What's the point of analytics on MacGuffin?
What kind of data do you collect?
Why did my browser ask permission to send location data?
What's incognito mode for?
Who can view the analytics on MacGuffin?
I'm a writer. How should I interpret the analytics of my story?
The analytics on MacGuffin are design to a) show trends in changing reader behaviour and taste, b) help writers learn about how their work is read and shared, and c) help readers decide whether they want to read or listen to a story, in advance.
We collect anonymised data on reading events (i.e. when users start and stop reading or listening to stories), and some location data showing where in the world these users are reading or listening to that content. This data is anonymised to protect the privacy of users, and location data (which appears as a pin on a map) is 'fuzzified', which means reader locations are randomised within a 25km square grid. We also collect and display anonymised data on what tags that have been added to stories.
No. When you publish a story on MacGuffin, analytics data about that story is made available for other MacGuffin users to view, in accordance with the Content Rules
Location data enables the analytics to show where in the world stories are being read (this appears as a pin on a map in the analytics panel). This data is anonymised and 'fuzzified', which means reader locations are randomised within a 25km square grid.
We believe that analytics data will help writers to understand how their work is being read and shared. However, MacGuffin also has an ‘Incognito Mode’. When reading a story in Incognito Mode, data about that reading event will not be stored or made public on MacGuffin, and will not appear in the analytics for that story. If you switch to incognito while reading or listening to a story, data about that reading event will be retroactively deleted from our database, and will not appear in the analytics for that story. While using Incognito Mode is likely to reduce the risk of identification or re-identification of MacGuffin users, we cannot guarantee that identification or re-identification will not occur.
Click here to learn more about recent changes to Incognito Mode (28/7/2015).
The analytics for all stories on MacGuffin can be viewed by any user who is signed-in to the website (but are not viewable by via the apps).
This map shows where the story has been read or listened to. It only shows the location of users who've given MacGuffin permission to collect location data on their browser or mobile device (so there may be fewer pins on the map than the total number of reads/listens for a story). Locations are 'fuzzified' to a random point within a 25km grid.
Click on a tag to reveal tag analytics in a new panel. For information, see Tag Analytics below.
Shows how many times users have begun reading or listening to this story within the selected time period.
Shows how many times users have begun reading or listening to this story since publication.
Shows the average (mean) ratings users have given to the text and audio.
Shows the aggregated percentage of reading and listening. For example, if only one user has consumed a story, and read the first 10% of the text, then toggled to audio and listened to the end of the story, the ratio should appear as 10% reading and 90% listening. When multiple users have consumed a story, this read/listen percentage is aggregated. Because this data reflects the overall ratio of reading/listening (including toggles between formats), it may not match the data in 'Reads and listens within the selected time period' and 'Reads and listens since publication'. NB. Read completion percentages are derived from scroll progress. Listen completion percentages are derived from the audio file progress.
Shows the ratio of readers who complete the story and the readers who exit before completion. Read completion is derived from scroll progress. 85% progress counts as completion.
Shows the ratio of listeners who complete the story and the listeners who exit before completion. Listen completion is derived from the audio file progress. 85% progress counts as completion.
Shows the points where readers and listeners exit the story. Blue represents reads; orange represents listens. NB. As a straight line is plotted between individual drop-out points, these graphs are likely to be more informative for stories with a high number of reads and listens.
Tag analytics can be accessed via the analytics panel of any story. From the story analytics panel, click on a tag to reveal its tag analytics in a new panel.
This map shows the location of users when they added the primary tag (i.e. the tag that this analytics panel is concerned with) to any story. It only shows the location of users who've given MacGuffin permission to collect location data on their browser or mobile device (so there may be fewer pins than the total number of tag events). Locations are 'fuzzified' to a random point within a 25km grid.
This shows the two other tags that have been used most frequently in conjunction with the primary tag (i.e. when content is tagged with the primary tag, these are the two tags most frequently also tagged to that content). You can add or delete tags in this field to compare more tags to the primary tag.
Shows the number of times these tags have been added content.
Shows the number of unique users who have added this tag to content.
Shows the number of content items with these tags.
The completion rate shows the percentage of readers who failed to complete your story, whether reading or listening. Read completion is derived from scroll progress. Listen completion is derived from the audio file progress. 85% progress counts as completion. Bear in mind that if your story is short, and has a large section of blank space at the end, or the audio recording has a long period of silence (or applause, if it's from a live reading), this is likely affect the completion rate, as readers/listeners exit before the 'end'. For this reason, it's best to view completion rates alongside the drop-out graph, to get a fuller picture.
We ask users' permission to collect location data, both on the browser and app versions of MacGuffin. When users don't allow their location data to be used, read/listen events data will still be available (below the map), but not location data.
During MacGuffin's beta test, we found that most stories and poems typically have a lot of drop-outs right at the start of the text or audio (often more than 50% during the first 10% of a story or poem). It seemed readers often scan the first few lines of text, or listen to a few seconds of audio, then decide it isn’t for them. While this may indicate that the opening of your story/poem needs strengthening (or the audio quality is poor), it's worth bearing in mind that it also seems to reflect the way we browse literature, whether digitally, or picking up a book in a bookstore: scanning the first few lines, then deciding it’s not for us, and moving on to something else.
For this reason, you may find that the most useful drop-out analytics are those that reveal a miss-step (in plotting or pacing or tone) after the opening sentences of a story or poem. We also recommend that you compare your story or poem's analytics to those of other authors (including classics by writers like Chekhov, Dickinson and Joyce), for a more global picture of reader-behaviour.
If you want more people to read/listen to your work, try the following:
1) Share your story or poem on social media, or by email. You can do this by accessing the drop-down menu on any story (click the 'hamburger' icon'), and clicking the icons for Facebook, Twitter and email.
2) Add more tags to describe the content. For example, if it's a short story, tag it #shortstories and #shortstory. If it's set in Hackney, tag it #hackney #eastend #london. If it's comedy, tag it as #comedy #funny #humour. This will mean it's returned in more searches. Make sure you don't add misleading tags, though, as this will lead to low ratings and a high 'drop-out' rate in the analytics.
3) Improve your story/poem, and the recording. At the risk of stating the obvious, other users are more likely to share it if they like it.