As noted by Facebook’s chief product officer Chris Cox to Bloomberg – and re-affirmed by Mark Zuckerberg himself in this week’s Facebook full-year results announcement – Facebook’s ‘Reactions’ emoji toolbar will be available to all users soon. For those unaware, ‘Reactions’, which The Social Network announced back in October, is a way to give Facebook users the ability to respond to posts with something other than ‘Like’. The typical use-case of Reactions was explained by Zuckerberg at one of his regular Town Hall Q & A events last year:
“Not every moment is a good moment – if you share something that’s sad, like a refugee crisis that touches you or a family member passes away, it may not be comfortable to like that post… I do think it’s important to give people more options than liking it.”
For a long time, Facebook users have called for a ‘dislike’ option, but Facebook has (rightly) deemed that too negative and a tool that could lead to a lesser user-experience. Their alternative solution was to develop a toolset which utilises the rising trend of emoji, as well as the most common, one-word responses used across Facebook’s network, to create a set of emoji-type responses which people will be able to use in place of the traditional ‘thumbs up’.
Those emoji responses, based on Facebook’s data, have been refined down to:
In their first iteration, there was also another option:
But initial testing among users in Spain and Ireland found that ‘Yay’ was often misunderstood – and really, it’s largely redundant either way, given users already have ‘Like’ and ‘Love’ as options.
In application, when a user clicks/taps and holds on ‘Like’, a new pop-up will appear from which they’ll be able to choose a ‘Reaction’ that best fits their response.
So what do these new options mean for marketers? In a word: insight.
Some Facebook Pages already have a graph like the below, ready to track data from Reactions use within their Page Insights:
It’s evident from this that Facebook sees analytical and insight value in Reactions, and they’re giving Page owners the tools to track them, straight up – though interestingly, Facebook’s also made a point of noting that any ‘Reaction’, at least initially, will be measured as equivalent to a ‘Like’ in their system. So if someone clicks on your Facebook ad and selects ‘angry’ in response, that’ll actually increase the likelihood of them being shown more of the same content, because any reaction is counted as a ‘Like’, and within Facebook’s algorithm, likes are indicative of preference. While it’s understandable that Facebook wouldn’t necessarily have a way to measure the true value of Reactions in the early stages of their roll-out, the measurement of a Reaction as a Like does raise an interesting query – if a user tags their response to something as ‘Angry’, does that mean they want to see more or less of that type of content?
This is where the complexity of Reactions comes into play – what do those responses mean, in terms of audience interest and intent? And then, how will marketers be able to use that insight to better refine and maximize their content? This’ll be a big focus for social media marketing types over the next 12 months, and the only definitive way to establish what each Reaction means will come via experience and use. And even then, different Pages are going to see different results – a news service might see better engagement when they post content that generates more ‘Angry’ responses (as it’ll get more people talking about the topic, and thus, generate more reach), but then a brand selling natural soaps might see better website visits and conversion rates with posts which inspire more ‘Like’ or ‘Love’ reactions.
The only way to know for sure is through experimentation. The goal of all content is to generate an emotional response – emotion drives the majority of our responses after all (particularly in regards to purchases), so it makes sense, by extension, that having further insight into a users’ emotional responses to our content can only help inform our marketing decisions. But exactly what each response means, in a wider context, can only really be ascertained by seeing how it’s used across that expanded scope.
This is the same with all of Facebook’s data – one person deciding to ‘Like’ a Page in response to a post has little meaning in itself, but 1,000 people following the same path indicates a trend. When you extrapolate that across Facebook’s now 1.59 billion users, you can start to get an idea of how valuable even the simplest action might be, because it’s matched up against trillions of other data points and processes, and it’s in that wider sample size that genuine insight takes shape.
In this sense, the only way to know how valuable Reactions will be for marketers is to examine the data after they’ve been implemented and look for usage patterns and correlations. And they will be there. More data – especially more emotional data – can only be beneficial.
And at some stage, you may just find that Reactions data is able to highlight insights that would have never been discernible via Likes alone. Powerful, indeed.
Late last year, I attended an education session on Facebook’s News Feed algorithm, conducted by a social media lecturer of relatively high standing in the field. The session sounded great – insight into how Facebook’s News Feed algorithm actually works, the ‘hows’ and ‘whys’ of what appears in your News Feed and what brands can learn and implement in order to boost their organic reach. Organic reach, as anyone with any exposure to social knows, has been declining at a rapid rate – brand Pages these days are lucky to reach 10% of their total fans with each of their Facebook posts.
The info session sounded like a great learning opportunity, a great way to get some insight into how to work with the algorithm to maximize Facebook performance.
Except, the information presented was largely wrong.
This person, who speaks and presents to a great many people on social media best practices, outlined strategies that were either out-dated, ill-informed or just plain incorrect, yet stated them as total fact. And as other attendees narrowed their eyes and nodded along, I felt like standing up and saying ‘no, that’s not right’. But then that would assume I was right, and given Facebook’s secrecy around the specifics of their News Feed algorithm and how it works, maybe I actually had it wrong. Maybe what was being presented here was the correct info.
In order to get to the bottom of this and clarify for all those looking to maximize the performance of their Facebook content, I did some research into what’s known about Facebook’s News Feed algorithm and how it selects what content will be shown to each user, every time they log on. And while we can’t know every specific factor that plays a part in how content is distributed on the platform, there are quite a few well established principles that clearly indicate the path to best performance.
First off, a bit of history.
When Facebook launched News Feed back in 2006 it was a straight-up, chronological feed of all the activity of your connections.
Remember that? The basic looking blue links, the green speech bubble comments.
The ‘Like’ button was introduced a year later, giving Facebook its first insight into what users were actually interested in, and as Facebook became more popular, and more people started using the service – and the News Feed, logically, got more cluttered – Facebook started using those Likes (along with other measures including shares, comments and clicks) as indicative signals to prioritize the content appearing in each users’ News Feed to ensure posts from Pages they’d indicated interest in appeared higher in their stream.
This worked for a while, but there were a couple of problems with this basic approach.
The first issue was that people clicked ‘Like’ for different reasons – funny cat pictures were getting heaps of Likes, and thus, flooding peoples’ News Feeds, while more serious news content, which people weren’t clicking ‘Like’ on (because they didn’t necessarily ‘Like’ it), was being totally buried. Publishing click-bait style headlines became a key tactic as these garnered lots of Likes and clicks, pushing them higher in News Feed ranks – eventually Facebook was at risk of losing their audience because people’s Feeds were being crowded with junk and there was no way, under that system, for Facebook to filter and uncover better, more relevant information for users.
In 2013, Facebook acknowledged it had a problem on this front and sought to correct it with a new algorithm that would uncover ‘high quality content’, the first iteration of the News Feed algorithm.
