An analyzation for the Stukent simulation that examined my posts and performance for Mimic Social. 

Stukent Analysis

            Throughout my time at Newhouse, I’ve almost felt like a child playing adult. Sitting in class, I would analyze the various public relations sectors or examine how a PR team conducts its daily functions on behalf of an organization. While super interesting, there are distinct differences between studying the impact of social media and physically conducting a social media campaign. Creating and scheduling content through the Stukent simulation, allowed me to understand the complexities of a real PR campaign. Each week, we were given a weekly budget and tasked with listening to our target audience and posting content in an effort to earn the most revenue. While incredibly frustrating at times, I felt that this simulation was the most effective in helping me practice successful social media management techniques.

            When it came to paid content as opposed to organic content, I tried to follow the 80/20 rule. This meant that 80 percent of content was organic, and the other 20 percent was in the form paid promotions. With the sheer volume of activities occurring in today’s cluttered social media world, paid content gives the extra support a brand needs to ensure its message makes it into the news feed of its target audience and grabs their attention. While using Stukent, paid content was most helpful in earning new followers and advertising upcoming events like free shipping or big sales. After examining the Excel analysis of my social media activity throughout previous weeks, I limited paid content to Facebook and Instagram because it drew in the most revenue. For each paid post, I would select the appropriate photo and the proper target audience to accompany the image. Each paid post was targeted at a specific audience group and highlighted their interests with a clever caption. I examined the gender and age demographics pertaining to each platform to see where my targeted paid post would be the most successful. While paid content was essential in drawing in revenue and a new audience, organic content was essential in driving engagement and building a community. This is crucial for maintaining an audience as well as addressing concerns that can affect customer satisfaction. By the end of the campaign, I was paying for content to be promoted only on Facebook and Instagram because those platforms had very high profit margins. Other platforms offered couldn’t justify the high cost of paid content because the profit margins were so low. Organic content was posted across all social media platforms and I utilized the Excel spreadsheet to examine what types of content were the most successful. The documents Stukent provided such as audience demographics and platform specifics, were extremely insightful. Doing this allowed me to see that an image of a person outdoors holding the product was the most successful type of content. For organic content, I would select the image I wanted to post, use a targeted caption that pertained to the appropriate target audience, and distribute it to the platform I determined was the best fit. Twitter, LinkedIn and YouTube were used by a majority of males, so any photos of men outdoors with the product were posted to those social media channels. Facebook, Pinterest and Instagram however, were used by a majority of females. This meant that posts on these channels consisted of travel blogs to suit the City-Hopper Sue audience, and back-to-school photos in an effort to please the Back-to-School Mindy audience.

            For deciding the appropriate content, I relied on the interest of the company’s target market and past analysis. It was also important to examine the calendar time of the campaign. Since Halloween was coming up, I wanted to promote an annual Halloween sale through paid posts that were festive and seasonal. These did very well because they capitalized on a targeted market and motivated consumers to shop Buhi products through discounts and promotions to help save money.  I also relied on insight gained from my previous PR classes and personal experience with the platforms. In the beginning, I wanted to have a balance of content to keep viewers interested and engaged. This would be posting a blog one day on Facebook and then a photo the following day. In the weeks that followed, I stuck with content that tended to perform very well and got rid of any content that I didn’t perceive to be successful. The content that proved to be the most successful were pictures with the product in an outside setting. In the last week, I capitalized on this by selecting a variety of photos that showed the product outside and captioned it in a way that was very targeted to a specific market. Content that didn’t do well at all pertained to the company’s background and story which I found very interesting. Any infographic or blog post that went into detail about Buhi and how it makes its products did very poorly. I think this was one faulty aspect of the simulation because on the one hand, we are taught to have a developed image of the company to earn a positive reputation from shareholders. For this exercise however, it was about generating the most revenue and every post when through the website’s algorithm.

