I had a similar thought to Sasha – no matter how effective the tool is at matching consumers with products, the brand has to resonate with consumers if they are going to try it in the first place, let alone make a purchase off of the results. I think it’s easy to look at what Sephora has done with ColorIQ, for instance, and assume that something similar would work here…but I see the context as fundamentally different because Sephora is trying to increase sales among their existing consumers, whereas it seems Olay is trying to re-earn a spot on consumers’ consideration sets.
I think that what CircleUp is doing is super cool, especially for the point you raised around female investors and the potential elimination of biases pervasive throughout the fundraising process. My only concern is about the dependencies upon partners and data sources in general – if you don’t own and generate all of your own data inputs, how can you be confident that they’re not going to dry up? What happens if Nielsen decides they want a piece of the pie and pulls the plug on the partnership? What if some of your data providers themselves lose funding (as happened to me when one of my main sources of K12 school enrollment data used lost funding from the federal government last year)? Data risks certainly aren’t a reason to shy away from making data-driven decisions, but if I were investing in a fund that was making investment decisions largely on the basis of Helio recommendations, I would want to know that they have a plan to keep deploying capital even if Helio breaks down.
I wonder if what looks like lack of aspiration is to some extent an effort to set expectations low – I suspect that the implementation of any new technology comes with great risk that cost savings have been mis-forecast (similar to what happened at Fuyao Glass, where the protagonist mentioned they did not accurately anticipate the costs associated with fulfilling the job out of the U.S. facilities). As a company facing a lot of analyst and shareholder scrutiny right now, I wonder if the $2-3m is setting a low bar to clear and avoid further disappointing these audiences.
I’m curious whether this is truly an issue of mistrust, so much as it is an issue of irrelevance. I have only my own experience to draw on here, but I’ve always considered my bank perfectly trustworthy but just not well-equipped to offer any sort of financial advice. I think the survey results cited at the beginning support this.
While making investments in great AI is one way to build a great product, I also think it is a bit beyond the scope of understanding for the average consumer; I can’t be told exactly what it is you are doing with AI, so I just need to be shown that you are doing something that seems to fit my expectations. Banks need to think about what the real KPC’s are – if not trust or incredible AI, then what? User interface? Customer service? – and design around that, creating a product that is truly great to use. I suspect it doesn’t matter if you have the best AI in the world, if the UX is crap.
This was an interested initiative to feature – thank you for sharing it! I think there are some examples of municipalities who have already embraced this concept, albeit in less tech-enabled ways. Cambridge gets very excited about their participatory budgeting initiatives (https://pb.cambridgema.gov/), and some great ideas have come through that channel, including the residential composting. I find it notable, however, that participation is so low; Cambridge – a fairly civically-engaged town- had only 6.8k residents participate last year. Motivating residents, whether it be at the local or national level, to engage in innovation when we can barely get them to vote feels like a tremendous challenge.
I’m glad you mentioned the open question of what will happen to the 3.5m store clerks currently employed in the U.S. I worry that there is an extreme version of the future where this technology is rolled out rapidly and with multiple retailers (especially lower-service, higher-velocity retailers which we often see in lower-income communities), and suddenly a large chunk of your community is un/underemployed and therefore reduce their spending with local retailer – in which case we have a bunch of people without jobs and a bunch of stores that are having a hard time staying open because they aren’t generating income.