The second issue confronting The Social Network was that Facebook was getting big. Really big. People were adding more friends and Liking more Pages, meaning there was more and more competition for attention within the News Feed listings. But people only have so much time in the day to check their Facebook updates – according to Facebook, an average Facebook user is likely to have around 1,500 posts eligible to appear in their News Feed on any given day, but if people have more connections and Likes than average, that number could be more like 15,000.
Given this, it’s simply not possible for every user to see every single relevant post, based on their connection graph, every day. Facebook’s challenge with the algorithm was to create a system that uncovers most relevant content each day to provide every user with the best possible experience in order to keep them coming back. But that would also, necessarily, mean that Facebook would have to show some content people had indicated an interest in while excluding others which may also be of interest. The system needed to be incredibly clever to get this balance right.
“If you could rate everything that happened on Earth today that was published anywhere by any of your friends, any of your family, any news source, and then pick the 10 that were the most meaningful to know today, that would be a really cool service for us to build. That is really what we aspire to have News Feed become.” – Chris Cox, Facebook’s chief product officer (to Time Magazine in July 2015)
These were the two major challenges facing Facebook in developing the News Feed algorithm, and despite the protestations of brands who were forced to sit idly by as their organic reach slowly declined (and who were rightly annoyed at Facebook for promoting Likes as a means of reaching audience, then reducing their relevance), the numbers show that Facebook’s machine learning curation process for the News Feed is actually working. In their most recent earnings report, The Social Network reported that engagement was now up to 46 minutes per day, on average, across Facebook, Instagram, and Messenger, with Monthly Active User numbers also continuing to rise.
The continued rise of Facebook shows that they’re getting the user-experience right – brands don’t like it, many users don’t even know it’s happening, but the News Feed algorithm is working as a means of rationalizing and boosting user activity.
This finding, in itself, highlights just how much Facebook understands about their users and their likely preferences.
Inside the Machine
So how does the News Feed algorithm actually work? While the company’s understandably tight-lipped about the specifics of the News Feed calculations (largely because it’s continually evolving), the basics have been communicated by Facebook several times over the years.
Back in 2013, when Facebook introduced the first version of the News Feed algorithm, The Social Network noted four key points of focus for people creating content on the platform:
- Make your posts timely and relevant
- Build credibility and trust with your audience
- Ask yourself, “Would people share this with their friends or recommend it to others?”
- Think about, “Would my audience want to see this in their News Feeds?”
Those core principles remain the fundamentals of the News Feed – in a 2014 interview with TechCrunch, Facebook News Feed Director of Product Management Will Cathcart outlined a similar listing for the ‘most powerful determinants of whether a post is shown in the feed’:
- How popular (Liked, commented on, shared, clicked) are the post creator’s past posts with everyone
- How popular is this post with everyone who has already seen it
- How popular have the post creator’s past posts been with the viewer
- Does the type of post (status update, photo, video, link) match what types have been popular with the viewer in the past
- How recently was the post published
Cathcart’s advice lead to development of this equation, which is a basic overview of how News Feed prioritizes content:
(Image via TechCrunch)
Of course, as noted, there are many more factors than these at play, but at its most basic, this is the logic behind how Facebook chooses and displays the most relevant content to each user. But that system is always being refined.
Those refinements are borne of necessity – more people using Facebook means more content and more variables to take into account to ensure the best possible user experience for each individual. To get an insight into just how complex that equation is, take a look at the documentation behind Facebook’s ‘Unicorn’ social graph indexing system. While Unicorn was built to power Facebook’s Graph Search engine, the way that system works highlights just how many factors can come into play when trying to uncover the most relevant content for each user – particularly when you consider that a typical Facebook user’s relationship graph looks like this:
In the Unicorn documentation, Facebook refers to the amount of ‘nodes’, signifying people and things, and ‘edges’, representing a relationship between two nodes:
“Although there are many billions of nodes in the social graph, it is quite sparse: a typical node will have less than one thousand edges connecting it to other nodes. The average user has approximately 130 friends. The most popular pages and applications have tens of millions of edges, but these pages represent a tiny fraction of the total number of entities in the graph.”
And in the introduction to the document, Facebook notes that:
“Unicorn is designed to answer billions of queries per day at latencies in the hundreds of milliseconds”
Even without a full grasp of the technical complexities of such inter-connectivity, you can still imagine how complex Facebook’s algorithm needs to be to serve up the most relevant content, and how many potential variations need to be taken into account.
This is why it’s almost impossible to explain the full extent of how the algorithm works, and why Facebook largely avoids doing so. It also enables them to make changes without worrying about what they’ve said previously – if Facebook were to say ‘this is how the system works’ then make a change that altered that, brands that had structured their Facebook strategy around the previous rule would be disadvantaged (which is pretty much what happened with ‘Likes’ when they changed the rules). As such, the core principles noted above remain the driving force, and the key elements marketers should logically be focused on. The further complexities and refinements work to support these fundamentals – adhering to them should keep you in good stead.
In line with this, Facebook’s always seeking to refine and update the News Feed algorithm to better serve their users and deliver an evermore relevant on-platform experience. Time Magazine recently reported on how Facebook uses two primary devices to help refine and improve the News Feed algorithm – a team of around 20 engineers and data scientists who assess and evaluate the results of tests and updates to determine the best evolution of the system, and a group of some 700 reviewers, called Facebook’s ‘Feed Quality Panel’, who deliver real, human feedback on their News Feed results, which then help the data team make more informed choices.
“…[members of the Feed Quality Panel] write paragraph-long explanations for why they like or dislike certain posts, which are often reviewed in the News Feed engineers’ weekly meetings. Facebook also regularly conducts one-off online surveys about News Feed satisfaction and brings in average users off the street to demo new features in its usability labs.”
Through this process, combining feedback from real people and improved machine learning, Facebook is continually moving the News Feed algorithm forward and uncovering new best practices. This is why we see so many changes and updates to the algorithm rules, newer factors like ‘time spent reading’ are brought in as Facebook learns from user behavior – content that people click ‘Like’ on before reading, for example, is not given as high a rating as content that’s Liked after reading (after a person has clicked through on a link), because if you’ve taken the time to read something and then Liked it, that’s considered a stronger endorsement of of quality than a knee-jerk response to a headline. Such refinements are logical and thoroughly tested, and Facebook’s gone to efforts to underline that the way the system is weighted is entirely dictated by each individual users’ actions and preferences.
The way Facebook’s algorithm defines ‘high-quality’ in this sense is entirely user driven – if you like cat memes but hate posts from The New York Times, you’ll be shown more of the former and less, if any, of the latter.
