The Current State of Native Social Media Data Capabilities

Native social media analytics capabilities have changed a lot over the past year or so. Facebook, arguably, has one of the most-robust native analytics platforms available providing an overwhelmingly high number of data points. Other network platform analytics capabilities tend to live in the shadows of Facebook, but there have been some significant improvements in native social media analytics platform offerings recently. We wanted to step out of the day-to-day and highlight some things you might have missed or provide some reminders of features you might have forgotten. We’ll also call out some pain points and things to keep in mind when you’re exporting data.

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Pinterest Analytics

Pinterest’s analytics platform probably received one of the
biggest overhauls out of all the platforms (maybe excluding YouTube, more on
that later). Previously you could only see top pins by impressions, clicks, or saves
for the past 30 days. Now, when you set your date range, you’re able to see top
pins for that specific date range; across a wider option of metrics to boot
(impressions, engagements, close ups, link clicks, and saves).

The daily graph now lets you visualize impressions, engagements, link clicks, close ups, saves, total audience, engaged audience as well as related rates. If you’re feeling adventurous you can go one step further and segment the chart by content type (paid & earned vs. organic), claimed accounts (“pins that direct to your claimed website, Etsy, Instagram or YouTube accounts”), device (mobile, desktop, or tablet), source (your pins vs other pins), and format (standard, video, or story).

This (much-welcome) updated interface is significantly more-robust
and actionable compared to the previous iteration. The only significant bummer
is that the export doesn’t spit out multiple metrics in one file, meaning if
you want to put together a table of impressions, engagements, etc. by day,
you’re going to have to download a CSV for every
metric you need and combine manually.

YouTube Analytics

YouTube also experienced a significant overhaul of its
analytics dashboard and, in my opinion, it’s not for the better. The user-flow
for YouTube analytics used to be much more streamlined. This new version is
very segmented. There’s good information contained within and it lets you dig
into some interesting details, but it’s easy to get lost making it a challenge
to find your way out of the investigative hole you just dug. It’s also more
challenging to streamline reporting exports.

Previously, you could export daily performance across the available metrics, same with video performance for the selected time period. Now, you have to select all of the metrics you want included in your report. This is not unlike Facebook’s reporting in ads manager, but the major difference is that you can’t save templates. So, if you have a long list of metrics you need to export, you’re out of luck as each time you put together a report, you’re going to have to manually rebuild your settings each time.

LinkedIn Analytics

The biggest change with LinkedIn’s analytics platform is the
ability to download post metrics going back as far as one year. Unfortunately,
you can’t go back further than a year, but it’s a significant improvement over
the highly-limited export we previously had to rely on.

Twitter Analytics

Twitter’s native analytics platform hasn’t changed much, but
there are two elements worth noting. First, you can now download performance by
tweet AND by day, in case you wanted to track your impressions and engagements
over time as opposed to by content. Or you could do both and tell the full
story. Up to you, but you have that choice now! One thing you don’t have a
choice in, however, is the functioning date range for exporting data.
Previously, you could download a time period of 90 days. Now, the export will
only work if you select a 30-day time range, so pulling historical data is a
bit of a pain.

Instagram Analytics

The Instagram insight platform’s lack
of ability to download CSV of the data remains highly frustrating
. In order
to extract the information, you need to leverage a third-party platform,
extract data via API yourself, or manually record the data from your phone. There
are; however, a few metrics that make using the native analytics platform worth
it, the first of which is the “discovery percentage”.
This metric lets you know what percent of people reached by your content have
never seen a post from you before. It’s a great way to assess how well your
content is at reaching a new audience. A similar metric is the number of
impressions from hashtags. This is a great way to assess your hashtag strategy
and see if what you are tagging your photos with is gaining you additional

Native social analytics platforms remain the one of the best
sources for measuring brand performance. Sure, they have their share of bugs
and issues, but the data you get directly from these channels will let you
paint a more complete picture of your social media marketing efforts.

Are you a bit overwhelmed by the plethora social media data? We’d be more than happy to help make sense of it and streamline your reporting efforts.  

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