Modern digital lifestyles are built on a myriad of connections. As much as it’s convenient for customers to log-in and shop online, the ability of retailers to deliver on customer expectations depends on multiple factors that are often beyond their control. In the past two years, supply chain shortages and volatility have added to the complexities of delivering a good customer experience (CX). Companies have had to adapt and it’s been a difficult balancing act to try to keep customers happy when there is so much uncertainty to manage on both sides of the retail journey.
Traditionally in retail, the supply chain was relatively predictable and it wasn’t difficult to plan for seasonality based on historical supply and demand data. The sudden increase in digital commerce placed additional pressure on logistics and delivery capabilities. Stock and labor shortages combined with shipping delays and reduced transportation capacity meant requests for same day or even next day shipping could often not be met. The supply chain went from an area of business that was stable and understated to being one of the top priorities needing to be updated weekly on the CEOs agenda. This accentuated the need to have technologies in place that could keep up with the shifting changes in supply and more accurately forecast to meet a dynamic demand.
While most customers were aware of the challenges that resulted in delayed deliveries, their empathy mostly extended only to the delivery people. If a retailer had a product listed and offered a delivery method, customers expected it as advertised. For retailers who were already challenged by the rapid transition to digital channels, it added another dimension to the complexity of CX. Retailers not only had to be able to integrate digital shopping with inventory and delivery systems, they also needed to access the information in time to keep customers updated when delays occurred.
The pressure on companies to be able to scale to meet the new levels of digital demand was immense, and it was impressive how quickly many of them were able to pivot. In a way these circumstances were the catalyst that ushered in a new level of acceptance of technologies such as machine learning (ML) and artificial intelligence (AI). The ability of ML and AI to navigate complexities at scale became a lifeline and a foundation for a new way to do business.
Customers are browsing across multiple digital channels and regardless of whether they’re engaging on social media, a mobile app, or a retailer’s website – they’re expecting a consistent brand experience. However, different generations have their own preferences and retailers looking to engage with customers have to understand what’s important to customers on an individual level in order to get them to engage.
For example: instead of simply using social media as a hook to drive visitors to a website where everyone gets served the same digital experience, it’s an opportunity to leverage the different channels to better understand customer behavior and meet customers where they are. With these insights it becomes possible to deliver a more personalized experience when a customer lands on a specific retail web page.
While investments in technologies such as AI have increased, there’s also the realization that technology is merely an enabler that can help companies better connect with customers and generate insights to improve decisions. If this isn’t matched with an agile mindset that uses the data generated to make the most of new opportunities then companies won’t realize a return on investment as expected.
For example: during the pandemic many pharmacies became vaccine clinics. With a significant increase in foot traffic over that period of time, it was an opportunity to increase inventory of specific products that customers waiting for vaccines may want to stock up on. Having technologies that could help connect all the dots can enable managers to make more informed decisions to capitalize on additional sales opportunities.
Another important consideration is the growth in mobile commerce. Customers have become so accustomed to using their phones to browse for different options and engage with brands and retailers. Buy Online Pickup In Store (BOPIS) that developed out of necessity during the pandemic is a shopping experience that many customers have come to love. Going forward retailers will need to consider what’s important to customers and what their preferences are, even if in-store shopping becomes the norm again. Optimizing CX for mobile is one way to bridge the gap and create hybrid shopping experiences that link online and in-store.
The challenge with volatile market conditions is that there isn’t a great deal of historical data to inform decision making. But now with AI, it becomes possible to predict what inventory is needed and how and where customers might purchase. There is also the advantage of continual learning. As more real-time data becomes available it becomes possible to adapt decisions according to customer buying behavior. This enables retailers to adapt faster to changing market conditions while at the same time factoring in customer preferences and buying habits.
On the supply chain side, once there is sufficient data, AI can further generate efficiencies by helping to automate some of the processes. The focus is geared to leveraging technology to drive better customer engagement and digital experiences.
Technology is no longer the bottleneck holding back progress, it's the approach to retail that requires a new mindset. Traditional ways of shopping are largely obsolete. Customers may return to stores, but they’re still engaging online and retailers need to continue to seek out ways to engage with customers to deliver relevant information at the right time. AI has a big role to play in this, particularly in learning from how visitors navigate web pages and how this differs on different devices and channels. AI driven optimization coupled with a progressive mindset towards experimentation is what will help retailers stay ahead of the game, despite volatile market conditions.