“…there’s a line that we can’t cross, which is deciding that a specific piece of information – be it news, political, religious, etc. – is something we should be promoting. It’s just a very, very slippery slope that I think we have to be very careful not go down.” – Adam Mosseri, Project Management Director for News Feed
Due to this, it’s up to each individual brand and business to create content that appeals to their specific audience, and caters to that audience’s needs.
It’s worth noting too, in considering Facebook reach and how to worth with the system to maximize reach and performance, that the actions users take after exposure to your content are far more important than them seeing it in the first place.
This was pointed out by Facebook marketing expert Jon Loomer, who noted that even if your Page reach has declined, that’s not really relevant – what is relevant is whether your website clicks have also declined as a result.
“Let’s assume for a moment that reach actually did drop. If all engagement remained healthy — including website clicks and conversions — what does that drop in reach mean? It would mean that Facebook was showing your content to people most likely to engage favorably — which is what we as marketers and users would want.”
It may just be that, as a consequence of Facebook improving their algorithm, that your Page reach will inevitably drop, because your content’s being shown to a more targeted and focused audience based on their behaviors. And that isn’t necessarily a bad thing.
In all, the main thing to focus on in order to maximize Facebook reach and response is quality content, as defined by audience response. The more utility and value you can provide for your audience, the more likely they’ll want to see more information from you, which they’ll indicate through their Facebook actions – be those direct (Likes, shares, comments, clicks) or indirect (time spent viewing, word-of-mouth via off Page comments). Facebook’s tracking all of it, and in this sense, the core fundamentals of Facebook content remain the same as they did the day the News Feed algorithm was introduced back in 2013:
- Make your posts timely and relevant
- Build credibility and trust with your audience
- Ask yourself, “Would people share this with their friends or recommend it to others?”
- Think about, “Would my audience want to see this in their News Feeds?”
The News Feed is constantly evolving, but its fundamental principles remain the same. Understanding your audience is key to maximizing your Facebook reach.
The new battleground of combined social and search is going to become a significant storyline in the world of social media marketing this year. Last week, we saw the first examples of what tweets might look like in Google search results as part of Twitter’s new deal with the search giant. It’s now being reported that Facebook is testing a newsearch feature – not quite on the same path, but more significant than it may, initially, seem.
Facebook is testing out a new functionality for iOS users which enables people to search for links while composing a status update, in-app. Just like adding a picture, the function would enable users to click on a link icon, then do a keyword search for articles related to that topic in order to share that content with your update.
At a glance, this seems relatively minor, adding in links is no major upgrade, it’s just streamlining that process – and really, it may be slightly restrictive, most people like to be able to share the exact links to the exact posts they want, and searching via this method might not necessarily help you locate the right content any more efficiently than searching outside of the app and cutting and pasting the link yourself. But then again, it might. And considering the massive amount of mobile sharing Facebook hosts, this process could prove hugely popular, effectively cutting Google out of the equation and keeping users on Facebook longer. And what’s more, it would also grant Facebook more control over more information, in the form of search data, which it could use to entice more publishers to its publisher platform. And that might just be the start.
Mo’ Data, Mo’ Options
So, let’s say this becomes a popular practice, that people are finding the links they want via this search process, Facebook learns your favourite websites and can better provide contextual searches, based on your previous sharing behaviour. That being the case, couldn’t Facebook then use that in building its case for publishers to post first-run content direct to Facebook? What if, as part of their pitch, they could say that “people use this new in-app search functionality 35% of the time, and we control the search results they get – we could ensure your content appears high in those results, significantly increasing the chances that users will link to your posts, thereby increasing your overall audience.” That’s interesting, right? What, too, does that increase in searches on Facebook do for Google traffic and Google’s share of audience? We know that Facebook leads social referral traffic by a significant margin (and that’s not even counting dark social shares) – if this addition were to catch on, it could be a significant concern for The Big G’s hold on search traffic.
Obviously, these are extrapolations, we have no idea how this is going to go till we see it in the wild and we get some stats on how users view this addition. But it could be something. It could be more significant than it may seem, at this early stage.
Earlier this week, Facebook updated their News Feed algorithm again, in what many are seeing as the next move towards ‘Facebook Zero’ – i.e. 0% organic reach for pages. Facebook announced three updates – the first is around users who don’t have a lot of content to see. Previously, the algorithm ensured people were not shown multiple posts from the same source in a row, they’re relaxing this measure for people who run out of content to view and are seeking to view more. Nothing major there, the impacts should be minimal.
The second update has a bit more to it – as noted in Facebook’s announcement, this update:
…tries to ensure that content posted directly by the friends you care about, such as photos, videos, status updates or links, will be higher up in News Feed so you are less likely to miss it. If you like to read news or interact with posts from pages you care about, you will still see that content in News Feed. This update tries to make the balance of content the right one for each individual person.”
So the focus of this one is on those friends who you regularly interact with, on showing you more content from those users and ensuring those posts appear more prominently in your feeds. This is based on your interaction history – Facebook will use past behaviour as a guide to add weight to the prominence of friends’ posts and ensure they appear higher in your results. This will impact page posts because it will be adding increased preference metrics to content posted from certain profiles – most probably, the impact of this will be minimal, but if a person is more likely to be shown content from friends, they’re conversely less likely to see posts from pages in their daily News Feed allocation.
The third update relates to posts that friends have liked or commented on:
…many people have told us they don’t enjoy seeing stories about their friends liking or commenting on a post. This update will make these stories appear lower down in News Feed or not at all, so you are more likely to see the stuff you care about directly from friends and the pages you have liked.”
Again, the precise impact of this change is hard to predict, but it underlines the fact that ‘likes’, in themselves, are becoming little more than an aesthetic measure – and worse, that even interactions like comments are not necessarily going to increase your post reach. This change inadvertently puts more emphasis on shares and on prompting users to take direct action to explicitly promote their support of your page.
So what’s that mean for Facebook marketing? This change further underlines the need for brands to move from a broadcast focus to making themselves part of the conversation. With this update, Facebook is essentially saying that their users want to use the platform to interact with friends and the content they’re individually interested in, and the only way to effectively promote your pages without moving to paid ads is to generate conversation amongst people independent of your properties. That’s obviously easier said than done, but the principle for Facebook marketing remains that you need to create great content, you need to listen to what your audience wants and is responding to, and you need to become part of those conversations in order to attract more direct interactions with individuals and ensure your brand is part of any relevant conversations.
This also underlines the need to work with individual advocates – I’ve already seen it suggested by some that maybe brands should create personal profiles to help get better reach amongst their communities, but that won’t work, as it’s in violation of Facebook’s terms. Having people speak on your brand’s behalf is the best way to ensure you’re maximising Facebook reach – this is why employee advocacy is becoming a big focus, because who better to speak on behalf of your brand than those who live it everyday? Happy, engaged, socially-empowered employees can play a big part in brand awareness, and this update only reinforces the need to consider ways to facilitate authentic conversations across Facebook’s social graph.
