Buy online, pick up in store (BOPIS)

BOPIS, short for Buy Online, Pick Up In Store, is a retail fulfillment model that allows customers to purchase items through an online storefront and retrieve them at a physical location. BOPIS workflows increasingly intersect with AI systems, particularly those that support customer communication, real-time inventory checks, store operations, and automated status notifications. 

How BOPIS works

BOPIS is enabled by the connection between a retailer’s online shopping platform and its physical store inventory systems. When a customer places an order online and selects in-store pickup, the retailer must confirm that the item is available at the appropriate location and prepare it for handoff.

Operationally, the process typically involves:

• Real-time inventory validation: The online platform checks whether the item is stocked at the selected store. 
• Order confirmation and reservation: Once the order is placed, an inventory management system reserves the item and notifies store employees to retrieve it.
• In-store picking and staging: Store staff collect the item, prepare it for pickup, and update the order status so that customers know when it’s ready.
• Customer pickup process: The shopper typically receives a text or other alert letting them know the order is ready. They can then collect the order from a designated counter or curbside area.

AI-powered automation is increasingly used to support forecasting, staffing, inventory management, and customer communication.

How BOPIS shapes modern AI-driven customer service

BOPIS amplifies the importance of accurate, real-time data. AI systems need to interpret customer intent and provide clear guidance without delay. AI can also proactively reduce service demand by sending automated alerts about order readiness, delays, or substitutions.

Additionally, because BOPIS intersects with both digital and physical operations, AI models often help detect anomalies—like unexpected inventory shortages, order bottlenecks, or pickup congestion—that could negatively affect the customer experience.

Factors that influence BOPIS success

BOPIS works best when digital and in-store systems operate in sync. Customer expectations for speed and accuracy are high, which means AI tools used for inventory checks and customer support rely on current, consistent information. A few operational elements tend to determine whether BOPIS runs smoothly:

• Inventory accuracy: AI tools can only give correct answers if store-level inventory data is reliable. Inaccurate counts often lead to cancellations or unnecessary customer service inquiries.
• Timely order communication: Alerts about order readiness, delays, or substitutions must reflect real pickup status. Mistimed updates create confusion and poor experiences at the counter.
• Low-latency system updates: AI systems depend on fast data refresh rates across e-commerce, order management, and in-store tools. Slow updates can result in outdated or incorrect customer information.
• System speed: When AI models interpret changes in order status or inventory availability, slower inference time  can delay responses and lead to outdated or conflicting BOPIS updates, especially during high-volume periods.
• Consistent in-store workflows: Even with automation, store teams handle picking and staging. Predictable processes help AI suggestions and customer-facing messages stay aligned with real operations.

When these elements are stable, AI systems can deliver more accurate updates, reduce support demand, and help ensure BOPIS interactions feel seamless for customers.