Content categories on Instagram: from promotional to interactivity for business development

Purpose — The study aimed to analyze the content on Instagram and to examine the relationship between the content categories and the reach and impressions of the posts. Method — This study analyzed 58 content posts from the Instagram account @Generasi_kenzu using purposive sampling, divided into five categories and measured based on accounts reached and impressions, using descriptive statistics, a Kolmogorov-Smirnov test for normality, and a Kruskal-Wallis test for comparison of mean reach and impressions across the categories. Result — The content analysis revealed that promotion was the most prevalent category, followed by information and education, with a mean reach of 64.22 and a significant proportion of views from the user's profile, and found hashtags to be an effective method of increasing visibility, though with a considerable degree of variation among individual posts. The Kruskal-Wallis test showed no significant difference in the distribution of accounts reached, reach from follower, reach from non-follower, impressions, from profile, from hashtags, from home and from other across the five content categories. Contribution — This study contributes by adding knowledge about content categories' effectiveness on social media platforms, providing valuable insights into content and reach of Instagram posts, and suggesting the need for further research to explore impacting factors.


INTRODUCTION
Social media platforms enable the sharing of a large amount of information through text, photos, sound, video, and other forms of media (Young et al., 2020). These tools have become popular for socializing and business purposes (Stieglitz et al., 2014). In business, social media can serve seven functions: identifying customers, conducting two-way communication, sharing information about customer preferences, maintaining a customer presence, building customer relationships and location-based interactions, establishing a company reputation, and creating groups among customers (Stieglitz et al., 2014). However, small and medium-sized businesses (MSMEs) have not been able to fully utilize social media to their advantage, often only using it to follow trends and attract attention rather than for commercial gain (Cesaroni & Consoli, 2015). Instagram, in particular, can be used for digital marketing by sharing photos, videos, and stories (Bull et al., 2012;Stieglitz et al., 2014;Young et al., 2020). It can also be used to promote content and engage with customers, potentially increasing the value and engagement of visitors through creating high-quality content.
According to Chawla & Chodak (2021), the level of seller activeness on social media can significantly influence promotions. Interactions, such as the number of friends or followers and the growth in the number of followers, can impact many people's recognition of a product (Hajli, 2014). Marketing efforts on social media can also have a significant effect on potential buyers and lead to customer loyalty, which can affect sales (Fu et  . Using social media for promotions can be more profitable than print media, such as brochures, newspapers, or magazines, and the perceived price of a product can positively impact sales for small and medium-sized businesses (Chawla & Chodak, 2021). In 2020, there were 160 million active social media users on Instagram, and in 2021, there were 91.77 million social media users in Indonesia, with 36.4% being in the 18-24 age range (Alimudin et al., 2022). Instagram is particularly popular, being the thirdmost used social media platform after YouTube and WhatsApp.
There are still gaps in the research on social media, specifically Instagram, that need to be addressed. For example, there is a need to research how customers perceive a company's official Instagram account. Chang (2014) identified a suitable approach for engaging Instagram audiences, but there is still a lack of detail on the types of messages that should be posted. In order to effectively affect customers emotionally, it is important to consider the emotional content of the posts. Different researchers have classified social media posts into various categories. Caseiro 2013) categorized posts as those that use business names, those that reference emotional content, and those that reference immediate purchases of products or services. Coelho et al. (2016) identified six categories of posts that can be made on social media, including advertising, events, fans, information, promotions and services. In this article, the content is divided into five categories and will be analyzed in the following paragraphs based on previous research findings. This categorization approach differs from previous studies, which have employed various systems for classifying the content.
Educational content is designed to appeal to readers' rationality by providing information and knowledge. It differs from entertaining content intended to elicit emotional responses from readers (Luo & Hancock, 2020). Han & Xu (2020) study showed that social media can effectively influence people's perceptions and behaviours by sharing educational content that reinforces the importance of interpersonal communication. Three features that can be used to identify educational content on social media include its relevance to current issues, its emphasis on a specific subject area, and its use of activities or exercises for learning or application (Liu, 2010).
