Liz Sprague

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On November 15, 2018, Liz Sprague commented on Can an algorithm replace “the pill”? :

I love the idea of this contraceptive. As someone who struggled with taking hormone-based contraceptives (mood swings, sudden outbursts) I think this is a really powerful product that gives women control over what they choose to put in their bodies. Although I understand the 7% failure rate is a problem, as long as the business is upfront about the risks I believe women should be able to choose. The FDA should treat these just as any other product and should not require higher levels of efficacy. It seems as though the wearable is a necessary next step, leading to more accurate source of data and better learnings. I believe this efficacy rate will come down as the product develops!

This is so interesting! I am a massive Spotify loyalist for exactly this reason. Every week, I get to play my “Discover Weekly” playlist, and I am amazed by how well they understand my music preferences. This is certainly a reason I would never switch from Spotify to Apple Music. It was interesting learning about how they actually provide these recommendations. It really encompasses all aspects of a song: other consumer preferences, sound, and lyrics. For these points, I am not worried about Apple Music. I think Spotify has developed a loyal base of users who are unlikely to switch. Additionally, I see them as the experts in music – Apple can stick to the hardware!

On November 15, 2018, Liz Sprague commented on Promise and Peril for Machine Learning at Netflix :

Great thoughts! I tend to lean towards more personalization, as I believe it provides the best customer experience and can truly drive customer retention. The use of consumer’s time is a resource, and I think that any way Netflix can cut down on the amount of time searching for content will drive business into the future. My current frustration with Netflix is how long I search before I find something that I would like to watch! I think it would be a good idea for Netflix to start supplementing its own data with other stats from social media sites. If Netflix could target me so effectively that the first recommendation was an immediate hit for my preferences, I would be one happy consumer.

On November 15, 2018, Liz Sprague commented on Coding the Way to Better Patient Outcomes: Machine Learning at Cigna :

Interesting concept – this seems like a natural extension for machine learning and hopefully can have a real impact on people’s lives. I’m an optimist, and think both goals can be accomplished – Cigna should be able to maintain a competitive edge while also helping patients. Data should be used in tandem with human contact/judgement to ensure the best outcome for the patient. I do like the idea of health data permeated all aspects of life to help with data collection. I think a lot of people would be willing to wear watches etc. for the greater good.

On November 15, 2018, Liz Sprague commented on Your Personalized Dinner is Served :

This is such a great concept! I am new to the cooking world and would love to use this. I think its interesting that Wellio is taking a concept started by Blue Apron/Hello Fresh and advancing the product to become fully ingrained in the consumer’s life. I do wonder if they are trying to be too many things at once – the combination of personalization and complicated logistics much be very challenging. I also wonder if the “no commitment” aspect will eventually be detrimental to the business. I see this as as a constant part of someone’s life and think they may need to add a loyalty component so consumers remain engaged – this would also help with the data problem you identified in the first question. If a customer is consistently using it, Wellio is collecting more data and providing a better experience for that person. However, I generally think this is a great business idea. I see the barriers to cooking a meal as the time needed to find a recipe and shop for groceries. This solves these problems with the added benefit of nutrition.