The Unwired Exchange: 24/7 Customer Engagement and AI Call Centers - Francesco Decamilli, CEO of Uniti AI speaks about AI in Self-Storage
Welcome to The Unwired Exchange, where we spotlight the trailblazers shaping the future of self-storage. In this edition, we speak with Francesco Decamilli, CEO of Uniti AI, a company at the forefront of AI-driven customer engagement.
As self-storage operators face growing expectations for round-the-clock responsiveness, Francesco shares his insights on how AI call centers are transforming the way facilities connect with customers — improving efficiency, boosting conversions, and keeping operations running 24/7.
Please tell us a little bit about yourself and Uniti AI.
I'm Francesco Decamilli. I'm the co-founder and CEO of Uniti AI. We are an AI contact center for self-storage operators. We do multichannel customer engagement across email, text message, website, chat, and phone. Our primary goal is to help operators create a more efficient and cost-effective way to convert and engage prospective customers in a more efficient way. By leveraging AI to manage customer communication, we can deliver a better customer experience.
How can self-storage operators benefit from Uniti AI?
The number one pain point we hear from self-storage operators concerns inbound lead conversion. Specifically, not having strong enough systems in place that enable them to 24/7 instantly engage their leads. They see a lot of drop-off in leads who call out of hours. I think OpenTech Alliance has estimated that six in ten storage leads will go with the first operator that gets back to them. And something like 60% of calls come in after hours. So when you take these two things, it creates a very clear picture for operators why 24/7 is important.
Our solution helps storage operators quickly engage leads at all hours of the day, across multiple channels. What we found is that some leads prefer to interact via text message, others prefer to rent by phone, and yet others prefer email. You have to really combine all of the channels to see the highest overall engagement and conversion rates. That's really what we're after.
On the sales side, most operators today have in place either in-house or outsourced call centers that manage sales and support. About 80% of calls are typically service and support calls. People need to make payments, they are locked out, or need to make a change to their existing lease. That is a clear opportunity for AI to provide a more cost-effective solution to handle those types of requests compared to a call center. A call center has a place within the organization, but it should focus more on higher-value leads looking for sales, and AI should handle service and support.
What other areas of self-storage operations would also benefit from implementing AI solutions?
An area that really could benefit from AI is collections: sending out invoices or reminders, or making calls to clients overdue on payments. AI can play a role from the beginning to the end of the customer journey of a lead. Today, we're primarily focused on getting more leads into the building. But I think there's a role for AI in keeping leads in the building by reaching out every three or six months or checking in whether they need anything. If they're overdue on their balance, AI can help them with a payment plan and ensure a strong collections effort is in place for the operator. Having an AI workforce that complements your human staff is very important. Your human staff will still be needed. You might need fewer but higher qualified people working with a fleet of AI agents to perform tasks that are core workflows within the customer journey.
The other area, which is outside of what we do, is AI reporting and analytics. Many operators have reporting responsibilities, and there's a high burden in creating the right reports to share with management. AI can do a lot of the heavy lifting. When integrated with the facility management platforms, operators could almost talk to these solutions and tell them which report they need generated. For example, generating occupancy reports or comparing move-ins by month. This kind of on-demand, spin-up reporting is another key area that AI can support.
There are many benefits to AI solutions. However, implementing them will always be a little bit disruptive to existing operations because it is adding a new system and new processes. How difficult is the transition, and how can it be made easier?
First and foremost, the transition requires a champion driving the process, who is a senior stakeholder in the organization. AI is not only disruptive, it can be nerve-wracking. It causes instability, and sometimes the behavior of the AI can be unexpected, creating hallucinated outputs. A lot of the anxiety also comes from uncertainty over job loss or insecurity. It's important to have a senior champion managing AI change, putting it in context by showing it's not replacing jobs but solving specific pain points. Everybody would love it if AI could take that grunt work off their plate, and that's what we're going to use it for.
From there, start small. Don't expect AI to handle all tasks, like move-ins, support, collections, and reporting, from day one. Pick one area and start there. Many customers get a lot of calls after hours, currently going to a call center. What if these were routed to an AI agent, which is less expensive? If this goes well, move into phase two: introduce AI during business hours as a rollover, then make it the first line of offense for answering sales, and eventually handle support and collections. Focus on different customer lifecycle stages as you get more comfortable with AI.