This also sets the stage for updates to Facebook’s own search capabilities – Facebook recently announced changes to their API, effective April 30, which will reduce the capabilities for third party apps, particularly in relation to personal profiles, groups and search functionality. These changes seem relatively small, but for Facebook to be restricting them, my guess is that they’re close to releasing improved search functionality within their own walls, hence, these changes are designed to keep people on Facebook, as opposed to managing their Facebook presence via other platforms. This News Feed update somewhat supports this, in that it puts more emphasis on search to find content, as opposed to tangential organic reach.
Whatever the outcome, it’s clear that this update doesn’t help Facebook marketers and further supports the looming dawn of Facebook Zero. So should you just move on and forget about Facebook marketing? Depends on your audience, depends on how this changes your engagement levels – depends on many individual factors that can’t be answered in a generic sense. The fact is that Facebook has 1.44 billion active users, and many of them are likely interested in your products and services. Reaching them might not be as easy as it once was, but it is still totally possible, and totally viable when done in a considered way.
So, if a social media expert, or someone going under a similar moniker, comes to you and tells you that absolutely have to create video content, it might be time to look for a new advisor. Video is powerful, no doubt, and it’s a great way to generate engagement and build your brand online – the expanded capacity of our mobile networks and the evolution of apps and social platforms has enabled a new age of video communication. But if you’re only producing video content in order to make videos, to ‘do video content’, it’s quite possible that you’re missing the point, and will struggle as a result.
A Question of Quality
The thing is, bad content is bad content. It won’t matter if it’s video, audio, performance art – if no one likes it, it won’t get shared. Actually that’s not true, maybe people not liking it is what you’re going for, and that leads to people sharing – if it’s not sparking an emotional response of some kind, it’s going nowhere. And this is the biggest risk in the new wave of video content – while everyone should consider and be encouraged to think about how they can utilise video, if you don’t have an original or interesting idea, it may not be worth doing. The increased emphasis on video is seeing people make video content for the sake of making it – I’ve seen people post video of themselves holding their new products as they wave a description card along the bottom of the screen. I’ve seen content like this, from Mike, who, evidently, buys golf clubs:
Okay, bad example, that’s actually been shared a heap of times, but you get my point – making video for the sake of making video is probably not the best way to go. I mean, it won’t cost you a heap – the array of video recording and production apps these days enable anyone to make good quality video at low cost – but the problem is, if the quality of video content, overall, starts to drop, and people’s news feeds get flooded with average quality posts, users will rightfully complain. And complaints lead to algorithm shifts.
“And Like That… He’s Gone”
Facebook, above all else, values user experience. This has been debated over time, whether they care about users or money, but Zuckerberg’s line has always been that user experience is their number one priority. And it’s hard to argue it isn’t, almost every major Facebook algorithm shift has been triggered by user feedback; users said they didn’t like clickbait, so Facebook altered their filter; users didn’t like overly promotional posts, so they were de-emphasised by the algorithm. Facebook knows that, above all else, their power is in audience engagement on the platform. And they also know that people can and will migrate to other platforms, the social landscape can change very quickly. They know this, of course, because that’s how Facebook supplanted MySpace. In social media, if you lose the crowd, you lose, a fact that all the major platforms are acutely aware of, and as a result, they tread more carefully than ever when rolling out updates and features.
So what happens when people start seeing an increase in content they don’t like? They complain, and Facebook is forced to re-evaluate how that type of content is distributed. Right now, native video content is getting the highest organic reach of any post type, but that could change, and that change could literally happen overnight. Currently, Facebook’s distribution algorithm is pretty good at filtering out low quality content – organic reach is, of course, at the lowest it’s ever been, so it’s pretty hard to reach a significant audience either way, and their ad filtering works on a quality scoring-type system to reduce the reach of ads that no one’s responding to. Low quality content, in whatever form that may be, degrades user experience and forces Facebook to re-evaluate how they distribute content to satisfy the needs and expectations of users. Making bad video content is bad overall, as you’re not only potentially hurting your own reach (in terms of post performance influencing future content), but you may also be contributing to a wider resistance to video posts, overall.
There Can Be More Than One…
The argument here is not video or Facebook-specific. – there’s an inherent risk to over-emphasising any one type of content. If you force people to create video – or blog, or post infographics – making people focus on any one type of content will inevitably lead to some people struggling to produce quality work. I love blogging, I write all the time, but I know plenty of people who struggle with it and I’ve seen them post average quality work which, understandably, is getting little engagement, and this is frustrating for them because they’ve been told they absolutely, definitely have to blog. But maybe they’d be better off focussing on something they can do confidently – it’s possible that they could have massive success producing live streams for Periscope. Maybe they’re no good at writing, but really good at conversation – Hangouts on Air or Twitter chats might be a better focus. Definitely, written content is a key element, particularly for SEO purposes – and outside production assistance is always an option (cost prohibitive) – but you might also be able to also utilise transcripts, Storify logs – there are different ways to ensure you’re ticking all the content boxes.
To say anyone needs to create content of any specific type is potentially risky, and with so many options now available to connect, it may be keeping them from their best option to generate interest and engagement.
What’s Good for Them is Good for You
So what content should you focus on? The best way to make content your audience will love is to listen to them. Analyse what your communities are talking about, look at the key interests and topics being discussed amongst those most likely to buy from you or your business. You can use apps like Social Crawlytics to establish where and what content is driving the most social referrals to your site, or BuzzSumo to search for what content is being most shared amongst those in your industry. If you don’t have enough content to go on, run your competitors’ websites through those apps and see what’s driving the most engagement for them – if they’re seeing a heap of engagement with image posts or quizzes, maybe that’s what you should do too.
If you can identify trends or commonalities amongst your audience, you can let those fuel your ideas for content – this will enable you to work with what your audience is after, what they’re most likely to respond to. And of course, this is not to say you should be afraid to try or resistant to testing out what can be done with any type of content – video is generating great response and there’s a wide range of tools available to experiment with. But you shouldn’t be making video for the sake of making video. There’s no point to that and you’re likely not helping your brand any by posting video content that lacks passion, purpose or any spark of creativity. Content is crucial, but what type of content you create should be driven by what your audience is responding to and what’s within your capacity to provide.
But then again, it’s always possible that your worst idea might end up getting the most attention. Now, I’ve gotta go find some old golf clubs.
I was doing a talk recently on the correlations between Facebook likes and personality traits when someone put their hand up and said: ‘so what?’ What does this mean – what does it matter to the average business that Facebook likes can indicate a person’s personality? It got me thinking about how to better communicate the relevance of social media and social media data and how it relates, not only to academic studies, but why it’s important, and indeed, good for all businesses to be involved and to understand the possibilities of quantifiable interactions.
