Today on my drive to meet with one of @Enjoyful customers to discuss the pain points they are facing with their customer/user flow, from becoming aware of the brand to making their 1st purchase to ultimately making their recurring purchases, I pop up my @Rockship.FM and came across a very interest podcast episode (btw, I set the podcast to play on a randomized schedule so I can try my best to eliminate selection bias, aka choosing the topic I think, which might not be the reality, is most useful for running my startups)
Today’s episode focuses on how growing and matured tech companies utilized data to make last-minute informed decisions for the consumers. For example, everyone knows Yelp is really good at making food recommendations, whether it be based your historical search terms and/or the reviews you left for restaurants/food trucks your stomach fought through. But what is even more interesting is they even make recommendations based arbitrary data sets (arbitrary in the sense that it is not totally within human controls, though we are pretty good at forecasting weather with a pretty high precision accuracy. Guess that’s why IBM bought Weather Channel to incorporate their weather data into the Watson platform). For example, Yelp will more likely going to make comfort-food related restaurant/food truck recommendations if the weather is gloomy and rainy that day. On the side note, guess Seattle needs to build a lot more comfort food spots to fulfill these high demands, thanks to Yelp.
Joking aside, I think this has implications for companies and startups building and launching a consumer-facing concept. Take @Enjoyful for example, if the weather forecast is predicting a 95% of 100F this weekend here in Austin, one might logically assume that the demand for certain product type might increase exponentially versus that of the other’s. Hence in this type of situation, we can launch short marketing email snippet a day or two before the weekend to drive both potential new and recurring purchases.
This is applicable across several industry sectors. Take food delivery for example. People are more likely to use food delivery services in gloomy days (mainly b/c they don’t want to get drizzled on or simply because we are lazy). Discount code provided the day before and/or on the rainy day per the forecast will potentially driven customer adoption.
But a word of caution is that these are very short-term customer acquisition strategies to get customers into the door, so at the end of the day, building the branding around the core value props and offering customer-centric service will provide long-term stability.
Intersection notepad 