Tikola Nesla's Profile
Cool post! Your last question was great and made me think about causation versus correlation. Clearly the correlation is there – NBS’s predictions move positively with a band’s success and vice versa. However, which caused which? NBS can do a few things to evaluate this question. The first strategy that comes to mind is doing a controlled matching experiment using historical data. To do this, they would make two groups of past bands, one for NBS promoted bands and one for non-NBS promoted bands. Each band in the NBS group should have a partner in the non-NBS group that has similar demographics like launch year, starting fan base, genre, social media outreach, etc. Using a success rate metric, like number of fans after a certain time period, as the dependent variable, they can then run a one sided t-test to see if the NBS group had a statistically significant higher rate of being successful. Each group had comparable bands within it, so the null hypothesis is that the NBS group success should equal the non-NBS group success. If the t-test comes up with a low p-value, then they would reject the null hypothesis and the alternative would be true that the NBS bands are more successful than the non-NBS bands. Thus, telling us that NBS’s promotion actually caused the success. NBS can then choose to use this information to re-position their marketing message to bands and sponsors or not.
I like how consumer-centric Raw has been through the product development phase. I was thinking how you could use your data to run regressions to find statistically significant trends, because that would be extremely powerful to your brand and mission. One opportunity is to target consumers on the fence.I bring this up, because the first set of consumers seem to have been more open-minded to organic skincare given the fact that they were willing to use a product on their body without knowing what it was. Therefore, they self-selected in, which makes sense for figuring out how to make your target consumer happy. However, to bring in consumers that are more hesitant, Raw can purposefully test skeptics (extreme users) and measure their subjective feedback as well as an objective professional’s feedback after using the product for a certain amount of time. You can then run a regression on this set of consumers to learn what demographics are skeptical as well as gain supporting research to show them that shouldn’t be. Good luck!
This is a cool concept. I wouldn’t downplay the big data angle, though. The consumer insights gleaned from this website will save companies a lot of money. First, they don’t have to conduct research on their own. Instead, they can gather information from a broad range of demographics and geographies using The Hunt. Second, they can forecast trends better, which can be costly in a customized business like fashion.
Aside from the data, I imagine now that the community is large enough, fashion companies will also pay to use the site to recommend their own products as a form of targeting advertising. However, The Hunt will need to monitor the corporate posts to make sure they are adding relevant information (i.e. not recommending boots when the user is looking for sneakers) or else the quality and trust of the site will decrease.
Either way, the Hunt’s unique crowdsourcing model has positioned it to be a lucrative acquisition for a Google or a Facebook, scrounging around to find any consumer information they can.
In elementary school, I remember thumbing through the thick volumes of Encyclopedia Britannica at the library. As computers became more readily available in schools, we started using the Encyclopedia Britannica CD-ROMs for research projects. Nearly a decade later, Encyclopedia Britannica no longer offers their information in books or CD-ROMs. They are strictly an online publication now, and arguably a direct competitor of Wikipedia. What I find so interesting about this is that Encyclopedia Britannica articles, written by one distinguished expert, are traditionally an acceptable source, while Wikipedia articles, written by multiple self-declared experts, are not. I would argue that the crowdsourced articles of Wikipedia are more well-rounded, because the sources are from multiple points of view. Therefore, the open platform of knowledge sharing can be just, if not more, reliable than traditional sources.
This was an interesting post. However, I view the crowd engagement in a more positive light. My sense is that this movement holds both sides accountable. It keeps companies honest and challenges consumers to provide constructive solutions instead of only complaining. As a CPG company, I would much rather channel consumers’ feedback towards solving problems instead of creating them, which is where crowdsourcing comes in. In the long run, crowdsourcing builds communities (like Prodigy and Elance) around a product/service, which helps to elevate brand value. I am not a potato chip person, but the hype and innovation around the Do Us A Flavor competition grabbed my attention for a product that I typically ignore. Perhaps as crowdsourcing becomes more common, it won’t be as enticing, but I think it works for now.
