By driving the cost of AR app development and the total cost of ownership of smart devices down, Upskill is poised to change the axis upon which their enterprise clients compete.
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In 2010, roughly 8.3% of US consumers, or 19 million people, were considered ‘unscorable’ by FICO, a credit rating service whose models serve as a key underpinning of the US system for assessing credit worthiness.[1] Included in this contingent of [...]
Kaggle’s recent acquisition by Google casts doubt on the viability of crowd-sourced expertise as a service. What went wrong?
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Great question, Felix. I haven’t looked at the data, but it would be interesting to see if there is any shuffling in the rankings of the top Kagglers. My understanding is that the community has been consistently growing — hopefully that has been evenly distributed among experts and newbies.
Spot on, Gil! The need is significant here, and to your point, I’m especially interested to see how their loans perform in the event of another recession (hopefully not anytime soon). This will show us how effective their models really are.
They definitely keep their model details close to their chest as that has been defining their competitive advantage to date. Over time, the data they collect on their loan performance will create greater value, but given the recency of their loan issuances, many have yet to complete a full term’s worth of data.
Yep, commented briefly on the ZAML pivot at the end of the post and I agree 100% on the challenges of the existing model — payday lending in general is just not a great place to be in given inevitable regulatory uncertainty. Key will be understanding if ZAML finds a recurring need among its customers.
Thanks, Yao. I imagine many of the variables are quite transferable, ie income, hours of the day searches are conducted. My understanding is that they cannot take their China data out of China, so that likely limits their analysis in a cross-border context.
RIGHT?! Many of the other variables are ones you’d expect: income, zip code, default history, etc.
Great question. ZestFinance closely monitors their models to ensure they aren’t systematically discriminating against certain classes. That said, it’s unclear to me how payday lenders ultimately defend themselves here as the demographics of their accepted applicants are likely quite homogeneous.
This is so cool! It will be interesting to see if the customers who miss out on buying festival tickets will be the same ones who would invest in a headset and WaveVR experience. My initial hunch is no, but who knows!
Wonder if there’s also a value creation opportunity here from the B2B side: namely, helping content creators co-innovate with their end user through a new platform. A lot of the DJ light shows and instrumentals can feel similar, esp for EDM, so this could be a way to cheaply experiment. And as you pointed out, it’s much easier to charge on this end than on the consumer end!
Interesting stuff! Any idea how these guys prioritize content development across these various use cases? My initial thought would be to go deep into one area to maximize the data collected and resulting value-add they can deliver to their end user. I imagine there is additional overhead here in ‘training’ customers on how to use the product, which is another cost to consider alongside content development.
Cool post, Tomo! Given the clear barriers to adoption, curious if the company has explored other revenue opportunities by positioning itself as a training tool more so than one that used in practice? This could derisk a hospital’s decision to purchae it, and perhaps get folks comfortable using it to drive broader adoption in the future.
Super interesting stuff. Palantir has had some public shakeups with clients who have decided not to continue past the pilot phase of an engagement. Wonder if this means Palantir is best applied for some verticals and not others. Would be interesting to know what ROI Palantir is able to demonstrate for its successful client engagements vs.the others.
Super interesting! Wonder if this has an impact on real estate investors who acquire property for primarily financial gain. We’d probably see prices inflate at a slower pace. Will be interesting to watch what happens to these guys as transaction liquidity that’s critical to their business may be hard to sustain.
Super cool stuff. Do we have any sense for the degree of coupon conversion? Of course it will be imperfect given that customers may not always use the coupon at the point of purchase, etc, but I’d want to know as someone working on this campaign. And I wonder how rich of an inventory of coupons needs to be maintained by Target to retain continued customer interest. Discount fatigue!
Agree these guys provide key transparency in a market that is generally lacking in adequate reference points. I imagine the struggle here is that users may not be using contractor services frequently enough to justify an ongoing subscription. To ensure reviews are evenly submittedbetween new and returning users, I wonder if they could employ a give to get model – users can only see reviews if they submit.
Cheesy garlic bread ftw. It seems like a lot of these campaigns have a pretty negligible impact on R&D. Wonder how much of this is truly to get ideas vs simply engaging with a customer segment that might otherwise be disengaged.
Interesting post. Curious to know which of the incentive structures are most popular. The rewards-based approach seems a bit perverse in that maybe we should be donating purely out of the goodness of our hearts, but I could see people gravitating toward that option.
Great post! It feels like platforms like these are commoditizing what feels ‘homemade’ and ‘artisanal’. Wonder how/if Etsy helps its retailers expand their inventory to stay unique and retain customers.
Curious what Prosper’s loan success rate will look like once we have enough years of data to look back on — most loans have multi-year terms. Also curious what their marketplace means for equality and inclusion; how do they ensure the algorithms aren’t systematically disicriminating against certain underserved segments to preserve a certain default rate?
It’s pretty cool how companies can essentially outsource data science development work to the Kaggle community. I remember they launched a specialized consulting service for the oil & gas industry a while back, but had to shut it down due to market cyclicality. Wonder why they haven’t pursued it across a broader set of verticals.
Definitely struggle with how Venmo captures value. Would it have survived as a standalone company long term if it hadn’t been acquired? If I were a merchant, I’d be curious to know how I could extract value from data in Venmo’s social feed, ie which users who are always splitting late night pizza bills. Maybe they’ll one day introduce better tagging in the feed to facilitate another monetization stream.
Your last point makes me wonder if Quirky could become the overarching layer inventors use to track and manage their invention workflows, from initial demand measurement, usability testing to production. Seems like the problem they’re really looking to solve is how to make ideas successful for inventors without lots of resources. Quirkly could become the tool they plug existing point solutions into (ie your usertesting.com results or kickstarter data) to bring these ideas to fruition.
This post makes me wonder if traditional publishers like Penguin can exercise their unique ability to hone and shape successful stories from their initial script stage more effectively to beat Amazon. There’s so much marketing that goes into how a book is crafted, down to the colors and fonts of its cover. Perhaps the way Penguin competes now is by providing a value-added, agency-like service to budding writers or established ones looking to easily advertise their books with the right channel partners and retailers.