One of the biggest success factors for SMB AI integrations is if it can offload or automate the tedious daily tasks that they dread. Compared to past emerging tech that they may have viewed as tech-for-tech-sake, automating daily annoyances addresses common pain points in tangible ways.
One of those functions was invoked several times at Localogy’s L26 event over the past two days: responding to reviews. This task carries the lethal combination of growing importance and neglected execution. SMBs want to spend their time being dentists and nail artists, not digital marketers.
Automating the task of responding to reviews can solve these issues by both taking it off SMBs’ plates and ensuring that it happens in a timely manner. For the latter, one of the factors that AI engines increasingly weigh is recency. That applies to user reviews and the dialogues brands can have through review channels.
SOCi calls this freshness, and it’s a key factor in AI search. AI engines are doing a better job than Google, says SOCi CMO Monica Ho, in synthesizing up-to-date chatter in Yelp reviews. So SMB engagement and dialogues in review channels can help them steer the narrative and boost their AI engine visibility.
But though this addresses the need for speed, a red flag persists: ability. Can AI respond in natural-sounding ways? Many SMBs don’t want AI conversing with their customers, said Tiger Pistol’s Joe Nathan. These well-founded trust issues compel hybrid approaches with some manual oversight.
Cracking the Code
SOCi is getting creative to crack this code. It trains AI models on the ‘voice’ of a multi-location business and its brand guidelines. It then deploys those “parent” models on a per-location “child” level to learn local nuances. Those nuances include things like regional colloquialisms, and the way the business talks.
All the above is underscored by the growing importance of reviews, AI engines increasingly use reviews as a citation and source of truth. This is partly driven by AI search behavior. Queries made in natural language are longer and more nuanced, which requires AI engines to dig deeper for answers.
And one place they’re digging deeper is reviews (and Reddit). This is where they can find answers to complex questions like “I need a dentist that works with kids, and my son is terrified of going to the dentist.” Queries like this need to synthesize lots of sentiment to find qualities like bedside manner.
To quantify the assertion around more nuanced and conversational queries, SOCi found in its Local Visibility Index that AI-engine queries are up to 6x the length of traditional search queries. We’ve been trained for so long to search in caveman-speak, but AI engines are unlocking natural language.
So with that emphasis on reviews comes an amplified need to engage with customers in reviews channels like Yelp. And that brings us back to the ability to automate responding to reviews. This opportunity will only grow as underlying models get better, and as local businesses put AI on a longer leash.