I hadn’t thought of this industry as displaying network effects, probably because they are more indirect as you mentioned. It’s a good point and made me think about AMEX and their relationship with network effects. AMEX has chosen to go with a business model that relies on swipe fees, while Visa and MasterCard rely on interest charges. Therefore, AMEX charges merchants a higher percentage to accept their card and some retailers would rather not lose that extra 1%, so they don’t accept AMEX. Credit card owners know about this and some would rather not risk being turned down, so AMEX has to draw in customers by other perks such as high membership fees in exchange for high-end perks like access to airline lounges and no international fees. Basically, AMEX goes after the big spenders and retailers that cater to them. Using this strategy, AMEX has been able to overcome the barriers of network effects put in place by incumbents.
Another type of indirect network that we can discuss is advertising within the app. To my knowledge, Tinder is not taking advantage of paid advertising. Brands are getting creative with guerrilla tactics by setting up profiles while leveraging Tinder’s large user base. Here’s an example:
Internally, Tinder can benefit from ads as well. Tinder started off as a hook-up site, but has since expanded into dating. Unclear if they want to break away from the hook-up culture altogether, but they can use ads to change their own image with socially responsible ads such as this campaign against sex trafficking:
I agree that the biggest risk thredUP faces is the threat of substitutes – the barrier to entry is low for competition and the switching costs are low for consumers. However, thredUP can make changes on both the demand and supply side to create value that makes it difficult for competitors to get a foothold.
For example, to increase demand, thredUP can build a community that includes forums and webinars for everything from school fashion to parenting advice. If consumers come to the site to learn, it will be very easy for them to seamlessly start browsing the clothes available as well. Also, by sharing articles or videos from the site with other parents, the networking effects will draw in more potential customers who will view thredUP as a trusted, parenting site. Or, thredUP can use the data they have gathered from an individual’s past purchases and send out custom weekly/monthly emails with suggested clothing based on size, gender, and style. This will help smooth demand in off-seasons. Plus, customers will be less inclined to switch because they are receiving curated style advice based off of past purchases.
On the supply side, thredUP might consider leveraging their current buyer base. They can do this in two ways. One is by recommended them to act as sellers as well. The best model for thredUP is for users to be both buyers and sellers to create a self-sustainable market. Two is to drive network effects by giving buyers discounts for every new seller they recommend to the website (similar to what Lyft is doing to attract drivers).
Buzzfeed’s business model of inserting paid links into their articles worries me for two reasons. First, just like Uber’s most valuable asset is their drivers, Buzzfeed’s most valuable asset is their community. They rely on “shares”, “likes”, and all things social media to spread their articles and capture value. That being said, readers could be turned off by Buzzfeed’s tactics and move on to a new source once they understand how it works. Second, Buzzfeed’s end goal to create value by becoming a serious content provider seems hypocritical given its current pop-culture reputation. If anything, I think this move will destroy value within their current user base. They should keep focusing on the ridiculous and light-hearted, because everyone needs a cat video in their life at some point.
I have a Google Chromecast too, and I love it. My main driver for picking Chromecast instead of Roku or Apple TV (I have an iPhone) was value i.e. which one will give me the best bang for my buck. At $35, Chromecast covers 90% of my app needs, so it was the winner. Critics have downed Chromecast for not having an onscreen user interface. However, following up our Samsung case and the future of TVs, it makes more sense for a phone or tablet to be the control center, because actual TV screens may be on the way out.
I read an interesting article today about how Microsoft plans to make money while “giving away” Windows. Basically, they’re using guerrilla tactics to pull in users through a free product and locking them into Microsoft search tools, like Bing and Cortana, generating more queries and ad revenue. I’m not convinced this is a winning strategy. Windows software is where they create value, and sacrificing it to compete in Google’s world of search is dangerous.