The Facebook Study
Earlier this year, researchers from the University of Cambridge and Stanford University released a study which suggested that a person’s Facebook ‘Like’ profile could be more indicative of an individual’s personality traits and leanings than their friends, family members, even their partners. The study was conducted by getting 86,220 participants to complete a 100-item personality questionnaire, based on the International Personality Item Pool (IPIP) five-factor model, which measures each person’s responses and maps them to build a personality profile, based on the ‘big five’ personality traits.
Within each of these categories are sub-sets, more specific data points based on these over-arching personality points. Based on those responses, each participant’s personality profile was created, then matched against their Facebook ‘Like’s.
Now, on a small scale, this doesn’t mean a heap – a person who scored high for anxiety also likes Star Wars – so what? But on a wider scale – when matching this data over, say, 86,000 responses – correlations between interests solidify. Change the equation to 95% of people who scored .80 or above for anxiety also liked Star Wars and you’re starting to see that map. The researchers found that when the individual had 150 Facebook likes to go on, their model could predict their personality traits better than their family members. With 300 likes, it beat out their partners. And when you consider that the average Facebook user has liked more 220 things, you can see how this system could be used as an accurate predictor for a person’s traits and behaviours.
So what does that matter?
So what? What’s the big deal, right? It’s one thing for academics at some big name institution to some up with a complex methodology for indexing personality traits – and good for them – but what does this actually mean for you or I, for the everyday business owner? This is an interesting question, because you can’t just extract these sorts of insights in any easy way. It takes teams of data scientists to build such a model – months, years of learning to implement at such scale. What this research does highlight is the possibilities and potential of big data and social media. What it shows is that business owners should not be resisting social or avoiding it – they should be actively embracing and encouraging its use. Even if that business wasn’t overly interested or inclined to get involved themselves, the potential value of such insights for their own audiences are so great, so massive, that they should see these interactions as access to a whole new way of thinking.
How so? Consider this:
Ninety per cent of the world’s data has been generated over the last two years. Ninety per cent. That means everything that exists now, all the resources, status updates, like profiles – all but ten per cent of that was non-existent just two years ago. It’s not possible for any of us to truly understand what that means for business, for our day-to-day lives, for everything as we know it, because we haven’t had enough time to process all that info and figure out how it all relates. Definitely, where the emphasis has been on big data in recent years, the latest push is on how we rationalise and contextualise all that info. Big data has become a buzzword, people have become more wary, because for all the insights and intelligence we have at our fingertips, no one’s really sure how to utilise it. This comes back, somewhat, to futurist Ray Kurweil’s ‘Law of Accelerating Returns’, which stipulates that more advanced societies and technology progress at a faster rate than previous ones – so we’re now progressing faster than any generation before us, and thus, we can’t rationalise and compute all these new inputs all at once because our brains are still adapting and working to get up to speed.
This is, in large part, why we’re often not able to see the possibilities of big data and all those advancing connections – that, and the context for them is often presented in such a way that it’s difficult for someone without an advanced qualification in psychology or analysis to fully grasp the significance of a concept like Facebook knowing you better than your wife. The consideration that I see is actually two-fold: the future and the present.
As data advances, I see massive potential in all those reference points leading businesses and individuals to each other. In the case of the individual, let’s say that your Facebook profile – which we now know can be an accurate indicator of your personality – is only part of the overall puzzle.
Combining an individual’s activity on all three of these platforms would form an even clearer picture of who they are, not only in a personal sense, but professionally as well. When you consider that the next generation has grown up on social (remember, Facebook is now more than 10 years-old), and think about how much information each user has accumulated and logged online, you can imagine that if this data were combined, at scale, you would have a pretty accurate indicator of personality and career-oriented traits. This would enable you to make better decisions about employing people, build better understandings about the correlations between performance and personal traits, track the specific interests and personality types of the people who have purchased from you, enabling you to target future customers based on informed correlations.
At present, this data is not easily combined, as each platform keeps their own knowledge graph, but there are ways to extract such insights. There are methods you can use to build accurate personas – the next step is to build systems that track and expand your own data analysis in real-time. Imagine if you could build a system that logged the traits and behaviours of people who both Liked and went on to purchase from you, which updated in real-time. Imagine then that, armed with this knowledge, you could target your advertising or identify people to connect with based on those same traits, effectively highlighting your most relevant and responsive audience, based on data, and showing you new opportunities, every day. This is where the true power of social media data and data analysis lies – being able to locate and reach the right people, with the right content, at the right time – all the time. And with more and more data being entered, the reality of this scenario is becoming increasingly present. It pays to know what’s happening in this sector.
But again, that’s the future, that’s still some distance – and some cost – away from your day-to-day business, your real world grind. How does social media data deliver real, actionable, insights for you, right now? Really, with the amount of data we’re talking, how could it not?
For instance, let’s say members of your target audience – the people you need to get your brand name in front of – are active on social media. You can work out who, specifically, you need to be listening to, who your most likely prospects are, based on people who’ve previously purchased from you or people in positions that will make the call on whether or not to buy your stuff. You can analyse the presences of those target prospects and get an idea of what their questions are, what they’re discussing, what they’re most interested in. Let’s say you identify that a large portion of your audience is talking about a new TV show – you could use that in your own communications (contextually relevant, of course) and create content that’s more likely to resonate with the people you need to reach based on their specific interests.
Or you could work out who they listen to – word-of-mouth is the core thread of social selling. If you can work out that your target audience is listening to a specific influencer or influencers, you can examine their profiles, work out what they’re interested in, then reach out to them and connect to your target audience that way, by connecting through their established information sources and getting your name in front of them.
You can analyse your fans, followers, lurkers – there are any number of free or freemium social tools out there that enable you to extract specific insights and data about your social media audiences – both current and desired. And as the amount of interactions being undertaken online increases, so too do your chances of locating the information you need in your research. Right now, you can do this, right now, you can analyse the profiles of your business and your competitors and extract data insights and virtually no cost.
The Interaction Evolution
The Facebook Like study, to me, actually just reinforced or legitimised the power of social media data. Many people still see social as a fad, as nothing more than kids sharing pictures of themselves and/or their food. But if academia has found that those very actions can paint an extremely accurate picture of who a person is, you must also see that such data can form a map connecting your brand to your audience. Even if you’re not interested in social, if you’re not on the bandwagon, so to speak, have no interest in hashtags and LOLs and cute cats, you still have to recognise that social is the most powerful audience insights tool ever created. As Jay Z says:
If you can’t respect that, your whole perspective is whack”.
Maybe your audience isn’t on it – but are you sure? Maybe your customers don’t use it – but will they soon? The way people communicate has changed, the way we interact is evolving. Right now, you can livestream your life to the world, a level of connectivity that is unprecedented, would have been unfathomable just years ago. And that evolution is accelerating at a rate that we may not even be able to fully comprehend. What we do know is data. That which is happening is trackable, traceable, laid-out and accessible to anyone who cares to look. Used well, this can provide your business with a level of insight you’d never have even considered.
