Tips for social media competitor analysis: Let’s stop talking about follower count

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Tips for social media competitor analysis: Let’s stop talking about follower count

06/11/2018 Blog 0

This year, Hootsuite announced that 3.196 billion people are now active social media users. That is 42% of all the people on earth. In the UK, that percentage climbs to 66% and it’s 71% in the US. Even with recent data protection scandals, platforms like Facebook, Twitter, Instagram, LinkedIn, Wechat, and Pinterest are a huge part of daily life.

This kind of impressive cut through makes it more likely that we can use social media to find our audience, but that doesn’t mean that everyone on the platform is desperate to hear from us. In reality, when we use social media as businesses we’re competing for what might be a very small, very niche, but very valuable cross-section of a network. This means that whenever we do social media marketing, we need a strategy, and to have a successful social media marketing strategy it’s vital to know how we compare to our competitors, what we’re doing well and what threats we should be worrying about.

Without effective social media competitor analysis we’re working in the dark. Unfortunately, a lot of the time when we compare social media communities we keep coming back to the same metrics which aren’t always as informative as we might like. Fear not! Here’s a guide to find the social media stats which really tell us which competitors to watch out for and why.

What are we trying to achieve with social media?

One of the biggest problems with creating a social media strategy is the subjectivity of social can make it incredibly hard to get solid, reliable performance data that can tell us what to do next. If we want to get actionable information about how we compare to competitors, it’s important for us to start with why we’re on the platforms to begin with (we’ll use these agreed facts in later sections). If we agree that;

  1. The value of a social media competitor analysis is to help us perform better on social
  2. The value of social is to help us achieve the business objectives that we set out in the first place.

Then we can agree that the numbers we look at in a social media competitor analysis must be defined by what we actually need the networks to achieve (even if it takes a while for engagement to become page views).

With that in mind, here are the most common aims I think we try to achieve through social media, ordered roughly from high commitment on the part of our audience, to low. When we are comparing social networks we need to make sure we have an idea of how the numbers we look at can contribute to at least one of the items below (and how efficiently).

  1. Sales (this can include donations or affiliate marketing as well as traditional sales)
  2. Support (event attendance etc. paid event attendance being included in sales)
  3. Site visits (essentially ad sales, visits to websites that don’t run on ads can be considered a step towards a sale)
  4. Impressions/staying front of mind (this is also a prerequisite for each of the above).

Why we should stop talking about raw follower counts

We often hear social media accounts evaluated and compared based on raw follower counts. If we agree we should look at numbers that are defined by our key goals I have some reasons why I don’t think we should talk about follower counts as much as we do.

“Followers” is a static number trying to represent a dynamic situation

When we compare social communities we don’t care how effective they were in 2012. The only reason we care about how effective they were over the last six months is because it’s a better predictor of how much of the available audience attention, and conversions they’ll take up over the next six months. What’s more, as social networks grow, and implement or update sharing algorithms, the goal posts are moving, so what happened a few years ago becomes even less relevant to the present.

Unfortunately, raw follower count includes none of that context, it’s just a pile of people who have expressed an interest at some point. Trying to judge how successful a community will be based on follower count is like trying to guess the weather at the top of a large hill based solely on its height – if it gets really big you can probably guess it’ll be colder or windier, but you’re having to ignore a whole bunch of far more relevant factors.

Follower buying can also really throw off these numbers. If you want to check competitors for follower buying you may be able to find some signs by checking for sudden, unusual changes in follower numbers (see “What we should look at instead”) or try exporting all their followers with a service like Export Tweet and check for a large number of accounts with short lifespans, low follower numbers or matching follower numbers.

An “impression” is required for every other social goal

I’m going to move on to what other numbers we should look at in the next section, but we have to agree that in order for anyone to do anything you want with your content, they have to have come into contact with it in some way.

Because of the nature of social networks we can also agree the number of impressions is unlikely to exactly match the follower number, even in a perfect system – some people who aren’t following will see your content, some people who are following won’t. So we’ve started to decouple “follows” from “impressions” – the most basic unit of social media interaction.

Next we can agree – if an account stops producing effective content, or stops producing content altogether, follower count will make no difference. A page that posts nothing will not have people viewing its nonexistent posts. So follower count isn’t sufficient for impressions and impressions are necessary for any other kind of success.

Depending on the kind of social network, the way in which content spreads though it will change. Which means follower count can be less decisive than other systems in different ways. We’ll look at each format below in isolation, where a network relies on more than one means (for instance hashtags and shares) the effect is compounded rather than cancelled out.

