Analysing Twitter feature results in Google SERPs

by on 8th April 2016

Over the past couple of days, I’ve spent some time looking at what makes a Twitter featured result turn up in Google’s results. Along the way we’ve discovered some interesting things that seem to play a part, if you’re looking to get your account featured in a specific Google search query.

The main takeaways were that an account seems to need to pass a threshold on validity, possibly based on followers and verified status to have it be likely to show up in a feature. The tipping point seems to be 12-15,000 followers for an unverified account or 20-25,000 for a verified one. Seemingly being verified increases the likelihood of a result showing up, but may also require more followers to prove that the verification is truly notable from Google’s perspective. Getting to those numbers takes, on average, around three years.


For the avoidance of doubt, this is the feature type we’re talking about:


Query: Star Wars


Query: Hillary Clinton


Query: Red Bull F1

These features were introduced in August of last year, and we’ve been tracking them since. Now that we’ve got a reasonably sized dataset, I thought it’d be worth a look to see what happens to trigger an account appearing in a result.

Note that this doesn’t look at what types of results surface a Twitter feature box – that’ll be in a separate post next week.


The first thing we found is that where an account is located makes a huge difference as to whether it features or not. International SERPs and Twitter accounts rate far better than US accounts. Below is a table of average positions for different locales where the Twitter account has a timezone set:

TimezoneAvg. Position
Eastern Time (US & Canada)5.7
Pacific Time (US & Canada)10.6
Central Time (US & Canada)10.8

This gets even more interesting when you break it down by continent and whether or not an account is verified:

TimezoneUnverified Avg. PositionVerified Avg. Position
North America5.712.8

In both areas, verified accounts tend to get higher results than unverified ones. However, European unverified accounts do better than ones in America. This prompted a further question – is it verification that’s making the difference, or is it simply correlation? What else might make a similar difference?

Follower Counts

N.b. the follower numbers are for that number up to the next one, except for 1,000,000 which is that and higher. Accounts with less than 1,000 followers were ignored for this, as they virtually never turned up.

With that in mind, above is a chart showing the position achieved by a Twitter feature, against the number of followers that that feature author has. As we can see, with a large number of followers, we often get position 2, and even if it’s not that high, then it’s still in 3 or four fairly regularly. If we compare that two the lower numbers we get something very interesting…

Now we see that there’s no greater likelihood for any particular position. It’s far less likely that these accounts will show at all, and if someone else has a Twitter account with greater follower numbers, then the larger always be the one that shows.

Followers or Verified?

Now that we know that both verification and a high follower count are both indicators of an account being likely to show, I thought we’d take a look at how many followers a verified account is likely to have.

As expected, verified accounts tend to have higher follower counts. For our sample, verified accounts averaged around 25,000 followers, whilst unverified accounts had 15,200. It’s worth noting though that this is only accounts that showed in Google, so very small accounts would be unlikely to turn up at all.

Interestingly we also saw a similar story with charting the average number of tweets by the number of followers. Perhaps unsurprisingly, accounts with more tweets tended to have more followers, and to be older.


Many thanks to our good friends at STAT who provide the ranking data for our client reporting suite via their API (download some of their data here), and to Highcharts who we use for all our charting needs. If you’d like to build your own charts, take a look at our Highcharts Generator which I used to save time making this post.

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