Five Ways Retail Leaders Can Use AI To Streamline Operations

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Five Ways Retail Leaders Can Use AI To Streamline Operations

Salman Shahid, CEO at OXO Packaging.

AI-powered solutions use LLMs and machine learning models that provide convenience and help achieve faster outcomes in retail businesses. In this article, I discuss five ways AI solutions can help you streamline your business operations—whether you’re planning to start a retail business or are already running one.

1. Supply Chain Optimization Through Automation

Seamless supply chain management (SCM) can improve product fulfilment, streamline your retail operations and help you save business expenses. Retail giants like Amazon and Walmart already embed automation into their distribution centers and fulfillment centers.

For example, you can adopt automation to mitigate packaging hassles and optimize your supply chain on a large scale. Computer vision applications in packaging can help avoid errors and improve efficiency.

Supply chain automation can improve your warehouse efficiency, reduce operation costs and minimize errors. For example, AI can be used to gather operational data from machines using IoT. This data can help you make informed decisions about SCM and help ensure you utilize your resources efficiently.

2. JIT Inventory Management With AI

The just-in-time (JIT) approach can help in managing your inventory and reduce both employee and customer frustration. This approach minimizes the inventory unnecessarily occupying space by controlling the production according to market demand.

You can benefit from this inventory management approach using machine learning. To do so, consider inventory management solutions like Microsoft Azure and IBM Sterling that incorporate data collection, tokenization, model training, prediction and fine-tuning.

Regardless of the platform you use, make sure you can integrate your trained models with the software. For example, you may want to connect your ERP (enterprise resource planning), SCM (supply chain management), and MES (manufacturing execution system) with the JIT inventory management solution to save human capital and production costs.

In-house-trained AI models can help you with demand forecasting. They can also provide real-time insights that help in production planning, inventory optimization and quality control.

3. Hiring The Right Talent With AI

Building an experienced team that can manage your business operations is necessary yet challenging for retailers. But you can make onboarding easier with the help of AI.

Using AI, you can create programmatic advertisements to make recruitment more convenient. For example, the moment a team member files their resignation, an AI model can be triggered to run ads, helping you find a replacement easily and quickly. Keep in mind, though, that you’ll need to combine your ERP with AI to run automatic job ads.

You can also use a machine learning model for recruitment analytics. By feeding it data from your recruitment database, this model can create a detailed report showing the strengths and weaknesses of your recruitment process. For example, you can list your recruitment dos and don’ts and use this checklist to gauge if you followed your recruitment guidelines correctly. Adopting such a transparent approach will hold you accountable for your hiring decisions and help ensure you onboard the right people.

4. Establish An AI-Enhanced Marketing Infrastructure

Marketing that helps engage buyers across different channels requires a strategic approach for the success of your retail business. With an AI-enhanced marketing infrastructure, you can narrow down the marketing funnel and get more qualified leads.

For example, you can gather all the data from your marketing channels and feed it into your KPI-tracking AI model. This approach can help you decide how different channels performed and what changes you can make to boost your ROI.

You can also use your data to measure your “brand love” to determine the effectiveness of your marketing efforts. Doing so will help you align your marketing strategy with your business goals.

Getting “brand love” results has become easier with the use of AI tools. You can perform sentiment analyses and other first-party data analyses to gauge how customers talk about your brand. With any of the leading AI marketing platforms, you can get valuable insights from customer surveys and learn how you can dominate the retail industry.

You can also take advantage of machine learning to understand how your customers behave, training models to make data-driven customer behavior predictions. This will also help with customer segmentation and enable you to focus on customer needs to enhance their experience and boost brand loyalty.

5. Dynamic Pricing With AI Algorithms

Offering market-competitive pricing and securing profit on products are fundamentals of a retail business. With AI, you can establish a dynamic pricing strategy that can help you beat the competition.

To do so, you can use large language models (LLMs) like Gemini, Perplexity or Claude to help conduct competitor research, such as reviewing the profit and loss statements of your competitors. This helps you establish an omnichannel pricing system that offers competitive yet profitable product prices.

You can also use LLMs to analyze sales data and seasonal trends to help personalize promotions based on customer behavior. These insights will also assist you in determining a customer’s value.

Conclusion

These five examples illustrate how AI can help streamline your retail operations and provide more profit with minimal effort. Adapting these strategies to your business needs can help you gain a competitive edge.


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