Discovery driven by hashtags

Ignoring other amplification mechanisms (which we’ll discuss below), follower count can be much less relevant in comparison to the ability to cut through hashtags. The end result of either a large, active following or content effectively cutting through a hashtag (or both) will be shown in the engagement metrics on the content itself, we have those numbers, so why rely on follows?

Discovery driven by shares and interaction

The combined followings or networks of everyone who follows you (even at relatively small numbers) can easily outweigh your audience or the audience of your competitors. Engagement or shares (whatever mechanism the platform uses to spread data via users) becomes a better predictor of how far content will reach, and we have those numbers, so why rely on follows?

If you’re interested in analysing your followers or competitor followers to find out how many followers those followers have and compare those numbers, services like Export Tweet will let you export a CSV of all the followers of an account, complete with their account creation date and follower number. Also, if you have to look into raw follower numbers this can be a way of checking for fake followers.

Discovery guided by algorithms

In this case, content won’t be shown to the entire following, the platform will start by showing it to a small subsection to gather data about how successful the post is. A successful post is likely to be seen by most of the following and probably users that don’t follow that account too, a less successful post will not be shown to much more than the testing group. Key feedback the platforms will use to gauge post success is engagement and, as we’ve said, we have those numbers, why rely on follows?  

This particular scenario is interesting because having a very large audience of mostly disengaged followers can actually harm reach – when the platform tests your content with your audience, it’s less lightly to be seen by the engaged subset, early post success metrics are likely to fare worse so the content will look less worthy of being shared more widely by the platform. This can mean that tactics like buying followers, or running short-term competitions just to boost follower count without a strategy for how to continually engage those followers, can backfire.

I’m not saying follower count has no impact at all

A large number of follows does give an advantage, and make it more likely that content is widely seen. The fact is that in most cases, engagement metrics usually tell us if posts were widely seen, so they are a much more accurate way to get a snapshot of current effectiveness. Engagement numbers are also far closer to the business objectives we laid out above so I’ll say again, why rely on follows?

At most I’d only ever want to use follower count to prioritise the first networks to investigate – as far as I’m concerned it isn’t a source of the actionable insights we said we wanted.

What we should look at instead

Engagements

In many ways, engagement-based numbers are the best to look at if we want to put together a fair and informative comparison including accounts we don’t own.

Engagement numbers are publicly visible on almost every social network (ignoring private-message platforms), meaning we aren’t having to work with estimates. What’s more, engagement is content-specific and requires some level of deliberate action on behalf of the user, meaning they can be a much better gauge of how many people have actually seen and absorbed a message, rather than glancing at something flying past their screen at roughly the top speed of a Honda Civic.

What business goal does this relate to?

Impressions. As mentioned above, engagements require the content to be on-screen and for the user to have recognised it at some level. Because engagements are like opt-in impressions, we can judge comparative success at staying front of mind. We could also use it as a sign that our audience is likely to take further action, like visiting our site or attending an event, depending on how you interpret the numbers (as long as it’s consistent). It’s fuzzy, but in a lot of ways less fuzzy than follows (due to removal from actual business goals) and actual impressions (due to lack of data). What’s more, the inaccuracy of this data leans towards only counting users who cared about the content, so it’s something I’m happy to live with.

That being said, when you’re comparing your own community to itself over time (and not worrying about competitors) impressions itself is still a good metric to use – most social platforms will give you that number and it can give you a fuller idea of your funnel (we’ll cover impressions more below).

What numbers should you use?

As with follower change and impressions (which I discuss below), we need to control for varying follower base and posts-per-day. I’d recommend:

  • Engagements per (post*follower) (where you multiply total follower count by total updates posted)
  • Engagements per post
  • Total engagements per post.

The first number should help you compare how well a follower base is being engaged, the second should give an idea of return on investment, and the third is to avoid being totally thrown off by tiny communities which might not actually be moving the needle for business objectives.

It’s worth checking the Facebook and Twitter ad reporting (relatively new additions to each platform) to see if the page is spending money promoting that content.

What tools should you use?

The platforms themselves are an option for gathering engagement numbers, which is one of the reasons this kind of check is ideal. This can be as simple as scrolling through competitor timelines and making notes of what engagement they’ve received. Unfortunately, sometimes this is time-consuming and many platforms take steps to block scraping of elements. However, I’ve found some success with scraping engagement numbers from Facebook and Twitter and I’ve included my selectors in case you do manage to use a tool like Agenty or Artoo.js to help automate this.