            When it came to platform choice, it was a mix of analytics, demographics and previous experience with the platform. LinkedIn was a very male-dominated platform, so utilizing the demographic information given by Stukent, I would post blogs, infographics and photos targeted at the target market known as Up-and-Comer Raj. Examining the research, I determined he was most likely to use this platform since he was starting his new job. I posted in the morning between seven and ten as that was when audience engagement was the highest. I stuck to organic content in the last stretch of the campaign as paid promotions weren’t very successful in terms of impressions, clicks and conversations. Upon researching, Twitter was also used by a majority of males so I would utilize memes and photos that pertained to the target market of Daypacker Tom. I chose memes as they were very successful in campaigns that we examined in class however, they weren’t very successful in terms of likes, clicks and shares. Towards the end of the campaign, I posted a majority of nonpromoted content like photos, as the revenue return wasn’t worth the investment and people outdoors with the product earned the most engagements. Upon examining all the information given to me from the data analysis, Instagram seemed to do the best overall. It was significantly higher than any other category in terms of impressions, engagements, and shares. Pinterest appeared to be the next highest in all three categories. Facebook then followed suit across all the categories. Instagram was definitely where I performed the strongest in the simulation. Since the platform is used by 57 percent females that are roughly 18-29 in age, I generated posts that appealed to target markets like Back-to-school Mindy, and City-Hopper Sue. While that’s not to say I neglected the other target markets, I focused on these heavily on these two when creating content on Instagram. In the final week of the campaign, I only promoted content on Facebook and Instagram, as they generated the most revenue and had the highest profit margins.

            Overall, Instagram and Facebook seemed to benefit my campaign the most because both continuously brought in a steady stream of revenue, as well as very high numbers in terms of awareness and engagements. While my promoted content brought in a successful amount of revenue, I was surprised to learn that much of my organic content that wasn’t promoted but very targeted towards markets like City-Hopper Sue or Seaside Sally, brought in a lot of revenue. The highest revenue however, didn’t always translate into the highest impressions. On Instagram, holiday advertisements seemed to bring in the most conversions and earned the highest impressions. Photos that promoted the interests of Seaside Sally, appeared to also generate the most clicks, likes and comments. On Facebook, promoted content in the form of advertisements, brought in the most revenue. This had a direct correlation with the highest amount of impressions, clicks, reactions and comments, and conversions. As mentioned before, Twitter wasn’t very high in profit margins so the content that performed the highest consistently for revenue, was holiday images and advertisements. For this platform, revenue didn’t directly correlate with impressions, however revenue did correlate with clicks. The image with the highest impressions, was a holiday image that didn’t earn a lot of revenue in comparison to other posts. The post that had the most clicks also brought in the most revenue for a platform and it was a nonpromoted image. I think it’s important to mention that in the first week, I had posted a photo that showed the Buhi backpack at a beach on a variety of platforms such as Instagram, Twitter and Pinterest and it was the single most successful post on all three social media channels in terms of revenue and clicks. I think this is very interesting upon examining the rest of my posts because that photo wasn’t promoted and targeted the smaller audience of Seaside Sally. Upon taking a look at Pinterest overall, most of the posts that generated a significant amount of revenue were paid and promoted advertisements. Some of the posts that generated the highest impressions, pins, and clicks, brought in the least amount of revenue. One criticism I do have for the simulation is that our class rank was strictly based on revenue. Even though some of my posts weren’t necessarily unsuccessful because they garnered a lot of clicks, I considered them to be ineffective because they didn’t bring in a lot of revenue.

            One main takeaway from the Stukent project is that analytics are everything. It is so crucial to examine the raw data and understand what it means in a real PR campaign. When you are using company money and have an allocated budget each week, you have to ensure that money is being spent wisely. If the data isn’t analyzed properly, a practitioner runs the risk of missing the mark on their target audience. It is so crucial to conduct the proper research so the target audience is not only identified, but also examined to see what content they want to see in order to maximize the potential profit revenue. I think I struggled in this campaign because I didn’t tag enough posts and spent more time trying to come up with a caption than properly analyzing the content. I was hesitant on re-using content and I believe I lost out on a lot of revenue because of it. Instead of capitalizing on posts that did really well in the past, I stuck to new experimental content that didn’t end up doing as well as I hoped. One strength was that I was able to create very targeted posts with clever hashtags and through my past experience and ease with the Instagram platform, bring in a significant amount of revenue than any other platform. My questions for this simulation are centered around the accuracy of this simulation. I feel that there was some disconnect in what I was taught and what the simulation wanted me to do. Do consumers appreciate being shown the same post twice in a three-week span? Are companies just concerned with revenue as opposed to clicks and impressions? Do clever captions really not matter? How important is it to have an established company image that depicts an overview of the company in addition to the product, as opposed to content that pertains to just the product? While I hope to work in the investor relations field in the future, I will still be utilizing social media metrics to examine profit margins on campaigns as well as communicating those numbers to investors, shareholders and employees.

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