Karen RR

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Pinterest Needs to Improve Revenue Per User Ahead of IPO
Karen RR
Last modified on November 13, 2018 at 11:51 pm
Pinterest's userbase is growing faster than its publicly-traded peers, but the company lags in revenue per user. I exam their existing machine learning infrastructure and recommend how to use it improve revenue growth ahead of their 2019 IPO.

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On November 15, 2018, Karen RR commented on Juul Labs: Transforming Vaping through Open Innovation :

Very objective article on an admittedly controversial subject. I agree with your suggestion the Juul needs to use more open source innovation to interact with their client base. First, it should decide it’s target market: does it want to get current cigarette smokers to switch onto their device as you allude to, or capture a new market who no longer think that cigarettes are “cool”, but may be interested in this product. Once they have their target group, I agree with your recommendation about asking the end user about what they want to see in their product. I think you also touched on an important topic about the supply chain. As you mentioned, most e-cigarettes are sold at bodegas and small stores. Perhaps Juul can work with larger stores and major distributors to innovate their product in a way that makes it acceptable to be sold in larger, more mainstream stores (with legal implications in mind).

On November 15, 2018, Karen RR commented on Ministry of Supply: Using 3D Printing and AI in clothing :

This is so cool! I love the idea of revolutionizing the fashion industry and clothing production model using innovation. As you pointed out, this creates a clearly superior product. In addition to that, it also reduces the need for manual labour. The production process for clothing has always struck me as one of the most archaic. A picture of hundreds of workers sitting in front of sewing machines would have represented a clothing plant in the 1950s, and would still accurately represent a clothing plant today. This is pushing the production process further and further down the labour pay spectrum into arguably predatory areas. Howerever, I could see push back from large textile labour unions to protect the jobs of their workers. However, I expect this to be far into the future as it should take a long time before costs of this production method become low enough to trickle into that labour spectrum.

To address your question on scalability, I think this industry needs to take an Amazon approach: operate at a loss and use external funding until you reach enough scale to make the unit economics work. If this company can successfully do this, they could revolutionize an antiquated industry.

On November 15, 2018, Karen RR commented on Straight to the Source: Open Innovation at Buzzfeed :

I think you have identified the perfect strategy for buzzfeed to remain credible while still using open source innovation. Buzzfeed inherently has two identities: a social platform that lists movies, funny memes and recipes. It has also recently tried to position itself as a credible news source, and contrary to their “no political” rule, a platform for social commentary. In order to keep readers engaged and stay credible, they need to be very judicious in where to crowdsource their information. Crowdsourcing points that need little diligence to confirm. Restaurant recommendations and movie lists are the perfect use of crowdsourcing. News, however, needs to be controlled by the company – including the comments section – if they want to stay objective and credible.

On November 15, 2018, Karen RR commented on Goldman Sachs: Is a dedicated App Store the Future of Retail Banking? :

Very interesting article. The need to innovate and move into fintech is a huge focus for bulge bracket investment banks. However, I am a bit weary of using open source innovation in a bank, especially with regards to personal deposits. Open source innovation works best with the sharing of information, which is inherently personal and very private in a banking sense. I would be nervous that any security breach from one of the apps (like we see often on iphones) would cause extreme media backlash as we saw with Wells Fargo.

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On November 15, 2018, Karen RR commented on Goldman Sachs: Is a dedicated App Store the Future of Retail Banking? :

Very interesting article. The advancement into fintech is a big focus for global investment banks, and Goldman’s investment in Marcus is very innovative, especially since they do not have a standard retail operation like JP Morgan and Citibank. However, I am a bit nervous about using open source innovation on retail banking, where there is a high risk of compromising security information. Goldman already has a lot of media scrutiny around it, and having a security breach could cause a media and public backlash as we saw with Wells Fargo. Further, the banking industry, especially investment bank

On November 15, 2018, Karen RR commented on Venture Capital: Rumors of my death have been greatly exaggerated :

Using AI to hack VC is obviously a very impressive advancement. However, I wonder if VC is the best market for it? VC is actually where I think you need the highest level of subjective searching, and where past performance may not predict future performance. Aren’t Unicorns titled as such because they are drastically different than anything to come before them, and therefore can disrupt the industry?

I wonder if using AI would be even more fruitful in Private Equity or more mature growth capital, where the companies have longer track records of financial metrics that machine learning can use to train the algorythyms, and where the industry is look for good, stable companies rather than riskier, industry changers.

On November 14, 2018, Karen RR commented on How McKinsey is Dealing with the Machine Learning Challenge :

I have learned so much about consulting firms since I started HBS. What impresses me most is their ability to use what they learn from their clients to make themselves better firms. The above article is a perfect representation of that.

Helping companies better use technology is a huge area of need. this is especially true as older companies fight to stay relevant and at the forefront of the industry. Mckinsey already has very established relationships with these companies already, so this acquisition is a natural fit for them.

On November 14, 2018, Karen RR commented on Machine Learning at Amazon: Will Amazon Go Reinvent Retail? :

Great article. I personally love amazon, and think it’s the way of the future. However, I wonder if they are unnecessarily investing in brick-and-mortar space. Are they spending money on a problem that people don’t want fixed? I wonder how much time people will be spending in stores once amazon truly takes over online retail. Are they using AI to fix problems in stores that people will no longer visit?

On November 14, 2018, Karen RR commented on The Future of Portfolio Returns and Wall Street Traders :

The advance of the robots is a big worry of top traders at bulge bracket banks. While they may increase effenciency and increase returns at clients, a lot of bankers are worried that it will be a race to the bottom, and actually increase risk in the system.

The perfect trade exists when there are direct and executable price mismatches in the market. For example, take two exactly identical pairs of shoes were for sale directly accross the street from one another, but one is priced at $10, and one is priced at $20. If you were able to buy the $10 shoes, walk accross the street and sell them to customers in the other store for $20, you have a riskless, perfect trade, or arbitrage opportunity. Electronic trader finds these market anomolies and exploits them, even if they last for only a fraction of a second. Traders argue that these traders are the safest way to get returns, or maximize alpha. If everyone employs machine trading, these opportunities wont exist anymore, and traders will start looking to trade more on their forecasts or guesses of the future, which is inheritly more risky.

On November 14, 2018, Karen RR commented on Revolutionizing personal credit with machine learning :

Great article! Today, credit scores are imperative to someone’s quality of life in America. They dictate if you can buy a house, go to school and work in a financial institution. However, credit scores are easily hacked and only measure a small part of someone’s past ability to pay, which may mean nothing about their future ability to pay.

In terms of barriers to entry, I think you hit the nail right on the head. Regulation is one of the most cumbersome parts of the financial industry, and having the money to deal with all of the regulatory barriers is one of the issues barring companies from entering the banking industry.