversational AI has overpowered retailers who were forced to embrace e-commerce and social commerce.
According to Gartner, 50 per cent of knowledge workers will interact and depend on Intelligent Video Assistant (IVA) every day by 2025. While consumers enjoy the IVA innovations in the form of Amazon Echo devices, Apple HomePod, and Google Home, these conversational assistants are being leveraged by retail companies to accelerate revenue. They believe that IVA can improve the business efficiency process, reduce costs, and streamline business processes.
While these front-runner IVAs have already improved the retail market, many brands have begun to make improvements for a better customer experience. A voice ordering service where the voice assistant is asked to add products to the cart is a popular trend as well.
For instance, some Amazon Go stores have attached Alexa devices to their shopping carts. Consumers can now check off items from the shopping list as they move down aisles, and Alexa can also help them navigate their way around the store. You wouldn’t have to hunt for those items tucked away in the corners.
Mirror, Mirror On the Wall
Augmented Reality (AR) in the retail world is a highly beneficial technology that can skyroket CX. Using AR, customers can have a 360-degree view of how a product would look on them without the need to try them out physically. This contactless shopping 2.0 in the post-pandemic world can reduce the number of SKUs in the shop and improve the consumer buying speed. Although a trend, it is yet to become commercially viable.
Meanwhile, some retailers have embraced the concept to offer an out-of-the-world experience to their customers. For instance, Dubai-based Max Fashion installed a magic mirror variation to engage their customers and had a 20 per cent conversion rate.
On the other hand, Adidas has installed interactive mirrors that utilise Radio-frequency Identification (RFID) in their trial rooms. It lets customers request different sizes or colours, and the AR allows them to pose with diverse backgrounds for a better look of themselves in a new product.
Security Checkpoint: Hackers Beware
New technology trends lead to new security threats. With online retail moving to the cloud and investing in e-commerce, the security of data and applications in the cloud is a top-order priority. This rapid retail transformation might create security complications, and brands might struggle to locate the misconfiguration.
Retail business leaders and security leaders have been trying to launch a beneficial security strategy and create cyber defence opportunities for improved resilience and brand trust. Experts advise companies to look beyond firewalls.
A Fortune Teller Named ML
Retailers are still trying to understand the shift in customer demand. Predicting the slightest change in behaviour is crucial to stay ahead of competitors. For a demand forecasting process, data is essential. Brands have begun to leverage ML solutions to make the process more effective. ML innovations can enhance inventory planning, automatic demand forecasting, manufacturing, marketing, and logistics.
Brands are increasingly optimising the process with NLP and cascade models, POS data and other data that includes exchange rates, market statistics, and economic factors. It can also help retail management teams avoid overstocking, reduce logistics expenses and support sustainable consumption and production. Being more adaptive, ML-driven demand forecasting is proven to follow customer demands better.
Course5 Intelligence offers customer analytics solutions and tools for better insights and effective customer engagement. To understand the customer demands, they leverage several technologies, including NLP engines and comprehensive API libraries.
