How Extra Space Storage cut coaching prep down to minutes with Level AI's AI Workers
Extra Space Storage's 500-person contact center generates a substantial volume of conversation data every day. Terry Porter, who leads quality and analytics, has been using Level AI for nearly three years. The recent addition of AI Workers has changed how his team turns that data into action.
This is the story of how two AI Workers, Coaching Plan Worker and Conversation Research Worker, became part of the daily operating rhythm at Extra Space Storage.
The old way: Two hours to build an individual coaching plan
When a frontline leader at Extra Space Storage suspected an agent was doing something they wanted to reinforce or correct, the leader had to find examples of it. One call would not be enough. A leader needed several examples of the same behavior to bring to a coaching conversation, and assembling those examples meant digging through phone calls until the pattern was visible.
Before, they would listen to phone calls for an hour, two hours to try and replicate a behavior that they thought was something that needed to be corrected.
The cost wasn't only the time. It was the quality of the coaching that came out the other side. Agents would push back on a single example, and the leader had limited ammunition to respond. The conversation often stalled at the same point: one call versus an agent's defense or excuse for it.
Coaching Plan Worker automates that two-hour investigation and subsequent coaching plan. A frontline leader gives the agent guidelines and the coaching plan structure, and the AI Worker returns a ready-to-execute coaching plan with examples from across the underlying transcripts.
The shift this creates inside a coaching conversation is what Terry highlights most often.
"A lot of frontline agents will say,' You just pulled that one bad phone call. But with this Coaching Plan Worker, I can give you 10 more examples of how it's not just that one phone call that reinforces that this is a trend that we need to correct, and we do that quickly."
The leader walks in with evidence. The agent sees a pattern, not a snapshot. The coaching moves from a debate over one example to a discussion of how to change a recurring behavior.
For a team lead carrying 10 agents and running one coaching per agent per week, the saved hours compound across the month. Terry estimates the efficiency Level AI creates could absorb as many as six to seven additional agents per team lead.
Conversation Research Worker Enable Ad Hoc Investigations Without Building Tags
Coaching Plan Worker handles the coaching workflow. Level AI’s Conversation Research Worker handles everything else that lands on Terry's desk as an ad hoc analytics request.
Extra Space Storage's stakeholders include UX, web design, revenue management, and data science teams that come to Terry's group looking for evidence about customer behavior. Before Conversation Research Worker, fulfilling those requests meant building a new tag in the platform, waiting for it to accumulate data, and then accuracy-testing it against the most recent interactions, which is a fraction of what Extra Space Storage takes in any given month.
Conversation Research Worker bypasses that cycle. Terry prompts the AI Worker against the existing transcript dataset and gets the answer back without building new infrastructure first.
Recently, the AI Workers tool has been a game changer for our frontline leaders and myself included. I can go in and quickly prompt out data that isn't something that comes up every day. It's very ad hoc, but I can get some pretty solid data.
Why AI Workers Have Expanded the Value of Voice of the Customer Insights
The most telling sign of how central Level AI’s AI Workers has become at Extra Space Storage is how it has changed Terry's relationship with another part of the platform.
"With all the different AI workers that are in there, it almost makes VoC insights hard to want to use because I can just go prompt everything out of it that I need."
The point isn't that Voice of the Customer stopped being useful. The point is that AI Workers gives Terry a single interaction model for almost every question he needs to answer against his VoC data. Ask the question. Get the answer. It’s the future of how we interact with enterprise software.
The Pattern AI Workers Enable
The Extra Space Storage deployment shows a consistent pattern across both AI Workers in regular use:
A leader has a question. The question used to require hours of manual review, a new tag build, or an analyst request to answer. An AI Worker now answers it against the same underlying transcripts in the time it takes to write a prompt.
The result is not just time savings on existing work. It's the work that gets done at all. A coaching that would have been skipped because the evidence took too long to assemble now happens. A stakeholder question that would have been deferred until the next tag accumulated enough data gets answered the same day.
Terry's framing of what changed is the cleanest version of it: "We were able to quickly support the thought or the trend we think's there with evidence for those agents."
That's the operational shift AI Workers deliver at Extra Space Storage. Suspicion becomes substantiated evidence in minutes, not hours, and the team acts on what they find while it still matters.
Want to evidence coaching plans the way Extra Space Storage does? Request a demo
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