Every contact center has calls that follow the same pattern. Where is my payment? What are your hours? How do I reset my access? Those calls matter to the customer, but they keep skilled agents away from the problems that really need a person.
AI virtual assistants promise to handle that routine work. The promise is easy to make and harder to deliver. So it helps to look at a real, published example. This article walks through Vonage’s case study on Associa and pulls out practical lessons for teams thinking about the Vonage AI Virtual Assistant or similar tools.
All figures below come from Vonage’s published customer story. We have not added any numbers of our own.
Who Associa is
According to the case study, Associa manages community and homeowner associations, with 50 branches managing thousands of communities. Its centralized Customer Care and Accountability team is the front line for homeowner calls and questions.
The problem
The case study describes a tough starting point. Callers were waiting three to four hours at peak. Abandonment was high, customers were frustrated, and agents were burning out. The existing call center setup was disjointed, which made it hard to route calls well, track performance consistently, or give agents what they needed to solve issues the first time.
Repeat callers made up 15-20% of total call volume. That is a strong sign that people were not getting answers on the first try.
What they implemented
Associa deployed Vonage Contact Center (VCC) together with Vonage AI Virtual Assistant. VCC gave the team unified operations, real-time visibility for supervisors, and smarter routing. The virtual assistant handled the most common, repetitive homeowner questions so agents could focus on complex, personal cases.
One detail stands out. Associa’s Director of Customer Care says in the case study that the team was initially skeptical of non-human support, and worked closely with Vonage engineers to design a solution that handled repetitive tasks while keeping a human touch. Customers who want a person can get one. Customers who want a quick answer can serve themselves.
The published results
- Call deflection of 46-48%. Associa had expected 30-35%.
- Average hold times reduced from peak waits of 3-4 hours to 31 seconds.
- Repeat callers fell from 15-20% of total volume to 7%.
Those are big numbers. As always, your results depend on your call mix, processes, and setup. But the pattern is worth studying.
Lesson 1: Start with the repetitive questions
The assistant was aimed at the most common, repetitive questions, not at everything. That is the right place to start. Pull a few weeks of call reasons, group them, and find the handful that are high volume and simple to answer. Those are your first automation candidates.
Lesson 2: Always offer a way out
Associa’s design let customers reach a person if they wanted one. That matters. A virtual assistant that traps people in loops will hurt satisfaction and push callers to other channels. Make “talk to an agent” easy, and make sure the agent receives the context so the customer does not repeat themselves.
Lesson 3: Fix routing at the same time
The case study credits VCC with smarter routing and real-time visibility as well as the virtual assistant. Automation works best on top of good routing. If your queues are poorly designed, a bot only moves the problem around. Our guide to omnichannel contact centers explains how unified routing works.
Lesson 4: Measure repeat contacts, not just deflection
Deflection is the headline figure, but the drop in repeat callers is just as telling. If deflected callers come straight back, you have not really solved anything. Track repeat contacts within a set number of days, and check that customers who used self-service are not calling back about the same issue.
Lesson 5: Involve the people who answer the calls
Associa worked closely with engineers to shape the design. Your agents know which questions are routine and which only look routine. Involve them in choosing use cases, writing answers, and reviewing transcripts after launch.
Lesson 6: Set a realistic target, then iterate
Associa set a target, measured against it, and exceeded it. Pick a clear goal for your first phase, such as a deflection rate for specific call types, and review it every few weeks. Adjust prompts, answers, and handoffs based on what you see.
How this fits with Salesforce
For teams on Salesforce, VCC runs with Salesforce as the agent desktop, so handoffs from the assistant to an agent arrive alongside the customer record. Read more in Vonage Contact Center for Salesforce. If you are also planning an Open CTI migration before Salesforce’s February 28, 2028 retirement date, our Open CTI migration paths guide is a good companion.
A simple first-phase plan
- Pull call reasons for the last 30 to 60 days.
- Pick three to five high-volume, low-complexity call types.
- Write clear answers and decide when to hand off.
- Launch on one line or customer group.
- Track deflection, repeat contacts, hold times, and satisfaction.
- Review transcripts weekly and improve.
Cost matters here too. Self-service can change how many agent hours you need. Our article on Vonage Contact Center pricing covers what affects the overall budget.
The bottom line
Associa’s published story shows what is possible when an AI virtual assistant is aimed at the right calls, paired with good routing, and designed with a clear path to a human. The lessons apply well beyond homeowner associations. To see how the platform works, visit our Vonage Contact Center page.
Get connected to a Vonage expert – free consultation
Curious what an AI virtual assistant could handle for your team? xRapid Media LLP is a High Tech B2B Marketing company and Vonage channel partner. Book a demo with a Vonage expert with 20 years of experience.
xRapid Media LLP is an independent company and Vonage channel partner; it is not Vonage. Vonage, Salesforce, AppExchange, WhatsApp and Gartner are trademarks of their respective owners. Customer results are as published by Vonage.