AI Call Handling at Scale: Why Multi-Location Systems Fail Without Unified Architecture

By Yaniv Masjedi, Chief Marketing Officer at Nextiva

Businesses that operate out of a single location need to choose carefully and strategically in adopting an AI voice answering service. But for an organization with multiple locations, that challenge can expand exponentially. The opportunities for errors and customer frustrations grow, putting reputational capital on the line.

The right AI call handler can avoid these pitfalls. Here’s how to make the scaling process successful.

The Challenge

A one-site business generally can teach a voice agent the most pertinent information, such as hours of operation, directions, and offerings. Managers determine who should handle which kinds of calls when human intervention is necessary, and program that in easily. All these details can be updated locally at any time.

But if that same business expands from one location to ten, the entire process shifts. Suddenly, the tool becomes an operational backbone for distributed teams. It has to combine general information about the business with location-specific data a caller might want. And it has to direct calls based on factors like peak load balancing and brand governance.

For example, picture this scenario. A customer wants to find out whether a business has a product in stock at a certain location, and how late that location is open. So the customer picks up the phone. (Calls are still the most popular way people across different generations choose to contact brands, surveys find.)

The AI receptionist answers. The caller asks their questions. But the system doesn’t know what’s in stock at each location. It directs the caller to their preferred location. Everyone there is tied up, leaving the caller on hold. Meanwhile, at another branch, five agents are available to speak. The system could transfer the caller there, but those agents lack the site-specific information the caller seeks. This kind of thing happens frequently because businesses still operate in silos, treating locations as islands and limiting or delaying information-sharing.

Research published this year in the American Journal of Interdisciplinary Studies explores these kinds of problems. It examined 68,000 customer service interaction episodes across 132 physical retail and hospitality locations, and specifically noted the challenges “multi-location systems” face.

AI-powered platforms can make a big difference, the study found. “Overall, the findings provided quantitative evidence that AI-enabled customer-interaction models functioned as operational mechanisms that improved service efficiency through faster resolution, higher containment, and reduced repeat contact when deployed within coherent omnichannel service architectures,” wrote author Mohammad Towhidul Islam of Trine University in Indiana.

Unification is the Great Equalizer

This is where a new solution comes in: unified customer experience management (UCXM). It ends these silos, pulling together information from all sites into a single record. It provides every agent, both human and AI, a complete understanding of the customer’s journey, including full records of past interactions on every channel.

A UCXM platform uses all that information to understand the customer and predict their needs. It highlights and summarizes the most important insights so that whoever handles a call can “know” the caller at a single glance. The platform also analyzes the conversation in real time, providing new prompts and ideas for how to resolve the customer’s concerns as quickly as possible based on what the customer is saying, incorporating both spoken and unspoken cues.

The best AI call handler is built to work in a unified ecosystem like this. My team at Nextiva designed XBert, our solution, with the power of UCXM. It includes location-specific greetings and routing rules across any number of locations to ensure that customers can get the information they seek and reach the right team member every time.

With this kind of architecture in place, the entire company shares a single organizational memory. And employees across all departments work in the UCXM, so that any updates are visible immediately across the network.

Here’s how the scenario then plays out. When a customer calls, the AI agent recognizes who they are, knows their interaction history with the brand, and has access to all the most pertinent information from all locations. It combines that data to deliver personalized, effortless interaction. The customer finds out about availability instantly, heads off to the store, and makes the purchase.

The result is the holy grail of CX: a seamless, enjoyable, memorable customer journey.