Walk before you run: What retailers need before considering AI
RETAILERS will without a doubt be using AI to run their operations in the future.
Technology such as computer vision, facial recognition, and robotics are already being trialed in some major retail chains to optimize operations and personalize service offerings to customers.
However, those technologies aren’t suitable for just about any retailer. AI on its own wouldn’t bring the necessary benefits to a company unless it is perfectly integrated into existing systems and supported by a robust infrastructure of end-to-end process automation.
However, Forrester reported that more than a third of businesses suffer from process gaps and manual routing.
Therefore, before getting started with AI, retailers must automate the customer’s journey.
For example, a customer’s first engagement with a brand can trigger a welcome email. After a client has made a purchase, companies can reach out to customers on their preferred social channels with further offers.
This lays the groundwork for collecting additional information about your customers, to which you can apply AI for a more personalized experience.
Of course, this would require retailers to build software that is tailored to their needs, and quickly. However, unless you are a major retailer, it is unlikely that you’d have the time or resources to build in-house.
Tools like low-code development platforms can help small or medium retailers to speed up software development and create solutions that cater to their needs.
Although it’s important to spruce up your customer-facing capabilities, retailers shouldn’t neglect the back operations, as this will ultimately affect customer service. Robotic process automation (RPA) can help automate manual tasks typically handled by humans.
This can include returns processing, customer support functions, logistics and supply chain management, demand and supply planning, accounting and finance, etc.
Automating these processes will give companies a holistic view of their operations, allowing them to make informed decisions based on the insights.
AI systems can also use the data to perform customer analysis, which can help better target marketing efforts or make customer recommendations more intelligent.
Retailers can also reap the benefits of applying AI to back-end processes. For example, using natural language processing (NLP) to written materials. By providing context, customers get a more relevant suggestion that what is available on search results.
Companies can also use chatbots and analytics to automate frequently asked questions. This would free up human customer service representatives to focus on helping customers with more complex issues.
There are lots of potentials to improve customers’ experience and make business operations more efficient with the use of AI. Without a groundwork of automated processes, however, any AI implementation is counterintuitive.
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