And that is good for business.
Do you ever come across a business profile or page and think ‘what the…? How did they get 3,000 followers?’ As with most things in life, if something seems fishy, there’s a good likelihood that it probably is, and with the fake social media profile industry worth hundreds of millions of dollars per annum, it’s not hugely surprising to find out many individuals and brands have taken this route. Like, a heap of them have – just take a look at the results from the recent Instagram fake profile purge, where a whole range of celebrities took big hits in their follower counts.
And it makes sense, having more followers and likes can definitely improve your brand position – if you’re looking for a service online and find two similar providers, one with 38 likes and another with 3,000, the latter one’s gonna’ stand out – but with the practice of buying followers and likes so widespread, it’d be great to also have a way to work out who’s telling the truth, right? Here’s a couple of ways to work out if they’re telling you the fibs.
How to work out is someone’s Twitter followers are fake
Twitter is the open network, the one where people go to broadcast their thoughts and voice their opinions on the happenings of the world. As such, the biggest advantage of Twitter is that most of their data is publicly accessible, which makes it easier to work out what brands are doing, what strategies their employing – and also, whether they’re faking. It’s actually pretty easy to spot on Twitter, even without any significant investigation.
When looking through Twitter, it’s not uncommon for a celebrity to have a follower to following ratio that looks something like this:
Gotye’s not a prolific tweeter, and as such, he’s not following a heap of people. But he’s Gotye, he’s a world-renowned musician, and his fans are keen to hear whatever it is he has to say – hence, despite him not following back many folk, he still has 414,000 followers. That makes sense for a public figure with a large fan base, but when you come across a non-public figure, someone you’ve never heard of, with a similar follower/following ratio, that’s a pretty clear indicator that something’s amiss.
There are a couple of options for testing this on Twitter – Status People’s ‘Fake Follower Check’ is one, Social Bakers, too, has a free fake followers test you can use – but my favourite is Twitter Audit, also free, very quick and very easy to use. The difference between each of these, and why I prefer TwitterAudit, is the number of records they check to get an indication of how many fake followers each profile has.
Of course, the accuracy of each is relative to the amount of followers the subject has – the percentage of followers you’re testing decreases in-line with increases in follower count – but generally this data has been found to be indicative, when compared with tests on a more comprehensive scale.
To conduct a Twitter Audit, you just enter the handle you wanna’ check, sign-in with your Twitter credentials, and away you go. How the test works is, it takes a look at that random sample of up to 5,000 of the person’s followers and it looks at a range of factors for each – number of tweets sent, date of last tweet, follower/following ratio, etc. From this, the system determines which of those tested profiles are likely fake, then gives you a percentage and pie chart based on those findings:
There is, of course, a margin of error in this data, but it’s normally a fairly accurate indicator, particularly when analysing profiles with less than 5k followers.
To clarify and confirm the data further, you can conduct a manual check – paid tools like Followerwonk or Socialbro provide in-depth reports on follower growth over time. If you look up a profile and find a big drops or jumps in their follower numbers, like this:
Pretty safe to assume those followers didn’t all randomly switch off in the same week (unless, of course, there was an offending tweet or similar logical connection).
Using the available apps, it’s pretty easy to work out Twitter fakes. Twitter’s always working to eliminate illegitimate profiles, so we might one day see an Instagram style purge with a heap of celebrities taking hits. But till then, if you ever need confirmation, just run ‘em through a Twitter Audit, then sit back and scoff at their vanity.
How to work out is someone’s Facebook likes are fake
Facebook fakers are a little harder to pin down. Unlike Twitter, most of Facebook’s data is locked up or hidden behind privacy settings, making it a bit more difficult to determine, definitively, if someone’s cheating. There’s a few ways to go about it and while none of them will provide as clear a result as the Twitter audit options, they will give you some idea as to what’s going on with any given page.
Find out where their fans are from
So, let’s say that the Facebook page you’re looking at is a local business – they work within your local region, they not a subsidiary of a larger international corporation – the people they work with are, logically, going to be based in the local area. The people who sell Facebook likes tend to be from third world nations – as noted in this piece from Copyblogger. Most of the fake likes you’ll come across originate from Bangladesh, India, Egypt, Pakistan, Afghanistan, Syria and Indonesia. Now, that’s not to point the finger and say all of the ‘click farms’ in the world are based in these regions, but if our local business has a heap of likers from these nations, that’s a likely indication that their faking it. So how do work this out?
Facebook’s graph search enables you to search for a heap of different parameters. The one we can use in this case is:
You insert the name of the business page at the end and it’ll give you a display of all the hometowns of people who like that page. The problem with this is that Graph Search results are sorted based on affinity – how they’re connected to you – not by total number, so you can’t necessarily determine where the majority of this page’s likes come from, but if it’s a local business and they have a range of the above mentioned nations among the hometowns of their followers, you may have reason to question why they’re showing up there.
Extra note: In this piece by Miguel Bravo, Bravo also suggests that the results of Graph Search queries like:
‘Pages likes by people who like [insert page name]’
‘Countries of people who like [insert page name]’
‘Languages of people who like [insert page name]’
Can also produce telling results (and they definitely do in the example he’s provided).
Check their interaction versus their Likes
This is a more tenuous linkage, but it can provide some insight. So, if the page you’re looking at has 3,000 likes, you’d expect them to have a reasonable level of interaction on their posts, some discussion about their brand, right? You can do a quick assessment of their posts to see what sort of engagement they’re getting on each – fake profiles are not going to interact with posts, so if they’ve got a crazy amount of page likes but are getting no action on their updates, they may have bought likes. Or they’re not very good at understanding their audience.
By clicking on the actual ‘Like’ number on the page, you get a graph like this:
Now, dependent on other factors, this could be telling – a huge jump in likes on any given day indicates either a really popular post or promotion, or that the page has bought likes, you’ll only be able to determine this by cross-checking the data against the posts. The other metric to consider is ‘People Talking About This’ – so, in this case, I’d be a little suspect, given they have 3.7k total page likes, a big boost in likes in the last week, yet only one person ‘talking about this’. Again, these are not definitive measures – they can often end up being fuel for your own conspiracy theories, where you’re really seeing what you want to see. But having a look at the numbers can be revealing on a page that’s clearly purchased fake likes.
Extra tip: Fake profiles tend to have no profile image, or odd-looking, copied images – this is another element to check to further your investigation.
Really find out where their fans are from
If you’re really serious about finding Facebook fakers, paid app Fanpage Karma will give you a breakdown of the location of any page’s likers.