Informative appeals use factual data outlining the advantages of a brand to stimulate cognitive activity (Macinnis et al., 2002). According to the arguments presented in the message, informational appeals seek to alter a consumer's perception of a brand (Chandy et al., 2001). The degree of abstraction used in informative appeals might vary depending on how much information is distilled (Alba & Hutchinson, 1987;Keller, 1993). Textual information, such as the text in an advertisement or marketing message, can contain various informative appeals that aim to persuade a consumer. These appeals include information about the brand, product features, special deals or discounts, pricing information, comparisons to other products or prices, specific target market segments, product availability, and product location. Lee  Facebook. Informative appeals in marketing messages can positively and negatively affect consumer engagement. On the positive side, informative appeals can provide relevant information about a product or brand that helps consumers better understand its features and benefits. This can lead to a more favourable evaluation of the product or brand and may reduce the uncertainty associated with purchasing it (Yoo & MacInnis, 2005). However, too much irrelevant information may negatively affect engagement, as it may overwhelm or distract the consumer. Research suggests that informative appeals can effectively promote a more favourable evaluation of a product or brand by providing useful and relevant information and reducing uncertainty (Stafford & Day, 1995).
Social media interactivity refers to the ability of users to engage with and control the information they see and share on social media platforms. This interactivity is characterized by two features: user control and two-way communication (Sreejesh et al., 2020). User control allows consumers to selectively browse and access social media information by swiping, tapping, and sharing (Newman et al., 2011). Two-way communication allows for real-time conversation between users, including brands and their audiences (Sreejesh et al., 2020). This means that brands can share information and listen to the reactions and opinions of their followers on social media.
Inspirational content is a type of marketing material that includes a value proposition designed to inspire customers to take action (Izogo & Mpinganjira, 2020). According to promise theory, companies can use social media content to appeal to consumers' cognitive or emotional preferences and motivate them to engage in various behaviors. When firms make promises that align with this theory through their social media content, they can inspire customers to take action (Izogo & Mpinganjira, 2020). Raney et al. (2018) suggest that social media is a key source of inspiring content, particularly for younger audiences. Meier & Schäfer (2018) found that social media content eliciting benign envy can inspire and increase positive emotions.
According to Straker et al. (2015aStraker et al. ( , 2015b, sales promotions are a common and effective form of marketing communication that are prevalent on social media platforms. Sales promotion content refers to promotional information posted on social media or used to build brand image and drive sales (Okazaki & Taylor, 2013). This is due to the persuasive and action-stimulating nature of the content, which can positively impact the brand image and influence consumers' intentions and behavior towards a brand (Hilman et al., 2017). With social media growing as a marketing platform, it has become an important channel for disseminating sales promotion content ( Instagram, a widely utilized social media platform, provides metrics for understanding the reach of a user's feed posts, including total reach, reach from followers, and reach from non-followers. As the name implies, the total reach represents the number of unique accounts that have viewed a particular post (Instagram, 2023). Reach from followers, conversely, represents the number of views a post received from the accounts that follow the user (Instagram, 2023). Reach from non-followers represents the number of views a post received from accounts that do not follow the user (Instagram, 2023). In addition to these metrics, Instagram also offers insights on post impressions. Impressions are the total number of times a post has been viewed (Instagram, 2023). They can be further broken down into impressions from the user's profile, hashtags, home feed, and other sources such as the explore page. These insights, when analyzed in conjunction, can provide valuable information for understanding the performance of a user's posts and inform decisions about content strategy. Studies have demonstrated that posts with higher levels of engagement tend to have a higher reach (Sen et al., 2018). By understanding these insights, researchers and practitioners can optimize their content to increase reach and engagement as demonstrated in (Meier & Schäfer, 2018).
Therefore, based on the gaps in previous research, the study aimed to analyze the content on Instagram and to examine the relationship between the content categories and the reach and impressions of the posts. As far as the authors know, this study is unique in its approach and adds new insights to the field. The study is significant as it will contribute to the development of digital marketing theory but also provide valuable insight for businesses seeking to expand their reach through Instagram. The findings of this research can help business people to understand how to optimize their Instagram content and effectively reach consumers in the digital age.

