Where has the spike in my analytics come from?

Where has the spike in my analytics come from?

As you start to grow your show, you'll likely notice a similar number of downloads each day and recognise familiar patterns in your analytics. Occasionally there maybe an unexplained spike in your analytics that looks something like this:



This guide will show you how to gather more information about that particular increase in downloads and we'll suggest some of the most common reasons why this happens.

When did it happen?

In the Analytics tab, look at the Listener Trends section
Change the drop down from All Time to show individual days e.g. Past 90 days, Past 7 days etc
Look for your spike in analytics, hover over it and make a note of the date it occurred and the number of downloads for that day

What was downloaded?

Next, in the Analytics tab, scroll down to the Episode Breakdown section
Click the Export button, select an export option that includes the date you want to look at, click the Download Episodes CSV button
Open the CSV file using software like Excel or Google Sheets
Scroll across the columns until you find the date you are looking for

This will show you which episodes have had downloads and how the spike in analytics is distributed amongst previous episodes of the show.

Why did this increase happen?

Looking at the CSV file, if the downloads on that date are spread evenly across a large number of episodes, this likely means you have picked up some new subscribers. Congratulations!
When someone subscribes to a podcast they may have auto-download turned on, which will download their chosen number of previous episodes for them to listen to offline. If we serve an audio file, we count it as a download.



This is standard across all podcasts and is a core part of podcast analytics. If we didn't count these downloads, you wouldn't have any record of subscribers listening to previous episodes. We can only count the episode at the point when it is downloaded. This only happens once for each subscriber. This doesn't happen for every listener though, it's still possible to listen to a single episode and not have previous episodes download.

Auto-downloads are not something we can change, it's solely based on the Subscribers own in-app settings.

How has this episode gained popularity?

Alternatively if the CSV file shows downloads predominantly for a single episode, there may be several factors that caused that.



Here are some possibilities of causes of spikes on individual episode. That episode could be:

A recently published episode that has been well promoted
Picked up by a new podcast app or platform
Promoted in a popular podcast platform for a specific category
Talking about a popular, well-searched for topic
Talking to a popular guest who has shared it with their own audience
Part of a recent paid-ad campaign if you are running paid ads
Shared extensively on social media with a direct link
Featured highly on your own website and remains prominent to website visitors

Where was this episode listened to?

To get more insight into where this episode was shared, you can look at the podcast players that were used to consume the episode.

In the Analytics tab, scroll down to the Podcast Players section
Click the Export button, select an export option that includes the date you want to look at, click the Download Episodes CSV button
Open the CSV file using software like Excel or Google Sheets
Scroll across the columns until you find the date you are looking for

This will show you if the episode was mainly consumed on the web, in apps, via embeds, sharing pages or on your Transistor provided web page.

Where can I find out more?

If you'd like to track where your listeners are coming from in more detail you can read our guide about Integrating with Google Analytics. This will show you where on the web your embed players are being used and who is linking to your sharing pages.

Additional Support

If you have additional questions about your analytics, please reach out to us on Live Chat or at support@transistor.fm

Updated on: 10/11/2021