Snapchat Geofilter Analytics - Swipe Time

EDIT: This post has been absorbed into our Ultimate Geofilter Guide. Check the guide out for advanced insights into every Snapchat geofilter metric.


I think about Snapchat geofilters a lot.

In this humble advertising platform, I see a sleeping giant that so far hasn't had the chance to stretch its legs.

I want to help foster discussion on the ways that geofilters and other geomarketing tools can be used in the arts & marketing worlds.

To that end, I hope you enjoy my first exploration into geofilter analytics - an area that needs much clarification. Not just for our clients, but for anyone who is willing to listen.

One element of Snapchat analytics that I’m intrigued by is Swipe Time.

I’ve seen Snapchat describe this as the average amount of time users spent looking at your filter. But what really does this mean? What kind of soft and hard data can we extrapolate from Snapchat geofilter Swipe Time?

Since I haven’t been able to find out any additional details on what the heck this means anywhere, I’m here to put forth a few ideas for how to interpret this analytic.

To me, a high Swipe Time means one of three things.

  1. Users liked the filter and felt it matched their experience well enough to use it multiple times.
    • If one use correlates to roughly 2-3 seconds of “Swipe Time”, a final Swipe Time of 12 seconds might indicate that users wanted to share their experience with multiple friends individually as well as with their Story followers.
    • Thus, they spent more time with the filter on screen as they prepped their content for sharing.
  2. Users were engaged creatively, and may have added to their content after applying a filter.
    • If a filter calls for an user to add a creative element such as their name, emojis, or stickers, then this might explain a higher Swipe Time.
  3. Users spent time reviewing the filter for particular information
    • When using a geofilter as a direct marketing tool, users may be presented with a lot of useful information in a small font. This means that if interested they might take more time to review the information being presented.

For small events, we see a concentrated number of filter uses in a short window of time with an associated swipe time that is relatively high.

At a recent museum event, our filter was used 100 times on-site with a swipe time of 12 seconds. The total views for these uses tallied over 5000, with a unique reach count of roughly 3500. To me, these numbers indicate that the view count wasn't recycled too much... which means that Snapchat users on-site could have been sharing their filter-applied content with personal friends as well as with Story Followers.

Their filter uses even popped up on the local Snap Map, which likely played a role in boosting unique view count. We managed the addition of content to "Our Story" for this event, resulting in approximately 250 views from (presumably) locals tuning in to see what was happening on Saturday in Raleigh NC. 

Do you have any thoughts on Swipe Time or other Snapchat Geofilter Analytics? I'd love to hear them. Share your perspective in the comments below and let's pick up this much-needed discussion.