BitPlatter transcribes over 10,000 new podcasts every day to enable people to search and perform analytics on podcast conversations. You can search this transcript database using our FluidDATA Podcast Search Engine, but this article is all about demonstrating some of the insights you can gain by performing analytics on our transcript data.
We've analyzed conversations of 5 car brands (Ford, Chevy, Tesla, Toyota, and Honda) based on 1,246,937 podcast published in the third quarter of 2018 (July, August, and September). This article presents only a high level overview of the types of analytics you can generate with the FluidDATA podcast dataset. If you are interested in performing your own analytics with our dataset then checkout our BitPlatter website for more information.
Share of Voice
Before I started looking at the results I would have guessed that Tesla would have received the most mentions in podcasts since they are the hip new car company popular with people interested in technology. However it seems that Tesla is mentioned about half as much as Ford or Honda. When we look at the topic analysis below you can see why this is the case. Ford, Honda, and Tesla have about the same amount of earned or organic mentions but Ford and Honda also pay for a lot of advertisement. This advertising is what pushes these two brands to make up nearly 2/3 of the share of voice compared to their competitors.
I was also surprised by how little Toyota is mentioned compared to the other companies. Toyota sells almost twice as many cars as Honda in the United States, but they are mentioned about 1/4 as much in podcasts.
As a note, mentions of the word "ford" were much higher in September due to events surrounding the Kavanaugh confirmation. Since ford is a common word the results for Ford were limited to only podcast conversations that mentioned "ford" along with the words "car", "truck", or "Ford motor[s]."
Chevrolet is commonly referred to as Chevy. For this analysis we included podcasts that mentioned both Chevrolet and Chevy and excluded mentions of the brilliantly funny Chevy Chase.
For the other brands (Tesla, Honda, and Toyota) the analysis was performed on podcasts mentioning the brand name with no additional filtering.
It's no surprise that the Ford F150 is the most mentioned vehicle in podcasts as it is the top selling vehicle in the world.
We can see that a new Built Ford Tough campaign started in September.
The most popular topics related to the other four brands are all fairly standard topics related to beefy pickup trucks and squeaky clean corporate advertising. This is not true in the case of Tesla. I limited the amount of topics to 5 in the chart, but in addition to these there were topics related to securing funding, wall street journal interviews, and smoking marijuana.
In August mentions of Elon Musk taking Tesla tesla private, started and this topic has dominated most Tesla discussions in August and into September.
And of course, Elon Musk's appearance on the Joe Rogan Experience podcast in August has been a popular topic of conversation.
Of the 5 car companies we are looking at in this article, Toyota is the least mentioned. Most mentions of Toyota seem to be from advertisements in local radio stations that upload their content in an RSS feed.
Most of the organic discussion about Honda was related to the Civic and the Accord with each getting about equal mention. Honda's Summer Spectacular Event was also mentioned a fair amount, though mostly in ads.
Honda appears to have unique position relative to the other companies we analyzed. Based on sales numbers one might expect the number of Honda mentions in podcasts to be similar to Toyota or Chevy, but they are mentioned almost as much as Ford which sells nearly twice as many cars in the United States. For some reason people seem to love to talk about their Honda but not their Toyota.
FluidDATA Stream API
The podcast transcripts used in this post were retrieved using BitPlatter's FluidDATA Stream API. The FluidDATA Stream API makes it easy to integrate podcast conversations into your analytics workflow. It's the perfect solution for media, social listening, advertising, open source intelligence, or other companies looking to expand their data sources to include podcast transcripts.