Type of research
This study employs a descriptive research design with a quantitative approach. Descriptive research is a method that aims to systematically describe scientific information about the subject or object of study, with a focus on providing a thorough explanation of the facts obtained during the investigation (Stewart, 1992). According to Lopes et al. (2017), quantitative research is a method of scientific investigation that aims to explore one phenomenon and determine the potential relationships or connections between variables within the defined problem.
In this study, we analyzed the reach data of 58 Instagram posts from the account @Generasi_kenzu, from August to November 2022. @Generasi_kenzu is an Instagram account established by CV Mamifood Sukses Abadi to promote its products. Despite being a new account, the company has yet to fully optimize it to reach a wider audience. To expand consumer engagement, the company has employed the services of content creators to generate organic content that appeals to a diverse group of consumers. The account utilizes five distinct content categories: educational, interactive, informative, quotes, and product/service. Educational content encompasses tips, essential terms, case studies, and other information related to the company's business. Interactive content includes games, puzzles, quizzes, and other participatory activities. Informative content covers fun facts, frequently asked questions, holiday greetings, and the latest news. The account also features quotes, aphorisms, and stories that inspire. Finally, product or service content highlights sales, events, discounts, and promotions.
The posts were categorized into 5 distinct groups: education, informative, interactive, quote, and product/service. The data examined included the overall reach, reach from followers and non-followers, impressions, profiles, hashtags, home, and other metrics. Table 1 displays the description and operationalization of the variables.

Descriptive analysis
Descriptive analysis is a method of evaluating research data with the aim of generalizing findings from a single sample. According to Stewart (1992), descriptive methods provide information to decision makers about the statistical connections between criteria and options, however, they do not suggest any particular ranking of the options. The dependent variable, comprising all Instagram reach insights, such as total reach, followers, non-followers, impressions, profiles, hashtags, home, and others, was subject to descriptive analysis. Additionally, the content category, as an independent variable, was also analyzed using descriptive techniques. The data analysis included the calculation of N samples, minimum and maximum values, standard deviation, and skewness.

Normality test
As stated by Liang

Kruskal-Wallis test
The Kruskal-Wallis test, a rank-based method, was employed in this study to examine the presence of a statistically significant difference among two or more groups of independent variables on a dependent variable with continuous or ordinal properties (Kruskal & Wallis, 1952). This test is also commonly referred to as a non-parametric one-way ANOVA test (Kruskal & Wallis, 1952). The study utilized the Kruskal-Wallis test as a hypothesis test to determine whether there is a significant difference between the independent variable, specifically the content category, and the dependent variable, which is composed of total reach, followers, non-followers, impressions, profiles, hashtags, home, and other. The conclusion of a Kruskal-Wallis test in an article would typically involve interpreting the results of the test in relation to the research question and the null hypothesis. If the results of the statistical test show a p-value less than the predetermined level of significance (usually set at 0.05), it can be inferred that there is a meaningful difference in the medians of the groups being examined, and the null hypothesis is rejected. The specific groups that are found to be significantly different would also be identified. On the other hand, if the p-value is greater than the significance level, then the null hypothesis would not be rejected, and it would be concluded that there is not sufficient evidence to suggest a difference in the medians of the groups.
The proposed hypothesis in this research project is outlined as follows: H0 : There is no significant difference in accounts reached and impressions between the educational, interactivity, informative, quotation, and promotional content categories.
Ha : There is significant difference in accounts reached and impressions between the educational, interactivity, informative, quotation, and promotional content categories.

