Agentic Traffic Control Room: Understand and Manage AI Shopping Traffic

‍Agentic Traffic Control Room is designed to give retailers visibility and control over how AI agents interact with their stores. It connects four priorities: understanding agent activity and its relationship to orders, improving product information, enabling relevant sponsored offers, and managing agent access.

A shopper asks an AI assistant for an air fryer for two people. The basket must be dishwasher safe.

A retailer has a suitable product, but its catalog does not include that detail. The agent cannot confirm whether the product meets the requirement.

For the retailer, the challenge is knowing what went unanswered—and what to improve before the next request.

Agent-led shopping introduces questions that commerce teams need to answer. What are agents looking for? Does the catalog provide enough information? Which interactions lead to orders? How should retailers manage access and commercial participation?

That is the problem behind Agentic Traffic Control Room.

Understanding a shopping journey that starts with an agent

When a shopper delegates a task to an AI agent, a single request can contain several requirements.

“Find a TV for my mom” might mean a budget under $400, delivery before Saturday, and a remote that is easy to use. Evaluating the options requires product details, pricing, delivery information, and an understanding of what matters to the shopper.

For the retailer, understanding that interaction means connecting the request, the information returned, and the outcome.

A television might fit the budget but arrive too late. Another might be available on time, while its description leaves the remote’s simplicity unclear. These differences matter when deciding which product meets the request.

Control Room is designed to help retailers examine those interactions and identify where their teams can take action.

See how agent activity connects to orders

A central goal of Control Room is to bring agent sessions and associated orders into the same view.

The session workflow is designed around the journey from a captured request to the products returned and the resulting purchase—or the point where the interaction ended.

In the television example, this would help a retailer understand which requirements were addressed, what options were presented, and whether an order followed.

The information available depends on how the agent connects and what it shares. Some connections may provide the shopper’s request or additional context. Others may expose only the catalog query and response.

Connecting those available signals to orders gives retailers a way to investigate the commercial value of agent activity. When a visit ends without a purchase, an unanswered question can provide a specific starting point for investigation.

Fix the product information agents need

A product can meet a shopper’s needs while its catalog entry lacks the information required to establish that match.

Capacity, dimensions, and price may be present. Details about cleaning, compatibility, or warranty coverage may be missing.

Topsort’s Catalog Health capabilities provide a foundation for addressing product information quality. Control Room extends that direction toward the questions agents ask.

Consider the air fryer request. The missing detail is specific: whether the basket is dishwasher safe.

The workflow is designed to surface that unanswered question, connect it to Catalog Health, and let the retailer review and approve an accurate answer for future requests.

The value is practical: identifying a gap in product information and giving the team a way to address it.

Agent questions can also reveal which details matter in a shopping context. “Does this TV have a simple remote?” points to a different information need from screen size or resolution. Capturing that question helps the retailer understand how its catalog could better support product evaluation.

Bring relevant brand offers into agent-led shopping

The television scenario also illustrates how brands could participate in an agent-led purchase.

A product meets the shopper’s requirements. A brand funds a $20 discount, making that option more attractive while keeping the product’s suitability at the center of the decision.

The sponsored-offer workflow is designed to let teams select products, define the offer, and set a budget. Through connections that support offers, eligible interactions could receive a clearly identified sponsored incentive.

Linking offers with associated orders, sales, and brand spend would give retailers and brands a way to evaluate the results.

A relevant offer supports the shopping decision. The television still needs to arrive on time and meet the shopper’s requirements. The commercial opportunity comes from making an appropriate product more appealing.

For retailers, this creates a way to think about brand participation beyond fixed placements: an offer connected to a product and the needs expressed in a shopping request.

Decide how agents access the catalog

Retailers also need a role in managing the relationships behind agent traffic.

A shopping agent requesting information on behalf of a customer serves a different purpose from a bot collecting prices. Those activities may call for different access decisions.

Control Room’s access-management approach centers on allowing or blocking agent connections and setting rules for unverified agents or identified price scrapers.

The scope of those controls depends on how access is handled through the connection. The objective is to give retailers practical ways to act on the activity they observe and decide which interactions they want to support.

Visibility and access management belong together. Understanding what an agent is doing helps a retailer make a more informed decision about its participation.

How Control Room fits into Commerce AI

Commerce AI brings product knowledge, shopper context, and business outcomes into commerce decisions.

Within Topsort’s product direction, T-Brain and Agentic Traffic Control Room address complementary needs.

T-Brain provides commerce intelligence. Its retrieval, prediction, ranking, and understanding capabilities support decisions about which products are relevant and how they should be presented.

Control Room focuses on external agent interactions. Its purpose is to help retailers understand what agents request, identify gaps in the information they receive, and manage offers and access.

These roles connect through a common objective: helping commerce businesses respond to shopper needs with useful information and informed decisions.

Sometimes that requires better product retrieval or ranking. Sometimes it requires a retailer to approve one missing fact about a product. Both matter to the shopping experience.

Control Room brings attention to the operational side of agent-led commerce: the visibility and decisions retailers need as external AI experiences interact with their businesses.

Make agent-led shopping a channel retailers can manage

Retailers need to understand how agent interactions relate to their products, their orders, and their commercial relationships.

The questions are concrete. What did the agent ask? Could the catalog answer? Was a relevant offer available? Did an order follow? Should that connection have access?

Agentic Traffic Control Room is designed around those questions, connecting visibility with actions a retailer can take.

It reflects Topsort’s approach to Commerce AI: helping businesses understand new shopping interactions, improve the information behind them, and retain control over how they participate.

Interested in Agentic Traffic Control Room? Talk to our team about your agentic commerce needs.

Frequently asked questions

What is Agentic Traffic Control Room?

Agentic Traffic Control Room is designed as a workspace for retailers to understand and manage AI shopping agents interacting with their stores. Its focus includes agent sessions and associated orders, catalog information gaps, sponsored offers, and access controls.

What problem does it address?

Retailers need to understand what agents request, whether their product information answers those requests, and how the interactions relate to purchases. Control Room is designed to connect that visibility with decisions about product information, commercial offers, and agent access.

Can it show a shopper’s full conversation with an AI assistant?

The information available depends on the agent connection and what it shares. Some connections may provide shopper requests or additional context; others may expose only catalog queries and responses. Visibility does not imply access to every conversation on an external AI platform.

How does it relate to Catalog Health?

The intended workflow connects unanswered agent questions with catalog information gaps. Retailers can then review the missing details and approve accurate answers for future requests.

How is it different from T-Brain?

T-Brain provides commerce intelligence through retrieval, prediction, ranking, and understanding. Control Room focuses on visibility and retailer control around external agent interactions. They address complementary needs within Topsort’s Commerce AI direction.