This is one of the clearest indicators you can use to determine if the page has purchased likes – if the top countries are nations where the brand doesn’t even operate, that’s a fairly large red flag waving in your face.
On one hand, it’s frustrating that there’s not an easier way to determine Facebook fakers, as there is with Twitter, but on the other hand, it doesn’t really matter either way – if they’ve purchased fake likes, there’s not a heap you can do. I mean, you could, theoretically, go through their list of fans and report each fake profile one-by-one (which you can also do on Twitter) but obviously, that’s pretty time consuming and with Facebook already dealing with thousands of reports per hour, it’s hard to know if those efforts will actually cause any effect – that, and the fact that some like sellers offer a ‘guarantee’, where they’ll replace removed spam accounts, lessens the potential impact of conducting your own faker crackdown. The ongoing updates to Facebook’s news feed algorithm mean that purchasing likes will hurt pages more than help in the end, and Facebook’s always working to eliminate fakes where they can. While a higher number of likes is better looking, as with most measurements in social, it’s only one part of the larger picture, one indicator of potential success. You might have ten total likes and that could be more effective than a thousand, if those ten fans are engaged, paying clients, responsive to your messaging.
Quality Vs Quantity
And this is the key element in the popularity contest – the metrics only tell a part of the story. While I can understand why businesses might consider boosting their numbers, metrics are only one element of the social marketing puzzle. What’s more, fake likes and followers hurt the core product of social platforms – there’s already been questions about Twitter’s actual user numbers with reports suggesting that 9% of profiles are fake. That sort of speculation hurts their brand sentiment and turns off potential investors – the fake profile industry is bad for social media business, and you best believe the platforms are doing all they can to identify and eradicate imposter accounts. As with Instagram, at any time you could see a similar cull on any platform – buying popularity could end up very embarrassing if you get caught out.
Any measurement is an indicator – Likes, followers, Klout, Kred – each, in itself, is something to consider, but the only way to confirm the true social credentials of a person or brand is to investigate them yourself. Look at their posts, their content, assess what they’re doing. There may be a logical reason why their numbers are the way they are. Or there may not. ‘Influence’ is relative – conducting your own analysis will show you whose earned it and whose bought something resembling what influence should be.
Recently, I got to thinking about how social media and the transformational impact it’s having on our broader communications process might be affecting overall political awareness. This came up during the election lead-up in my home state – throughout much of the campaign the general consensus of people I spoke to was that they didn’t really have much of an opinion either way on who won. Of course, the people I spoke to are not indicative of everyone – a great many were very invested in the outcome – but in seeing the low levels of engagement around me, and the sense I got about the campaign overall, I wondered whether social might be lowering our levels of political engagement.
The arrival of social has given people a whole new way of consuming media. Online sources are now among the main players in news media, and through social media, people can now curate and customise their own info feeds. This enables people to choose which outlets they read, where they get their news from – and it also means people don’t need to see content they’re not interested in. For many, this may mean cutting out politics, which effectively weakens political influence and leads to a less politically engaged society overall – but is that what’s really happening?
The Numbers Don’t Lie
I sought to test my theory – if I was right, the easiest way to prove it would be to look at the rate of donkey and ‘informal’ votes in recent elections. If that rate was increasing significantly, year-on-year, that would suggest political engagement is falling, which would tie into my wider theory of the impact of social media. And in Australia it is – the rate of informal votes has jumped from 3.78% in 1998 to 5.55% in 2010, and it’s increased every year except 2007, which was the year that the Kevin Rudd won the Australian Federal Election – in which the ‘#Kevin07’ hashtag formed a key element of his campaign. This aligns with my theory – people are overall less interested in politics, but the incorporation of a social media element into Rudd’s 2007 strategy may have actually countered that and kept those less interested more engaged.
But there was a flaw. Yes, informal voting was increasing, but it’s been increasing every year since compulsory voting was introduced (rates jumped in 1984, but that’s attributed to a change in the voting process). Looking at the data, and considering social media’s influence, any real impact from social engagement would only possibly be significant in the last ten years, and the higher 2007 result is among the three elections held within that time, so it’s hard to draw any definitive conclusions from those figures alone. State-based elections provided no definitive logic either – informal rates had dropped in some, increased in others – there was nothing concrete in the numbers to conclude that the changing media habits, caused by social media, were impacting negatively on voter engagement. At least, not at this stage – in five years time, when the communications shift is really in full effect, we’re likely to have a better understanding of the potential impacts.
I found the same with US Presidential Elections – voter turnout in the United States has remained steady at around 55%, with an increase to 57.1% in 2008, the election in which social media was a key platform for eventual winner Barrack Obama (labelled by some as ‘The Facebook Election’). Other nations too showed no significant patterns – while the case may be that people are less politically engaged, the sample size, at this stage, is too small to draw and solid conclusions – though the increases in participation relative to social media activity did indicate the importance of engaging audiences on new mediums.
Of wider concern with the shift towards more customizable media inputs is the potential spread of reinforcement theory. Reinforcement theory is where people seek out and selectively remember only information that supports their pre-existing beliefs. You see and hear this all the time, people will pick and choose certain aspects of an argument in order to support what they choose to believe. And it’s damaging – people who’re locked into certain thought processes are not beneficial to the advancement of rational debate – you can’t argue with a mind that’s not open, you can’t reason with a person who won’t listen. If you’re stuck in your view of how things are, and you align with that perspective as indisputable fact, then there’s no way that you’ll ever be able to empathise or re-align your view if new facts emerge. It’s one thing to stand up for what you believe – that’s something that should always be encouraged and supported – but it’s another to stand up for what you believe while being closed-off to any other point of view. There’s an onus on everyone to learn the facts, to educate ourselves on all aspects of any particular issue before we set forth on solidifying what our opinion will be. But too often we see people accept a narrow perspective, form a belief based on a limited amount of information, and then perpetuate negative influence through their own confirmation bias, seeking out sources that support they’re stance.
While people have always been able to do this to some degree – you listen to the same radio presenter regularly or read the same newspaper and you’re effectively enlisting your own reinforcement theory on some level – there is a level of concern that the customisation of our media consumption might actually narrow people’s worldly awareness. While social media and the web are great for connecting with likeminded people and building communities around shared beliefs, the potential negative of that is that it may also embolden the disenchanted and facilitate more siloed cultures around limited and narrow viewpoints. If you choose, you can create a news feed of totally one-sided perspectives and shut out everything else. Whereas in the past people would need to watch the nightly news to get an understanding of the events of the day, many people now rely solely on their social feeds for the same info, which reduces the breadth of information being shared. Is that a good outcome? Is that what will lead us to a more understanding, connected society?
‘Is This Thing On?’
