Published November 6th, 2025

The story starts at a front door. A Vivint tech finishes the install, wipes his hands, and taps his NFC badge. “Before I head out—would you mind leaving a quick note with my name so my manager knows I took good care of you?” The customer scans. Thirty seconds later, a review lands with the tech’s name, the service (“same-day install”), and the city. Multiply that moment by thousands of visits a day, across 400 locations, and you get the heartbeat of Vivint’s employee-powered reputation engine.

Before this shift, reviews showed up when they showed up—random, lumpy, and hard to coach. Conversion rates through automated software were below 10%. At a high level, everyone in the business knew that reviews matter; nobody really owned it, though. So the team made it simple for the frontline. Badges and links tied every review to a person. Micro-scripts kept the “ask” natural. Suddenly, sales people and technicians alike were quantifiably building the business in a way Vivint had yet to see.

The first week felt like a spark. Mentions of individual techs climbed. Photos showed real jobs, real people. Then velocity kicked in. Over 6 months, ~75,000 new reviews rolled in. Top performers brought in more than 200, alone. You could watch the culture grow in real time: Technicians, C-Suite, and sales people celebrated climbing the review leaderboard, one great interaction at a time.

Attribution didn’t just motivate. Attribution clarified coaching, it brought visibility. Leaders could see attempts to get reviews, published reviews with and without name mentions attributed, and which words customers echoed back (“on time,” “clean install,” “same-day”). A-players weren’t a mystery anymore; even better, their habits were teachable. Two ride-alongs with a top performer did more than any all-hands talk track. SPIFs rewarded the action (verified asks and published reviews of any rating), stayed within platform and FTC guidelines, and built momentum with simple tiers. The flywheel turned because it was fair.

The bottom line: Vivint rose to the top of AI Overview, three-pack, and reviews. When customers asked ChatGPT, Gemini, Perplexity, or Siri for “best home security near me,” Vivint began appearing more often, and with better justifications (“4.9★ last 90 days,” “same-day install,” “licensed”). Inside the team, the SOAR curve—the share of non-branded queries where an assistant recommended Vivint—bent upward week after week. Even with conservative math, that visibility translated into a real pipeline: more high-intent calls, more booked visits, fewer dollars needed to buy the same attention. Maybe more importantly, retention continues to rise as less people fall away because of bad reviews.

Here’s how the numbers felt on the ground. With assistant discovery in the hundreds of thousands per month across the footprint, a meaningful SOAR lift plus a small bump in click-through turned into hundreds of extra inquiries every month. Keep the close rate steady and you’re looking at a step-change in new customers. Layer on the mix shift—less paid, more earned—and CAC eased without slowing growth. The reviews weren’t vanity; they were working capital for the brand.

The cake isn’t done baking at Vivint. This is a multi-year effort that is ahead of schedule. As reviews continue to flood in, Vivint is turning high velocity into high optimism for the AI era.

So far in the Cheers x Vivint experience, Vivint is delighted by being at the top without paying nearly the same as competitors offering a worse experience. Vivint employees are constantly clad in Cheers badges and eager to collect feedback on their performance. As Vivint continues to utilize Cheers, the sky is the limit.