Analysis of YouTube Video Metrics for Engagement Benchmarks in an Industry
The objective was to benchmark the metrics like Views, Likes, Dislikes, Video Duration and posting frequency for the YouTube channels of companies that sell Paleo Diet products. This was done for a consulting project.
The client is a small Paleo Granola snack manufacturer who works as a single person for everything from manufacturing the product to marketing it. My team went in as consultants to help her out as part of our Information Strategy and Policy class.
Paleo Scavenger is a handcrafted snack company based in Chicago with the mission to make clean eating easy and accessible. The company was started by Brittany Chibe in June 2014 after pursuing a paleo diet to help her prepare for the marathon. Therefore, the consumers for this product are people who follow the paleo diet, and are overall health-conscious. Brittany has come a long way in the past year as she has gone from handing out samples at various fitness centers to selling them at renowned stores and finally starting to work with a national distributor to make her product readily available across the country.
Project Scope:
The motive of this project is to help channelize her social media strategy to move her efforts from in-person events to online sales. Currently, 30% of her sales come from in-person events and 10% from her website. She would like to use social media to steadily drive more traffic to her site and hopefully increase the sales percentage. This way she can reduce the number of in-person events, so she can concentrate on growing the company through the recent partnership with a national distributor.
The project involves intense market research to perform competitive analysis on the social media platforms competitors are using. In addition, we will analyze Paleo Scavenger’s google analytics data to determine the type of customer traffic she gets to her website. The outcome of this project is to analyze the data we collect to develop a social media strategy that will determine the platforms to concentrate on, and determine the type of content categories she should focus on for each platform.
Size of bubble represents users of platform, color saturation represents efforts required to post on the platform.
Scrapped video metrics like views, likes, dislikes, video duration and posting frequency for all videos of ten YouTube channels, big and small that sell Paleo goods using R and Python. Analyzed data and visualized results using Tableau, Excel and amCharts.
Metrics: The primary metrics that were recorded for companies and their YouTube channel are video views, video likes and video dislikes. For preliminary analysis total subscribers and video views were compared.
Categories: Every video was classified as belonging to primarily one of five types and they are:- Cooking Demos/Recipes, Healthy Lifestyle, Discounts or Contests, Events/Partnerships or Holidays, Product videos – Ingredients, new product, commercials, customer content
Traction Score:- Weights were assigned to each metric and a traction score was calculated to estimate the traction of each video category.Video views has a weight of 0.7, likes a weight of 0.3 and dislikes a negative weight of -0.2
Table below summarizes the cumulative traction score for a topic vs the cumulative # of videos made for a topic for all companies under consideration.
Following is the link link to the R code I used to scrap Video Titles, Video URLs and Video views from a particular channel. I got this code from dessyamirudin but the code was outdated as YouTube has long since changed its HTML and keeps making changes to its pages. Also the original code was to scrap this information for a particular search term, information of video results for a search term. I made changes to the code and the updated one is here. One just needs to replace the channel URL and its good to go!
I later used Python for scraping likes, dislikes and views. i am working on it to scrap comments too. I will post that soon.