Another fantastic AIM Conference is in the books. Each year, the event grows in both scale and influence, and this year was no exception. The content program reflected an industry learning quickly in a fast-changing technology environment. Much remains unsettled about what this means for apartment marketing, but several sessions explored important emerging questions. Unsurprisingly, the growing role of LLMs in apartment search took center stage.
It was a topic that came up during a panel that I moderated on Tuesday afternoon, conveniently scheduled immediately after the highly popular tequila luge that was organized by Opiniion (it was Cinco de Mayo!) The line dispersed to allow an engaging discussion about two important AI topics that have come up frequently in these pages over the last few months: resident sentiment and how it is increasingly driving automation in property management.
Sharing the (Review) Love
Tiffany Walsh of Nolan Living shared that since rolling out their AI concierge service, they had seen not only an uptick in the number of Google reviews at their properties, but also far more detailed review content. The ability to chat with residents about their experience not only discloses their feelings about the interaction, it also seems to encourage them to share the details on Google.
It begs an important question: What is the benefit of the improved Google review content? One answer to that question had already been given in an interesting session a day earlier, given by Turner Batdorf of J Turner Research. In his session “Star Ratings are Dead: Why Your Google Rating is no Longer the End-All-Be-All,” he presented compelling research into the role that both review scores and review content have on prospects’ likelihood to rent.
The gist of the research is that review scores and content have increasingly different roles in apartment search. As more prospects use LLMs for apartment search, shoppers seem to be using them to summarize review content. The research demonstrated a “reputation tax” that can be levied by even a small number of bad reviews. A couple of mentions of security, pest or charge-related issues drastically reduces the likelihood of renting, even in a property with a healthy review count and a 4.9-star rating.
The takeaway from the (very good) J Turner Research session was that reviews play a largely confirmatory role in apartment search and, in that context, review content matters more than scores. In my sentiment panel, Maria Banks of AMLI Residential made the important point that a significant share of LLM input data comes from Reddit rather than Google. That means the relevance of review data depends heavily on the specifics of the apartment shopper’s prompt. Based on the conversations at this year’s show, the industry is still in the early stages of understanding what that means.
What the LLMs Are Telling Us
Which brings us to one of my favorite sessions at this year’s show. Matthew Woods, CEO of ApartmentList, shared an excellent piece of research conducted in collaboration with Profound, (a leading AI-search agency) into shopping habits for LLM-based apartment search. Unsurprisingly, the research showed how renters appear to be using AI less like a keyword search engine and more like a conversational advisor for highly specific local questions.
What was more surprising was how some of the conversations started. The highest proportion of conversations began not with the features of the apartment, community or neighborhood, but with a question about affordability or rent payment. Woods described the transition from SEO to “AEO” (answer engine optimization) as multifamily marketing’s “blackberry moment,” likening the disruption of LLM-based search to the obsolescence that followed the launch of the iPhone.
The research suggests that winning in this environment depends less on generic traffic acquisition and more on becoming a trusted, citable source for nuanced renter guidance. Apartment List reportedly doubled its AI citations within weeks by optimizing content for renter intent, local expertise, and AI visibility analytics. The difference was summarized succinctly: “SEO is about getting found - Answer engine optimization is about being understood.”
What We’re Learning About Fee Transparency
And finally, the hot industry topic of fee transparency was well covered in an engaging session, also based on some new research. In today’s renter-friendly regulatory environment, it makes sense for operators to get ahead of legislation that demands greater clarity in the presentation of prices. This panel presented real-world evidence that we should regard this as a marketing opportunity.
Brandy Daniel, the Chief Strategy Officer of BH, shared findings from their test of fee transparency (more details available here), some of which were surprising. Overall, the results were highly positive, but clearly resulted in some different leasing behaviors. Daniel described “turning the funnel into a tunnel” as clearer pricing resulted in better-qualified leads. This observation appears to be supported by a 4% drop in delinquency at test properties, as better-informed renters make better decisions about what they can afford.
Fee transparency also factored into a lively Q&A session that I ran on behalf of my friends at Renew, where we probed “What Renewals Can Be.” The large and diverse group of participants shared views that tell us: a/ that lots of companies are attempting to improve renewal processes substantially; and b/ there remains plenty of opportunity for improvement. There will be a more detailed analysis of this point coming to 20for20 in the coming weeks.
In the meantime, many thanks as always to Steve and Dennis for curating another highly energetic and rewarding event. It remains one of the absolute highlights of the year in multifamily.