Facebook

Number
Shares Likes Comments Additional comments All visible posts
Selector
.UFIShareLink ._4arz span .UFICommentActorAndBody .UFIPagerLink ._q7o

Twitter

Number
Interactions All visible posts
Selector
span.ProfileTweet-actionCountForPresentation span._timestamp

Facebook Insights is another great source of information because it’ll give you some direct comparisons between your page and others. It’s not quite the level of granularity we’d like but it’s easy, free, and direct, so gift horses and all that.

NapoleonCat – I don’t work for this company but they have a 14-day free trial and their reports offer exactly the kind of information I’d be looking for, for both managed profiles, and ones you are watching. That includes daily raw engagement numbers, and calculated engagement rate and SII their “Social Interaction Index” which claims to account for differing audience size, allowing direct comparison between communities.

The hitch is that Twitter and Instagram only start collecting information from when you add them to the account, so if you want to collect data over time you’ll need to pay the premium fees. On the other hand, their support team has confirmed that they’re perfectly happy with you upgrading for a month, grabbing the stats you need, removing your payment card for a few months (losing access in the process) and repeating six months later for another snapshot.

Socialblade – offers some engagement rate metrics for platforms like Instagram and Twitter.  It doesn’t require you to log in but the data isn’t over time so your information is only as good as your dedication to recording it. 

Fanpage Karma does an impressive job of trying to give you actionable information about what is engaging. For instance, it’ll give you a scatter chart of engagement for other pages, colour coded by post type. Unfortunately,  anything more than a small number of posts can make that visualisation incredibly noisy and hard to read. The engagement-by-post-type charts are easier to read but sacrifice some of that granularity (honestly I don’t think there is a visualisation that has engagement number and post type over time that isn’t noisy).

It’ll also let you compare multiple pages in the same kind of visualisation where the dots still show number of engagement but are colour coded by page instead of post type, patterns can be a bit easier to divine with that one but the same tension can arise.

If you’re tracking these stats for your own content Twitter analytics and Instagram Insights are great, direct, sources of information. Any profile can view Twitter analytics, but you’ll need an Instagram business profile to look at the Instagram data. At the very least, each can be a quick way of gathering stats about your own contents’ impressions and engagement numbers, so you don’t have to manually collect numbers.

If you have to include a follower metric…

If you have to include a follower metric, I’d advise focusing on something far more representative of recent activity. Rather than total or raw number of follows, we can use recent change in followers.

While I still think this is a bit too close to raw followers for my liking, there’s one important difference – this can give you more of an idea of what’s happening now. A big growth in followers could mean a network is creating better content, it could also mean they’ve recently bought a bunch of followers, either way, we know they’re paying attention.

What business goal does this relate to?

Some people might use this number to correlate with impressions, but as I said we can use other numbers to more accurately track that. This number (along with raw post frequency) is one means of gauging effort put into a social network, and so can inform your idea of how efficient that network is, when you are looking at the other metrics.

These numbers are also likely closer to what senior managers are expecting so they can be a nice way to begin to refocus.

What number should you use?

We need to account for differing community histories, a way to do this is to consider both:

  • Raw followers gained over a recent period
  • Followers gained over a recent period as a proportion of total current followers.

We can use these two numbers to get an idea of how quickly networks are growing at the moment. The ideal would be to graph these numbers over time, that way we can see if follower growth has recently spiked, particularly in comparison to other accounts of similar focus or size.

Once we’ve identified times where an account has achieved significant change in growth, we can start to examine activity around that time.

What tools should you use?

NapoleonCat (I promise I’m not getting paid for this) can give you historic follower growth data for accounts you don’t own, although unfortunately it only reports Twitter follower growth since the point an account starts being monitored (other networks seem to backdate).

Socialblade offers historic follower stats for accounts you don’t own, the first time anyone searches for stats on an account, that account will be added to Socialblade’s watchlist and it’ll start gathering stats from that point. If you’re lucky, someone will already have checked, otherwise you can have a look now and check back later.

Impressions

It can be harder to get a comparison of impressions for content, but it’s one of our most foundational business objectives – a way to stay front of mind and ideally build towards sales. Everything we’ve covered in terms of Follower numbers is a step removed from actual impression numbers so it’s worth comparing actual impression numbers for recent content where we can.

What business goal does this relate to?