There have been various studies on the impact of social media on political consciousness, particularly among younger generations. In general, the findings seem to indicate that social media is good for political engagement because more people are talking about a wider range of issues online – trending topics, for example, inspire more people to evaluate their opinions on a particular subject. What studies can’t conclusively deduct is what impact those increased discussions are having on our wider political awareness – that can only be evaluated, effectively, by voter participation, which, as noted, is inconclusive given the data at this stage. What is clear, however, is that it’s becoming increasingly important for political parties to understand the growing reliance on social platforms as a means for building and fostering political engagement. It may be that the time for political jargon is dying out – it’s much easier in the connected era for people to tune-out anything that’s not engaging to them. Parliamentary Question Time, which is broadcast on TV in Australia, is a complex performance of political formalities and strategic doublespeak – you can easily see why people might opt to change the channel. The problem is, with the growing application of algorithms working to show users only the news relevant to them, based on their historical activity, the more people are switching away from politics, the less likely they’ll ever be switching back. Given that, it’s crucial for politicians to understand where their constituents are at, what they’re discussing, and importantly, how they’re discussing the issues of relevance to them. Just like businesses, politicians can access the abundance of audience data being logged every day online, the opportunity to build an understanding of the electorate is available and accessible to them. But it may mean a change of tact for the modern-day politician, a move away from the spin of old and towards a more connected process.
We were discussing the upcoming Super Bowl and newsjacking in a Twitter chat recently when Diana Wolff said this:
And she’s right, that tweet’s been discussed and lauded and referred to ad-nauseum in the two years since it was sent. And while there’s much to appreciate about the ‘Dunk in the Dark’ tweet, the real question is ‘was it effective?’ Did more people buy Oreos as a result of that tweet? Is that the true measure of success for real-time marketing? The question is, does getting sixteen thousand re-tweets correlate to positive ROI?
Did People Buy More Oreos as a Result of ‘Dunk in the Dark’?
This is hard to say, and really, only Oreo and their parent company Mondelez International are able to judge the return on their Super Bowl 2013 efforts. In terms of financial results, the actual attribution of that tweet is cloudy, as noted in by Danielle Sacks in her piece “Oreos Tags Pop Culture”:
Since Oreo embraced culture, the brand’s annual sales growth is up from the low double digits to more than 20%. But analysts attribute that to its expansion into emerging markets in Asia. It’s very hard to prove that new-media campaigns increase sales. During the Grammys this year, viewers who tweeted #SendMeOreo received a box of limited-edition cookies in new flavors that landed in stores a week later. “In terms of revenue, it was the biggest limited-edition launch that we ever had,” says [Janda] Lukin, Oreo’s North American chief. But no one at the company can tell me how—or if—”Daily Twist,” the Super Bowl tweet, and the Twist, Lick, Dunk app affected cookie sales. Asked specifically about the Super Bowl, Lukin admits, “There isn’t a great way for us to directly link it.”
Given there were so many campaigns and changes occurring around the same time, it’s difficult to directly attribute that tweet to an increase in revenue. But it definitely generated coverage, every media outlet from Forbes to CNet to The Huffington Post praised the genius of the Oreos tweet, which was universally considered to have won the Super Bowl ad blitz – some even questioned whether that one tweet did more for the Oreos brand than the $4 million Oreos ad that aired during the game.
Definitely the cumulative presence of these campaigns has had a significant and lasting impact, and has helped keep the brand within the awareness of many consumers, so in that sense, ‘Dunk in the Dark’ was obviously a huge win. Though the correlation is not as straight forward as many might suspect.
Did ‘Dunk in the Dark’ Improve Brand Perception?
Of course, sales alone may not be the true measure of the success of such coverage, it’s possible that Oreos saw increased brand perception, became better placed in the market or within certain demographic brackets as a result. This, too, is very difficult to measure, and no doubt the flood of coverage Oreos has received as a result of that tweet (including this piece you’re reading) has increased their brand awareness – but how beneficial has that one tweet been for overall brand sentiment?
Brand perception can be significantly influenced by a well-placed, real-time message. Arby’s, for example, would likely have seen a major boost in brand perception amongst a younger, hip audience when they sent this tweet in response to Pharrell Williams wearing a that now famous hat at the Grammys:
That single tweet brought them significant recognition, and helped them reach an audience they may not have been able to otherwise – their brand perception definitely got a ‘cool’ boost in the reflection of that tweet. There are regular examples of brands utilising real-time response to benefit positive brand perception – just recently, Australian telecommunications giant Optus posted this to their Facebook account in response to a iPhone error which had caused the alarms of many of their customers phones to go off an hour earlier than set, due to a time zone glitch:
Of course, giving people a free coffee doesn’t get them that hour of sleep back, but that extra effort to connect with their customers would have some impact on overall brand perception – no doubt better than just ignoring it and doing nothing at all.
So what about ‘Dunk in the Dark’? Would that message have improved the perception of Oreos, made customers more aligned the brand? Outside of maybe making a few more people feel like eating some chocolate biscuits, there probably wasn’t a significant increase in brand sentiment as a result of that message. It’s possible, like Arby’s, that they were able to reach a specific audience, through retweets and shares, that they’d otherwise not have hit, but again, how much would that perception reflect in the bottom line, at the end of the day?
Cause an Effect
The question of effectiveness really comes down to the specific people reached and the actions they subsequently took as a result of exposure to that brand message. The numbers themselves, in relation to the re-tweet, followers and favourites, are not, in themselves, a true measure of success. As noted recently by Gary Vaynerchuck, metrics like follower counts don’t necessarily correlate to success – reaching more people definitely increases your opportunities to convert, but getting through to just one person with the right message at the right time can be more successful than reaching 1000.
The discussion of ‘Dunk in the Dark’ and it’s relative success, based on impressions and interactions alone, is the perfect illustration of were traditional broadcast focus collides with new-school targeting and analytics. In the past, the way to win at marketing was to hit as many people as you could, get as many eyeballs as possible looking at your stuff in order to increase the chances of reaching the right few. This is why blast radius is still seen as such a significant measure to many marketers – but are impressions and reach really reflective of your success? As big data becomes more embedded and we learn more about analytics, and how to link specific data points to profitable results, it’s likely that bigger won’t necessarily be seen as better when we reflect on marketing effectiveness.
Of course, exposure is, and always will be of significant value, and research has shown that there is a link between social interactions and website visits. And far be it for me to make a call on the success of ‘Dunk in the Dark’ – the only people who can do that are Oreos themselves – although it as interesting that for such a huge, massive, win, they didn’t even try to replicate it, noting before the 2014 Super Bowl that they were ‘going dark’ this time round. No, the purpose of this post is to widen discussion of the metrics and what constitutes your own success, particularly as brands gear up to wade into the trending currents of Superbowl 2015.
Effectiveness is relative, it’s up to us to correlate the data and show what it means in the wider scheme.