Descriptive analysis
The content categories applied to the @Generasi_kenzu Instagram account include educational, interactivity, informative, quotes, and promotional. A descriptive analysis of the content categories was conducted and the results are presented in Table 2.  The results of the content analysis of the @Generasi_kenzu Instagram account revealed that the most prevalent category was promotion, with a frequency of 17 posts or 29.3% of the total content. This was followed by information, with a frequency of 14 posts or 24.1% of the total. The education category was also prevalent, with a frequency of 13 posts or 22.4% of the total. Interactivity and quotes were also present, with frequencies of 11 posts or 19% and 3 posts or 5.2%, respectively. These findings suggest that the @Generasi_kenzu account primarily focuses on promoting their brand or products while also providing educational and informative content to their followers. The presence of interactivity and quotes also indicates a desire to engage with and inspire their audience.
The study aimed to investigate the reach of Instagram feed content posts of @Generasi_kenzu using descriptive statistics. The analysis revealed that the Accounts reached can be divided into two groups: those that originate from followers and those that originate from non-followers. The results of the descriptive statistics of accounts reached by content category are presented in Table 3.  Table 3, the analysis revealed that the accounts reached can be divided into two groups: those that originate from followers and those that originate from non-followers. The overall mean for accounts reached was calculated to be 64.22, with a standard deviation of 60.093. The minimum reach recorded was 28, while the maximum reach recorded was 435. Furthermore, the mean reach from followers was determined to be 13.57, with a standard deviation of 2.128. The minimum reach from followers was observed to be 9, while the maximum reach from followers was 19. On the other hand, the mean reach from nonfollowers was found to be 50.67, with a standard deviation of 59.587. The minimum reach from non-followers was 15, while the maximum reach from nonfollowers was 417. These findings provide insight into the reach of content on different categories and can aid in the development of strategies to increase the reach of content on social media platforms. The next aspect of the Instagram account @Generasi_kenzu analyzed was impressions. The impressions were divided into four categories: profile, hashtags, home, and other. Descriptive statistics for the impressions generated by each category are presented in Table 4. It is important to note that the data presented in Table 4 pertains solely to the number of impressions generated and does not consider the number of posts or engagement rate. This approach provides a comprehensive understanding of the performance of each category in terms of generating impressions on the Instagram platform. Based on the descriptive statistical analysis presented in Table 7, it can be seen that the impressions category represents the total number of views per post. The mean value for this category is 76.34, with a standard deviation of 62.679. The minimum value for this category is 33, and the maximum value is 455. This indicates that on average, each post receives 76.34 views, but there is a significant degree of variation among the individual posts.
The from profile category represents the number of views obtained from the user's profile. The mean value for this category is 28.31, with a standard deviation of 14.857. The minimum value for this category is 10, and the maximum value is 66. This suggests that, on average, a significant proportion of views for a post are obtained from the user's profile, but again, there is a considerable degree of variation among the individual posts.
The from hashtags category represents the number of views obtained from hashtags used in the post. The mean value for this category is 38.64, with a standard deviation of 60.512. The minimum value for this category is 10, and the maximum value is 415. This indicates that, on average, hashtags are an effective method of increasing visibility for a post, but there is a wide range of performance among the individual posts.
The from home category represents the number of views obtained from the homepage. The mean value for this category is 7.79, with a standard deviation of 3.166. The minimum value for this category is 3, and the maximum value is 23. This suggests that, on average, the homepage is a less significant source of views for a post, but again, there is a considerable degree of variation among the individual posts.
Overall, these data points provide a clear picture of the performance of Instagram content in terms of visibility and engagement. It is clear that the Impressions, from profile, from hashtags, and from home categories all play a role in the overall performance of a post, but the degree to which they contribute varies significantly among individual posts.

Normality test
The normality test is an important statistical tool used to assess the distribution of data, particularly in the context of parametric statistical analysis. The results of normality testing using the Shapiro-Wilk test are presented in Table 5. The table presents the Shapiro-Wilk statistic, degrees of freedom (df), and significance level (Sig.) for different content categories and metrics. The Shapiro-Wilk statistic is a measure of the similarity between the sample data and the normal distribution, with a value close to 1 indicating that the data is similar to the normal distribution and supports the null hypothesis of normality. The pvalue, on the other hand, is the probability of obtaining a test statistic as extreme or more extreme than the one calculated from the sample data, assuming that the null hypothesis is true. A small p-value (typically less than 0.05) indicates that the data is unlikely to be normally distributed, and the null hypothesis is rejected. By analyzing the values in Table 5, one can conclude which categories and metrics have a normal distribution and which do not. Based on the results of the Shapiro-Wilk normality test presented in Table 5, it can be seen that the normality assumption is not met for several content categories and metrics. Specifically, the "Interactivity" and "Informative" categories had low Shapiro-Wilk statistics and significant p-values for several metrics, such as "Accounts reached", "Reach from follower", "Reach from nonfollower", "Impressions", "From profile" and "From other". This suggests that the data for these categories and metrics may not be normally distributed and may require non-parametric statistical methods for analysis. In contrast, the "Educational" and "Promotional" categories generally had higher Shapiro-Wilk statistics and non-significant p-values, indicating that normality assumption is met for these categories and metrics. However, it should be noted that the category "Quotes" had the p-value >0.05 for all metrics, indicating that the normality assumption is met for this category. It is important to consider these results when selecting appropriate statistical methods for analysis in future studies.

