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5 Hottest Trends for Ai in Retail

ElectrifAi
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August 19, 2021
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The retail industry constantly changes and evolves to align with revolving seasons and trending items. Keeping up with the fierce competition that seeks to draw in customers, however, can be difficult. How does a company really get to know its customers?

Many companies put a large budget towards customer research. But even large teams can only do so much to understand the vast differences in customer behavior. There are thousands of data points to sift through and that takes time to process.

But luckily… there is a better way!

Artificial intelligence (Ai) is a powerful technology that utilizes the processing power of machine learning to track and analyze patterns in data in a fraction of the time it can take a human being.

With such a fast and efficient way to analyze customer behavior, retailers using Ai can enhance business operations to grow profits, reduce risk, and decrease costs.

What are some of the best ways Ai can help the retail industry? Let’s take a look at the 5 hottest trends for Ai in retail.

Computer Vision to Track Inventory and In-Store Activities

Computer Vision is an Ai technique that trains computers to understand digital images or videos and take some action based on what is seen. There are many ways computer vision can help the retail industry, including:

  • Identify store displays that attract customers.
  • Monitor in-store surface areas that are the most touched to enhance cleaning operations.
  • Monitor and recognize suspicious activity.
  • Detect on-the-job safety and compliance errors
Forecast Demand to Ensure Optimal Supply

Optimizing your supply and accurately forecasting demand is important to leverage throughout your retail operations to improve business decisions. Machine learning can help you with these efforts to:

  • Ensure your customers can purchase the items they seek.
  • Improve supplier relations and empower your team to negotiate favorable purchasing terms.
  • Optimize inventory levels to reduce overstock or under-stock problems.
  • Increase organizational efficiency for business teams, such as sales, procurement, logistics, or finance.
Increase Brand Loyalty to Encourage Repeat Business

Excellent customer experiences are what keep people loyal to your brand, encouraging repeat business and word-of-mouth references. With machine learning, you can:

  • Gain critical insights into your customers to understand their spend passion and provide amazing customer products and services.
  • Establish a loyalty program that will boost revenue and customer retention.
  • Create an effective business strategy to attract new shoppers and keep them coming back.
  • Consistently provide high-quality products and stay on top of trends.
Optimize Marketing Efforts to Enhance Customer Experience

Marketing efforts can provide a great way to enhance the customer experience. Machine learning can help you:

  • Customer behavior analysis to better understand your customers and what they want.
  • Personalize marketing campaigns to offer products your customers are sure to like.
  • Optimize email campaigns to encourage your most loyal customers to come back.
  • Segmentation to distinguish customers by defined characteristics (e.g., return visits, click-through rates, ad engagements, purchase history).
Optimize Supply Chain Network Routes

With advancements in AI and ML, organizations can now automate and optimize route planning processes, enabling efficient and cost-effective delivery. AI and ML algorithms can analyze vast amounts of data to analyze patterns and trends to identify the most efficient and effective routes for deliveries. These technologies can even factor in vital information such as driver behavior, road conditions, and delivery schedules, making it possible to optimize routes in real-time.

Maintain the Optimum Inventory Stock Levels

AI and ML can play a significant role in helping organizations achieve the right stock levels through accurate stock optimization. Companies can now analyze a wide range of data points such as historical sales data, customer demand, and supply chain logistics to identify the optimal stock levels for each item in their inventory, thereby minimizing the risk of stockouts or overstocking.

Predict How Customers Will Shop in the Future

Customers’ shopping patterns can be identified and leveraged to predict how they will shop in the future. With machine learning, you can find useful information and patterns that can help you:

  • Accurately predict what your customers are likely to buy in the future.
  • Inspire customers before, during, and after purchases to encourage upsell, cross-sell, and repeat purchases.
  • Predict what customers are likely to purchase in-store to help sales associates close the sale.
How Can ElectrifAi Help?

Ai’s impact on retail is just beginning to make its mark and there is so much more that awaits. After all, machine learning use cases in retail are always expanding. There are many powerful ways retailers are usingAi. The question is, how are you going to get started?

ElectrifAi has pre-built machine learning models to help you begin your journey to Ai and machine learning. To learn more about the role ofAi in the retail industry, download this e-book:

MachineLearning and Retail: Built ML Models Can ImproveCustomer Experience and Boost Revenue

In this e-book, you will learn how you can optimize and enhance:

  • Traffic
  • Conversion rate
  • Average order value
  • And so much more!

Partner with ElectrifAi to ensure a great return on investment with machine learning. Don’t think that Ai and machine learning are out of your reach because it takes too much time or is too expensive. With our pre-built ML models, we can reduce your time to value with Ai. We make it easier for you to address high-value use cases within weeks compared to months.

To learn how we can accelerate your business success, contact us today.