Office supply retailer converts 51% of calls into orders and increases average order value by 10x.

Phone calls represented one of the retailer’s most valuable, but most underutilized, channels.

Customers would research products online, then call stores with specific questions about materials, turnaround times, or pricing before placing orders. These were highly qualified buyers ready to purchase. Higher-value opportunities, like large print jobs or recurring business orders, weren’t consistently reaching the Inside Sales team, and every conversation disappeared once the call ended. The company had no way to understand demand patterns, product interest, or customer intent at scale.

Store associates struggled to field those incoming calls because they were often tied up with in-store customers. Or struggling to get their own answers from their existing self-help chatbot which could only match a single question to a single pre-written answer. It couldn’t follow a multi-part question, couldn’t learn from new content over time, and gave every associate the same static response regardless of what they’d actually asked.

• High-intent phone calls got lost: A common pattern was a customer configuring products like business cards on the retailer’s website, then calling a local store with a quick question about turnaround time or materials before ordering. Store associates already helping in-store customers either missed these calls, put callers on hold, or answered a repetitive question that didn’t need a specialist.
• The wrong team handled the highest-value orders: The Inside Sales team was built to handle complex, higher-value print orders, averaging $450 per order versus roughly $40 for a typical in-store transaction, but wasn’t consistently receiving the qualified leads it was equipped for.
• Every call was a black box: No conversation data was captured, so product trends, competitor mentions, and customer intent signals disappeared the moment a call ended, leaving the company with no way to see what customers were actually asking about.
• One question, one answer, no more: The legacy associate bot failed on any question phrased differently than expected, or that touched more than one topic at once, so associates fell back on searching manuals or asking a manager, which was slower for the customer standing in front of them.
• New associates started from zero: With no consistent, always-current source of answers, newer associates couldn’t perform at the same level as tenured ones, and every policy or procedure update had to be manually rebuilt into the bot before it was reflected anywhere.

Quiq built two distinct AI agents, both grounded in the retailer’s own content and both designed to take action, not just answer questions.

• Multi-part understanding for associates, not single-intent matching: Unlike the legacy bot, the new assistant follows multi-part questions, learns and refines its answers over time, and lets the team upload process documents directly rather than manually rewriting bot content.
• Ticket routing built in: The assistant integrates with ServiceNow so associates can submit and intelligently route tickets based on the nature of the question, something the legacy tool couldn’t do at all.
• A full-page resource, not a widget: The team moved the assistant off a small chat widget onto a dedicated, full-page experience, with capacity to expand to additional in-store devices, along with reporting and NPS measurement the legacy bot never had.
• Given a friendly, on-brand identity: The team branded the assistant with a distinct name and personality to drive adoption on the floor, treating rollout as an internal product launch rather than a system update.
• Natural conversation for inbound sales calls: The AI Voice Agent greets callers, determines in real time whether a call is sales-related or general support, and answers simple questions immediately so customers can confidently continue ordering online or in-store.
• Real-time lead scoring, not a static script: For sales-oriented calls, the AI Voice Agent runs a flexible discovery process to collect product type, quantity, materials, size, and timeline, then scores the opportunity’s likely value in real time. High-value leads are routed to Inside Sales with full conversation context and explicit customer consent already captured; medium and lower-value leads go to in-store associates.

• A shipping-spec question, answered instantly: Instead of digging through printed reference sheets, an associate can ask the assistant something as specific as the maximum weight and size UPS allows for a shipment and get an accurate answer on the spot, in front of the customer.
• Proactive upselling prompts: When the design services team unexpectedly has open capacity, the assistant proactively messages associates so they can suggest design and print services to customers who might be interested, turning slack capacity into revenue instead of letting it go unused.
• “How fast can I get business cards?”: A customer calls a local store with exactly this question. The AI Voice Agent answers immediately, so the customer can confidently continue their order online or in-store without waiting for an associate to become free.
• A recurring print order, handled end to end: When a caller describes a larger, recurring print need, the AI Voice Agent works through product type, quantity, materials, and timeline, recognizes it as a high lifetime-value opportunity, and hands it to Inside Sales with complete conversation context and consent already obtained, so the specialist picks up exactly where the AI left off.

For store associates, the assistant changed the day-to-day rhythm of the floor. Instead of pausing to search for an answer or flag down a manager, associates get accurate information immediately, whether they’ve been on the job six years or six days. New associates now perform closer to the level of tenured ones on their first shifts, and the team has folded the assistant into every internal communication and SharePoint update as the default place to search first.

For Inside Sales, the shift was in the quality of what reaches them. Instead of relying on chance to catch a qualified caller before they hung up or got routed elsewhere, the team now receives leads that are already qualified, complete with product details, timeline, and consent for follow-up, and can start the conversation where the AI left off rather than from scratch.

For store and marketing leadership, phone calls stopped being a black box. Every call now generates structured data on what customers asked about, which products came up, and what indicated real purchase intent, information the company didn’t have access to before at all.

By building two AI agents grounded in the same knowledge base but tuned to two very different jobs, this office supply retailer turned both a stretched associate floor and an unmonitored phone channel into measurable, repeatable operations.

• 51% of sales-related phone inquiries converted into an order
• $38.5K in tracked sales during the initial tracking period, from a channel that previously generated zero visibility into what was happening on the call
• Every call now produces structured data on product interest, competitor mentions, and urgency signals, feeding directly into campaign design and seasonal planning that wasn’t possible before
• 35% increase in self-service containment for associate questions compared to the legacy bot, with a 68% average resolution rate over six months
• 4.82 out of 5 associate satisfaction score with the new assistant
• Associate assistant launched in 6 weeks, from proof of concept through pilot to chain-wide rollout