Impressions, but as impressions are the minimum bar to clear for all of our other business goals, this can also be considered top of the funnel for other things.

What numbers should you use?

  • Impressions per (post*follower) (where you multiply total follower count by total updates posted)
  • Impressions per post
  • Total impressions per account/all impressions for competitor accounts during that same period

Once you have collected impression numbers from a range of accounts on the same platform which are targeting the same audiences, we can sum them together and compare total impressions per account against total impressions overall to get a very rough share of voice estimate. This number will be heavily impacted by users who view content from one account again and again, but as those users are likely to be the most engaged, it’s a bias we can live with. Again, comparing this over time can give us an idea of trajectory and growth.

Some accounts may try to drive up key metrics by posting a huge number of times a day, there’s definitely a law of diminishing returns so as with engagements I’d also get an average per-post impression number to gauge comparative economy.

As this is post-specific, I would also recommend breaking this numbers down by post type (whether that be “meme”, “blog post”, or “video”) to spot trends in effectiveness.

What tools should you use?

Fanpage Karma again goes out of its way to give you means of slicing this data. Just like with engagement you can show impressions by post type for one Facebook page, or compare multiple at the same time. It can result in the same information overload but I definitely can’t fault the platform for a lack of granularity. Unlike with engagement, the platform will pretty much only give you impression data for Facebook and unfortunately sometimes it’s patchy (see the SEMrush and Moz graph below). 

It’ll also give YouTube view information, as well as giving you a breakdown of video views and interactions based on when the video was posted, it also offers cumulative figures which show how the performance of a video improved over time.

Tweetreach will give estimated reach for hashtags and keywords, by searching for a specific enough phrase, you can get an idea of reach for individual tweets, or a number of related tweets if you’re smart about it.

Content shares

This is specifically people sharing a page of your site on a social network. It may help us flesh out some of the impressions metrics we’ve been dancing around, particularly in terms of content from your site or competitors’ being shared by site visitors rather than an official account.

What business goal does this relate to?

Impressions, site visits generating ad revenue

What numbers should you use?

To control for volume of content created by different sites, I would look at both total number of shares and shares per blog post, for example, during the same time period. It could also be valuable information to sum total follower count of the accounts that shared the content, to weight shares by reach, but that could be a huge task and also opens us up to the problems of follower count.

What tools should you use?

Buzzsumo will let you search for shared content by domain, and will let you dig in to which accounts shared a particular item. It can give a slightly imbalanced picture because it’s just looking for shares of your website content (so don’t expect the figures to include particularly successful social-only content for example) but it’s an excellent tool to get a quick understanding of what content is doing how well, and for who.

Link clicks

This can be difficult information to gather but given its potential value to our business goals it’s worth getting this information where we can.

What business goal does this relate to?

Site visits generating ad revenue, event attendance, sales, depending on where the link is pointing.

In my experience it’s usually much harder to get users to click away from a social media platform than it is to get them to take any action within the same platform. Sharing links can also cause a drop in engagement, often because the primary purpose of the content isn’t to encourage engagement – success with a user often won’t be visible at all on the platform.

What numbers should you use?

  • Clicks per (link post*follower) (where you multiply total follower count by total updates posted)
  • Clicks per link post
  • Total link clicks

What tools should you use?

Understandably this is fairly locked-down, Fanpage Karma again goes out of its way to get you the data you need, and does offer to plot posts against link clicks in one of those scatter graphs we love. I’ve reached out to them for information on how they collect this data, will update when I hear back. As with impression data, click data can sometimes be patchy – the platform seems to miss data consistently across metrics.

Outside of that, the best trick I’ve found is by taking advantage of link shortener tracking. For example, anyone who uses free service Bit.ly to shorten their links can also get access to link click stats over time. The thing is, those stats aren’t password protected, anyone can access them just by copying the Bit.ly link and putting a + sign at the end before following the link.

Here are the stats for a link Donald Trump recently shared in a tweet.

Go forth and analyse

Hopefully, some of the metrics and processes I’ve included above prove helpful when you’re next directing your social media strategy. I would never argue that every single one of these numbers should be included in every competitor analysis, and there are a whole host of over factors to include in determining the efficacy of a community, for instance; does the traffic you send convert in the way you want?

That being said, I think these numbers are a great place to start working out what will make the difference, and will hopefully get us away from that frequent focus on follower numbers. If there are any numbers you think I’ve missed or any tips and tricks you know of that you particularly like, I’d love to hear about them in the comments below.

Distilled

 

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