AI Agent Operational Lift for In The Swim Discount Pool Supplies & Equipment in West Chicago, Illinois

Why AI matters at this scale

In the Swim, founded in 1981 and headquartered in West Chicago, Illinois, is a well-established e-commerce retailer specializing in discount pool supplies, chemicals, and equipment. With 201–500 employees and an estimated annual revenue of $150 million, the company operates in a highly seasonal, competitive market where margins are thin and customer expectations are rising. As a mid-market digital-first business, In the Swim sits at a sweet spot for AI adoption: it has enough data volume to train meaningful models, yet remains agile enough to implement changes faster than large enterprises.

The pool supplies industry is characterized by predictable seasonal demand spikes, perishable chemical inventory, and a need for expert guidance. AI can transform operations by turning historical sales data, weather patterns, and customer behavior into actionable insights. For a company of this size, AI isn’t just a luxury—it’s a competitive necessity to fend off giants like Amazon and big-box retailers while improving customer loyalty and operational efficiency.

Three concrete AI opportunities with ROI framing

1. Demand forecasting and inventory optimization – Pool chemical sales peak in late spring and early summer, but overordering leads to costly write-offs due to shelf-life limits. A machine learning model trained on years of transactional data, regional weather forecasts, and local event calendars can predict demand at the SKU level. Reducing excess inventory by just 15% could free up millions in working capital and cut warehousing costs.

2. Personalized product recommendations – Many pool owners are unsure which chemicals to buy or how much. By deploying a recommendation engine that analyzes past purchases, water test results (if uploaded), and pool characteristics, In the Swim can increase average order value by 10–15%. This not only boosts revenue but also improves customer satisfaction by reducing guesswork and chemical waste.

3. AI-powered customer service – The company likely fields thousands of repetitive questions about water balancing, equipment troubleshooting, and dosage. A generative AI chatbot trained on product manuals and FAQs can resolve 40% of these instantly, lowering support costs and allowing human agents to focus on complex issues. This also provides 24/7 availability, a key differentiator in a market where pool problems don’t follow business hours.

Deployment risks specific to this size band

Mid-market companies often face unique hurdles: limited in-house data science talent, legacy systems that weren’t designed for API integrations, and cultural resistance to data-driven decision-making. In the Swim may rely on a patchwork of e-commerce platforms (e.g., Shopify or Magento), email tools, and ERP systems that don’t easily share data. A failed AI pilot could erode trust and waste resources. To mitigate, the company should start with a small, high-impact use case (like demand forecasting) using a managed AI service or a pre-built solution that integrates with existing tools. Change management and executive sponsorship are critical to ensure adoption across merchandising, marketing, and customer service teams. With a phased approach, In the Swim can turn AI into a durable competitive advantage without disrupting its core operations.