Building my own data set and insights — here is what I learned

Getting the message across to the right audience has always been difficult. First, there weren’t enough media and now we have too many. It’s hard to fathom how some great original content gets a handful of views. Getting a better understanding of what people are sharing and what prevents them from sharing things could help. To this end, I created an ambitious but crude survey and this post is about phase-1 where I shared the survey and drew some insights. I am hoping to kick-start phase-2 through this post. The goal of the survey is simple: Determine what kind of information people share Determine where people share information Methodology I set up a google form with the following questions: P.S. This form is still active, if you have 30 seconds to spare, please fill it. I shared it with people on Linkedin, Facebook, Slack and Whatsapp. Irony, sharing a survey to understanding sharing patterns :) I got a small number of respondents around the world to respond. Here are my observations: Most people don’t share serious content because they need to figure out who the audience is. And that is too much work with little reward Jokes, memes and other generic content don’t fall into this category and go viral. Whereas, if you were trying to share a post on product management, you would have to figure out the relevant audience and then send it out. This seems to be a deterrent. The next big reason is, people, perceive it as spam. Closely following suit is laziness. It makes sense, figuring out the right audience and laziness are two ways of looking at the same thing. Mention who the content should be shared with and see if it gets shared more. Tip: What are people sharing? The results of the survey show that people are sharing knowledge & professional content. This may be due to . I only say this because I don’t receive that many useful forwards. The on my phone shows memes, jokes and other entertainment-related content outranking the professional and knowledge content. Closely following suit is funny videos, followed by memes, jokes & news. observance effect bias data Maybe people want to share better content but there isn’t much going around in the right channels. Also, you are likely to go viral if you make a meme or a cat video as compared to writing a serious blog post. I am guessing you already knew that. Tip: Where do people share professional content? The results say, office communicator/Lync/Skype for business. This confirms the first point, sharing within office takes away the need to figure out whom to share with. That is why blogs, professional content gets shared within office networks. This is followed by groups and Linkedin Groups. Whatsapp Office networks maybe an untapped source of readers. I personally find it embarrassing as I don’t want to look like I am promoting myself. I maybe wrong. Tip: Wha_t apps/ social media are people using?_ Disclaimer: The majority of my data is from India. I have received responses from many cities around the world but many of those respondents may be Indians as well. Whatsapp is the winner here in India. The penetration is unbelievable. Even people who make enough to barely buy 3 meals a day use WhatsApp. It makes sense, buying a data plan and using WhatsApp to call and send a message is way cheaper. People are on it, forwarding stuff all the time. The potential is unbelievable. Facebook is the next biggest. So, between Facebook and WhatsApp, Mr.Zuckerberg is sitting in a sweet spot when it comes to India. Share on WhatsApp if your audience is Indian. Insight: Closing Notes I saw responses from Australia, US, Canada, Luxembourg, Germany, Bahrain & India. The majority was from India. The respondents from other countries were in single digits. I couldn’t draw any conclusions for other geographies. I had designed the survey with many multiple choice questions. Multiple choice questions mean that you will have to spend time cleaning the data & making it plot-able. The survey itself could have been designed better. The demographics data was so messy, I had to normalize country names, city names etc. I have shared my data on GitHub sans the email addresses of the respondents. here This may not be a great dataset as phase-1 had very few respondents. I hope to have a bigger set on which anybody can work to produce good insights. There are 2 files: There is a CSV file which google spits out. There is a cleaned excel where I have extracted the data for each question and transformed it for better reporting. If you have any suggestions on how I can share this in a more meaningful way, let me know in the comments section. The goal of this survey was to reach a large number of respondents around the world. I can then make this a meaningful study with public access to the data. Something like this: _More than 15,000 people responded to the 2016 New Coder Survey, granting researchers an unprecedented glimpse into how…_medium.freecodecamp.org We asked 15,000 people who they are, and how they’re learning to code Data collection is the biggest challenge anybody who isn’t an influencer. If you are reading this, the survey is still open. It takes under a minute — Please fill it out & share it within your networks. Better data volumes help uncover more insights.