Last week I wrote a piece noting how my wife Michelle’s Google usage was down by nearly two thirds, thanks to her discovery of ChatGPT. I noted that Michelle isn’t exactly an early adopter – but that’s not entirely true. Michelle is more of a harbinger – if an early tech product “fits” her, she’ll adopt it early and often – and it’s usually a winner once it goes mainstream. The early Tivo DVRs come to mind – and they remain a better product than anything that’s come since in the television world (another example of how entrenched business models kill innovation).
But few early versions of any new product get to “Michelle market fit” on first attempt. For it to happen with an AI chatbot – well before I developed the habit – is rarer still. I mean, I’m supposed to be the early adopter around here!
So once I noticed Michelle was hooked, I asked her how she wrangles ChatGPT. As I noted in my last post, the majority of her usage focuses on information-intensive projects that tend to get messy when attempted with Google. For example, Michelle’s managing a real estate project with a complex set of inputs. The property requires extensive renovations but must conform to certain community regulations and standards. With the summer rental season approaching, she needs to make scores of decisions on everything from paint colors to septic system contractors. Prior to ChatGPT, Michelle would have started her searches inside Google, but quickly been frustrated by “content cruft” – reams of crappy results and, in her words, “way too many ads.” For commercial searches about household appliances, construction projects, landscaping ideas, and the like, Google’s index favors the kind of content created by “advertising mills” – cheap, low calorie stuff that crowds out the kind of trusted advice Michelle is seeking. She knows she’s being steered into choices that create profit for Google’s ecosystem.
Faced with those kinds of results, Michelle is more likely to call a friend who has already done what she’s looking to do, get one simple answer (even if it’s not exactly right), and go with it. And this is the first insight that springs to mind when I talk to Michelle about ChatGPT. For her, the service has become the equivalent of a “first phone call” for a competent point of view, minus the cruft. It’s as if OpenAI has culled most of the crap from the content mills that have larded up Google, and delivers only the good stuff.
Continuing along those lines, Michelle tells me she’s found a hack of sorts – she’ll ask ChatGPT for that competent first answer, then ask it to name top design blogs that focus on her particular query. Then she’ll dig into those sites, and more often than not, she’ll find confirmation of ChatGPT’s advice, or sometimes even better ideas. This is how, for example, she figured out which shade of paint would work for the property she’s working on. Here’s ChatGPT answering her query about two very specific paint choices:
In a darker home on the beach that faces east in New England, I would recommend using Benjamin Moore’s White Dove (OC-17) over Simply White (OC-117). The subtle gray undertone in White Dove can help to balance the natural light coming in from the east-facing windows, while the higher LRV of 85 can reflect more light and create a brighter and more spacious feel in the darker home.
Using a purer white like Simply White in a darker home can sometimes make the space feel stark and cold, especially if there’s not a lot of natural light coming in.
I mean, the confidence!
When I asked Michelle if she was worried that ChatGPT might sometimes be full of shit, she responded that in the end, she got what she wanted, a confident response that she could then put to the test in other ways – talking to folks at the paint store, friends who are designers, the aforementioned design blogs. And she got it in a few minutes – with no Google sludge to wade through. “The complexity of the questions that I can ask,” Michelle told me, “and the nuance in the answers that my questions can provoke, if asked the right way, is what hits right and keeps me asking even more. Plus, it’s such a relief to not have to scroll through all the ads and sponsored links.”
The implications here are pretty significant, given that these kinds of commercial searches drive a significant share of Google’s search margins. As long as OpenAI avoids an advertising model, its results will convincingly outshine Google’s in this category. This argues for refining the subscription model OpenAI is already pursuing, and will likely inform whatever Google’s been working on feverishly these past few months. Were I Google, I’d quickly launch a ChatGPT competitor that was free of ads, matched ChatGPT’s subscription offering feature for feature, and for the first year or two, is free to use. I’d market it as far superior to OpenAI because it’s updated by Google’s core search index – a differentiator against Bing Chat as well. Then, as the service gains millions of users, I’d slowly introduce premium upgrades – just as the company has done with Gmail and its office suite. Were that to happen, I’m pretty sure Michelle would become a paying customer – and so would I.
One last note: Michelle is keenly aware that OpenAI is building a formidable dataset on her queries, including information she said she’d usually not share with Google or any online service. This concerns her, and should concern us all – but that’s fodder for another post.