Firstly I'll start with data churned by an external application and provide my analysis regarding the information. I did not use social mentions, due to the fact that Between is a really generic word and the software had problems sorting through all that data on the net. So I couldn't find anything while using social mentions.
Figure 1.
Figure 2.
Figure 3.
Demographic Analysis
Figure 1 shows the Age Demographic of people talking about Between SG in the last 1 month. Within the age group of 15-17 and above 35, there is a significantly higher proportion of males than females. This is expected, however in the age range of 18-24 and 25-34 the proportion of males to females are about 60-40 with male being the former. Before looking at the insights, we initially thought that we should be more female oriented because of the nature of the application.
Cross referencing to Facebook Insights also showed similar Data with males audience numbers being considerably higher. This validates the idea of 'Guys week' that I suggested previously and recommendations wise, we could introduce more topics that cover the male spectrum of the relationship or generic topics that applies to both genders, over the course of posting, rather than just having a 'guys week'.
Total Page Likes
Figure 2, shows the fluctuations of like over a period of time. We can see that during the month of February, the graph has spiked up starting from the 30th of January. This was the period of time where we invited our friends to like the page in preparation for the post coming out on the next day. After it died down, the page maintained about 3 to 4 likes per day. From this graph we can say that, our page is getting some attention from people, however the numbers seems to be random as there is no definitive number of likes a day. After observing one Vulcan Post's insights, I noticed that in their boosted posts, they obtained a significant increase of views and engagement with their potential and current audience.
I assumed that we could increase the number of likes to the page by boosting the posts up. Although not organic, in this way we could potentially reach out to our audiences that wouldn't have got to know us, growing our like count exponentially. I wanted to try boosting the post, however we did not get around to doing that.
Total Reach Analysis
As seen in the picture above, our reach has dramatically increases over the period of posting. This is expected as Between Sg's Facebook page was not active before we started this project. Our total post reach has also steadily increased almost 2 fold to about 904 as at the date of this blog post. However, although the numerical value of post reach is important, what is more insightful is the figures displayed in figure 3.
Figure 3 shows us the engagement as a percentage of our total reach. It averages about 16% to about 8% through the posting period. On the platform that we're working on, engagement refers to post interaction such as comments, shares and likes. This proves that our posts are only getting through to a certain group and number of people, while the rest of the people just scroll through. What we have to do is to communicate in such a way that the audience pays attention to us. Maybe we should ask the audience what they want via private messages or face to face interaction, rather than assume.
In my opinion, people see companies as inanimate entities. They are just there to provide the goods and services in exchange for money. But perhaps with these interactions, it will make humanise the brand, and break down the stigma that surrounds us so that we'll seem more approachable and people would engage our content even more.
If we would have the chance to work on something like this again, I feel that this enriching experience would allow me to test marketing on social platforms in an entirely different perspective.
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