7 Simple Ways AI Will Improve the Retail Shopping Industry and Change Logistics


With COVID-19 accelerating change, these are interesting times for the retail business. On one hand, production and logistical costs are skyrocketing while on the other hand, consumers are getting pickier and harder to please, while shopping remotely. Most retailers are struggling to adapt to the changing ecosystem, but those who have embraced technology have found the secret of thriving in this crazy pandemic. Retail businesses are now using artificial intelligence (AI) to automate processes as a means of improving their efficiency and conversions. Here are some practical examples of how AI can help to improve the retail industry.

1. Before the pandemic, digital assistants were popping up everywhere.

In 2016, Lowe introduced LoweBot in its San Francisco stores to improve the customer in-store experience. LoweBot not only helps customers to find what they are looking for but it also provides any product information the customer might need. Retail stores can deploy such digital assistants which can help customers as they shop for specific products. When interacting with a robot, customers will feel freer to ask all sorts of questions including some that they might be afraid to ask a salesperson. But digital assistants can do much more than just finding products – they can also be used to carry out inventory tracking in real-time. Digital assistants will, therefore, improve the customer experience while at the same time helping the store owners with inventory control. Supermarkets like Stop and Shop have also introduced digital assistants in stores. After the pandemic, it is clear that less human interaction will become even more important.

2. Price adjustments and predictive technologies for price optimization are becoming commonplace.

AI has recently been used to determine seasonal trends and other factors that are known to influence the prices of goods. The data collected can then be analyzed and used to make relatively accurate price predictions. Predictive analytics can also be used to forecast the price points of products throughout the year. If customers had such an app, they would most likely be very loyal to the brand. Companies like Kroger and eBay are already using AI tools to optimize their prices. For instance, they make appropriate promotions and adjustments based on the data collected. Amazon is getting into this business, too. With the COVID-19 pandemic, customers will want future price protections and optimizations when goods are in high demand, rather than being at the whim of a greedy store owner who raises prices astronomically during times of crisis.

3. Supply chain management is becoming more important than ever – automation can help.

Supply chain management can make or ruin a business depending on the approach taken. Thankfully, automation can help to make the logistics process efficient, easy and inexpensive. Automation can help to eliminate bottlenecks in the supply chain that result in huge losses. For instance, AI can be used in network planning to ensure inventory doesn’t lag demand. When a company knows what to expect, they can allocate more resources where a higher demand is expected. Smart warehouses that are completely automated can also be adopted. Apart from simplifying otherwise tedious processes, smart warehouses will also reduce operational costs. A real-life example of how AI can improve logistics is the use of GPS tools by drivers. Drivers can use a GPS tool for taking the most cost-effective routes. The GPS tool would optimize the routes based on traffic conditions, distance among other factors.

4. Virtual dressing rooms might help reduce returns and increase customer satisfaction.

The thrill of picking up clothes randomly is ebbing away especially with the growth of e-commerce. The modern-day shopper wants to know how well the clothing will fit them before they even try it on – and that’s where virtual dressing rooms come in. The obvious application for virtual dressing rooms is for fitting clothes, but this technology can be applied in lots of different niches. For instance, you can upload a photo of your apartment to see how the furniture you intend to buy will fit in or upload your selfie to find the best pair of glasses. Virtual dressing rooms will make it possible to get the perfect items without having to visit the brick-and-mortar store for fitting. Buyer remorse will be reduced because shoppers will buy what they really want and not what a customer sales representative convinces them to buy. Additionally, with more satisfied customers, it stands to reason that there will be less returns and less headaches for shippers with buyer returns.

5. Predictions of customer behavior make the shopping experience personalized.

Customers want to be treated as individuals and not just some statistic. One sure way of achieving this is using AI to predict customer behavior and customize a unique shopping experience for them. Behavioral economics can be used to analyze the emotions and psychology of a customer in order to make relevant product recommendations, upsells and cross-sells. The behavior of the customer can also inform the algorithm of the optimal offers to suggest. During the customer acquisition stage, predictive analytics can also be used to predict which customer is likely to make a purchase. Such customers can then be forwarded to a dedicated salesperson who can guide them through the purchase process. With a more personalized shopping experience, retailers will again see less returns and logistics headaches.

6. MAP monitoring is helping retailers be more competitive – and profitable – than ever.

Minimum Advertised Price (MAP) monitoring helps retailers to know the lowest price at which they can offer a product. Selling products below the MAP will result in huge losses for the business and it might also damage the brand image. Every brand wants to safeguard its brand image by ensuring retailers are not selling their products below their MAP. AI can help brands to track product pricing in real-time. When the MAP goes below the threshold, the resellers can be notified and appropriate action taken. This intelligent form of logistics and supply chain management is the future – and retailers are starting to take it very seriously.

7. Check-out free stores will make the shopping experience more efficient and safe.

Automation will make it possible to have cashier-free stores. This will be in even greater demand once the pandemic comes to an end, as customers will want to minimize human contact. Amazon Go is a perfect example of this concept. The algorithm reacts to shoppers after they walk out of the store with the goods they want. The customers are then billed for the items they left with. Amazon envisions opening up lots of such stores that will have fewer human staff. There are lots of companies that have developed check-out free solutions for retailers. As the AI technology continues to improve, shopping and walking out of the store without having to scan the products at the checkout counter will soon be the norm. Check-out free stores will have less operational costs, more-efficient logistics, as well as a faster and safer shopping experience – that’s more important than ever in the age of COVID-19.

Overall, automation is making shopping and logistics more efficient than ever before.

Automation of menial and tiring processes is a sure way of improving efficiency while at the same time cutting down on operational costs. As artificial intelligence continues to evolve, more tools that can make retail better will be unveiled. Any retail business that takes business automation seriously is going to lead the pack even as the late adopters struggle to stay afloat – this is especially true with the COVID-19 pandemic and new safety challenges.