Digital transformation in the retail technology industry has taken off with new developments set to increase customer engagement and experience. Not only beneficial for customers, but these developments also help brands utilize data to improve service and maximize revenue streams.
So, what are the significant technological advances in the retail market at the moment?
Artificial Intelligence
Although AI has been around for some time now, it’s made massive strides in widespread application.
Retail brands are employing AI on their websites to enhance customer service via chatbots. The bots find quick solutions via text or calls. If it is unable to find a solution, the bots connect them with the appropriate human customer services department. Businesses have more time for actual problem solving than spending time attempting to identify the problem.
illustration by Folio Illustration Agency
Another development has been ‘centric visual search’. AI helps to identify relevant consumers for specific products through search histories and cookies. It uses capabilities that match the product and personalizes results. Again, significant customer engagement improvement. Small businesses are now able to employ these methods to engage with customers in additional geographical locations.
The future of retail reality is moving at a fast pace. Machine learning augmented reality, and automated processes will change the way we shop and sell in years to come.
Machine Learning
Making predictions about future business trends can help manage supply chain process, inventory management and stock numbers. Smart marketing campaigns are another attractive improvement.
Machine learning vastly improves demand forecasting. Businesses have seen an improvement in inventory management. Due to more accurate, real-time forecasts of predicted and actual sales, production can be optimized. Data is aggregated from the point-of-sale and captures trends on a short-term basis.
It can also play a vital part working with AI to highlight customer engagement trends, content demand and much more. Solutions can identify factors that may affect product bringing businesses to a more data-centric supply chain.
Quicker processing
Machine learning in payments has significantly improved customer experience for those shopping online and in-store. Counter-top card machines are now optimized for quick payment processes, contactless payment (with increasing amounts allowed) and provide an added layer of security.
For online shoppers, smart algorithms assess customer behaviour and reduce the number of verification steps. The data provided is processed faster, and there is less manual work for online retail owners.
A general concern with faster payments is the opportunity for cyber-fraudsters to interfere. To deal with this, some have begun to use ML algorithms to check every transaction for fraud. A task often fulfilled by banks rather than card-machine providers. The algorithms process large sets of data from payments made through online payment gateways or card-machines. Data collected is used to find correlations between user behaviour and how likely the transaction is to be fraudulent.
The pros of using ML for faster payments that have an added layer of security is plentiful, especially in comparison to traditional methods of rule-based fraud detection. It used to be that customers were required to fulfil multiple verification steps and payments took longer to process. If there is a fraudulent transaction, it requires manual work to identify and combat it: this harmed customer experience and overall brand reputation.
Online shopping is changing in more ways than one; augmented reality is making waves too.
Augmented shopping and virtual reality
Demand for AR systems has been consistently rising. Customers are now attracted to interacting with products online, instead of trying them on in-store. From furniture to shoes, consumers are now able to try anything on without having physical access to the product.
An example of this is how furniture shoppers are now able to, with precision, fit virtual objects into their homes. These virtual and almost realistic interactions with products are proving to be a valuable investment. AI can also suggest better products or offer changes that may suit the customer. Augmented shopping is shaking up the customer experience like nothing else.
Virtual reality shopping is an innovation that may be well suited to the post-pandemic world. However, the application may be difficult for the average retailer despite consumer adoption. Innovative companies are looking to adjust to the future, but difficulties of implementation remain.
5G
Gartner has found that 5G applications of AR and VR have the highest attraction rate. The quick, secure network allows for real-time rendering for videos and shorter downloading times. This extension of brands will enable retailers to create great immersive customer experiences. Many retailers realize that access to 5G networks remains expensive and difficult in specific geographic locations. Landlords have to make changes to implement this which would take some time to be widespread.
Final remarks
Moving into the future retail spaces, both online and in-store will see plenty of technological changes. AI, machine learning and virtual reality improve customer experience. With faster processing times and more try before you buy opportunities can attract customers increasing brand awareness and loyalty. Marketing campaigns will see massive improvements in targeting relevant consumers across the world. Retailers will find some costs associated with the initial implementation, but overall the streamlining of processes and improved services will pay off in the long-run.
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