Top 5 ways - Optimize Social Media Analysis

Top 5 ways - Optimize Social Media Analysis

1. Social media platform and its characteristics

2. Understanding Metrics on social media platforms

3. Data and bench marking

4. Paid content

5. Goals of your analysis

The available data of social network usage has made success measurement in this field increasingly popular, so many businesses and also political organizations have started assessing their performance with social media analytics.

Although we consider this a welcomed development to shed some light on what social media marketing can really do, we observe that these analyses often only scratch on the surface. They can lack substance or even deliver questionable results. This sometimes happens due to limitations by the used tools such as limited data availability, or simply because of time constraints. In some cases that may even lead to sufficient results.

When talking about social media analysis, usually refers to platforms such as Facebook, Youtube, Instagram, Twitter and Snapchat.

The focus is for the above channels, but Facebook , Instagram & Twitter are most popular. Data analysts are sometimes forced to bring together the data for the two networks. Nevertheless the different networks have to be regarded as independent platforms.

Their internal structures and logic's as well as their socio-demographic characteristics make this differentiation necessary. The micro blogging service offers the same kind of profiles for every purpose and also, most of the profiles are public. The flow of communication between all users on Twitter is thus much more unified than on Facebook. This has relevant implications for the usage and subsequent performance assessment of each channel. The socio-demographic composition of the users is relevant in the discussion of what role a network might play in society. Looking at the German market, Facebook is the largest network by far concerning the monthly active users, with Twitter lagging behind significantly. A representative survey shows that 51% of all Germans use Facebook once a week while the number for Twitter is only 11%. Facebook is thus far closer to represent the German society as a whole than Twitter, which acts more and more like a niche network for the media and politics. This however doesn’t mean that Twitter is not relevant. On the contrary, due to its socio-demographic composition it plays an important role in the agenda-setting for different channels, including legacy media.

2. Understanding Metrics on social media platforms

While analyzing social media data, some metrics can be misleading. One prime example is a metric that many people use for success or impact measurement – engagement. Many social media marketers’ dreams seem to be to engage people in a dialogue, trying to bring them closer to the brand or product.

In other words, bring them to interact with your content. But what these interactions really mean has to be thoroughly discussed especially when doing cross network analyses. Observing the total number of all interactions, often referred to as engagement, is a good starting point to see whether some analyzed accounts or figures stick out. However, we always have to take the different interaction types and their distribution into account.

The term engagement can also mean rather different things when it comes to specific platforms. Let’s again use the example of Facebook and Twitter.

On Facebook, engagement usually encompasses all interactions, meaning likes, comments and shares including the reaction emojis that are supposed to show different emotions and are actually an extension of the like button.

On Twitter, engagement means all retweets, mentions and likes.

You already see that this is different – also defined by the specific structure of each network. That being said, let’s focus on Facebook, The point that metrics have to be carefully evaluated, however, counts for all networks.

Example.com has 10 Likes are the type of interaction that is most easily used, it’s just one small click. Compared to a comment, where people have to put at least some thoughts into what they want to say, the hurdle to click on the like button is quite low.

Same holds true for reactions, although they include additional information for our analysis. Sharing content on the other hand needs some willingness to provide people within the own friendship group with content. So even if we only look at the Facebook universe, we have to carefully consider the different components that make up the metric of engagement, what they mean and how they are distributed. When it comes to the distribution, we want to point out to the problems when using aggregate data. The results can be driven by single events or constant news flow. Due to the logic of social media (virality) sometimes a single post or tweet can be the cause for the largest part of a profile’s engagement. This gets totally faded out when you use data for a full year and calculate a monthly average. The solution to this is to use different aggregates of your metrics and combine them with additional information.

When compiling a report you can, include the engagement for the post with the highest engagement and, if available, the stats for unique users. Or, try more sophisticated measures like a standard deviation that gives information about the spread or variation in your data.

3. Data and bench-marking

It often observed that social media analyses, especially in general interest media, pick some rather obvious KPIs and then speak about these numbers.

However, as in many other disciplines, it makes sense to use comparative approaches in social media analyses. Most analysts and researchers already compare their own brand’s or organization’s social media performance with other actors in their market or benchmark it with the own history.

This already adds a valuable perspective as you get to know if you’re lagging behind your competitors or if you are an over performer. Data from outside of social networks can give valuable further insights as well.

4. Paid content & its influence

If we take Facebook as an example, it is of course possible to measure the impact split by paid vs. organic for own activities. However, we don’t get this information if we want to analyze pages that we don’t have admin rights.

How much impact social media content creates organically and how much comes from paid formats is simply not possible to find out with publicly available data. It is however possible to create estimates, for example with processes that include machine learning with software’s available in the market.

So when talking about any social media impact bench-marking, we always have to consider that the split between paid and organic can only hardly be determined as of today. Accordingly, it needs to be discussed how we deal with that issue and if there are possible ways to overcome those limitations in the analysis.

Facebook has announced in Fall 2017 that there will be more transparency in the future especially for the highly debated political ads.

5. Goals of your analysis

Don’t let the data lead the way, always start with a clear question that you want to answer with the data.

Social media data can be used for different approaches. One example would be that you can look at the effect that social media content has on the audience when you want to assess the effectiveness of your content marketing strategy.

In that case, the analysis would focus more on data directly related to posts or tweets, thinking much more of individual content performance. You would more directly analyze engagement on a per post level to get a clear view instead of the overall page level.

A very different case is an analysis of customer care activities in which the metrics would focus on the exchange with users, such as looking at how many questions are being asked on your social customer care channel, when they come in and when they are being answered.

On the other hand, as social media are controlled communication by organizations, the data can be used to measure the positioning of an organization e.g. a company or a political party. So instead of looking at annual reports or party manifestos you can turn to the social media channels (i.e. Facebook) and measure the profile of a company or party. The combination of the two approaches finally gives you some hints as to how a profile is perceived by your audience. It lets you know if the main positioning fields are the ones your audience really cares about and, therefore, engages with.

This of course includes additional analysis tools like manual content analysis, word mining or more sophisticated automated content analysis like topic models. To put it simply: Which KPIs you report and which analysis and methods you use really depends on what you want to know from the data.

To Conclude:

One Size doesn’t fit all; a customized approach will provide ideal results

Every case needs a specific approach and considering that the digital realm is a fast moving one, changes in social networks will always require researchers and analysts to adjust to these changes on an ongoing basis. As social media is a communication tool for various contexts, its usage has implications for businesses, politics and society alike.