Kruskal-Wallis test
The next step in the analysis was to examine whether there is a significant difference between the independent variables (content categories of @generasi_kenzu Instagram feeds such as educational, interactivity, informative, quotes, promotional) and the dependent variables (accounts reached and impressions). To accomplish this, a non-parametric Kruskal-Wallis test was performed. The Kruskal-Wallis test is used to determine whether there are significant differences among two or more independent groups with ordinal or continuous data.
The Kruskal-Wallis test results of content categories on accounts reached and impressions are presented in Table 6. The table shows the test statistics and corresponding p-values for the comparison of the independent variables with respect to both the dependent variables (accounts reached and impressions). These results will be used to determine if there is a significant difference in the means of the accounts reached and impressions between the different content categories of @generasi_kenzu Instagram feeds. profile, from hashtags, from home and from other across the five content categories.

CONCLUSION
The results of the content analysis revealed that the most prevalent category was promotion, followed by information and education. The analysis also showed that the mean reach of the posts was 64.22, with a significant proportion of views obtained from the user's profile. The study also found that hashtags were an effective method of increasing visibility for a post. However, there is a considerable degree of variation among the individual posts.
A non-parametric Kruskal-Wallis test was then performed to examine whether there is a significant difference between the independent variables (content categories) and the dependent variables (accounts reached and impressions).
The results of the test showed that there was no significant difference in the distribution of accounts reached, reach from follower, reach from non-follower, impressions, from profile, from hashtags, from home and from other across the five content categories. This suggests that the content categories do not have a significant impact on the reach and engagement of the posts. Overall, the findings of this study provide valuable insights into the content and reach of Instagram posts and can aid in the development of strategies to increase the reach and engagement of social media content.

Limitations and future research
It is crucial to acknowledge that this study is not without its limitations. One limitation is that the content analysis only focused on the @generasi_kenzu Instagram account and therefore, the findings may not be generalizable to other social media accounts. Additionally, the sample size of content that was analyzed was limited to a specific time period, which could affect the representativeness of the sample. Furthermore, the study only focused on the content categories of the posts and did not take into account other factors that could influence reach and impressions such as the time of posting or the use of hashtags. Additionally, the study only focused on the reach and impressions, other important metrics such as engagement and user behavior were not considered.
In terms of future research, it would be beneficial to expand the sample size and sample period to get a better understanding of the content categories of @generasi_kenzu Instagram account. Additionally, it would be interesting to conduct a similar analysis on other social media platforms to see if the findings are consistent across platforms. Another avenue for future research would be to explore the influence of other factors such as time of posting and hashtags on reach and impressions, as well as to study the engagement and user behavior of the followers. Furthermore, it would be beneficial to combine quantitative and qualitative research methods to gain a more comprehensive understanding of the underlying reasons behind the findings.

Theoretical and practical implications
This study adds to the existing body of knowledge about the effectiveness of various content categories on social media platforms, particularly on Instagram.
The study provides valuable insights into the content and reach of Instagram posts and highlights the importance of considering the reach and engagement of posts when developing strategies for social media content. The results of the non-parametric Kruskal-Wallis test support this finding and suggest that further research is needed to explore the factors that do impact the reach and engagement of social media posts.
The practical implications of this research are that it can be used to help businesses and organizations understand how to effectively use Instagram as a marketing tool. By understanding the content categories that generate the highest reach and impressions, businesses can tailor their content strategy to maximize their reach and engagement. The findings also suggest that interactivity content and informative content are more likely to generate higher reach and impressions among non-followers and followers respectively.
Additionally, the findings suggest that businesses and organizations should focus more on the interactivity and quotes content in order to increase reach and impressions, and engage and inspire the audience. Also, the results of the study can help organizations understand the importance of the use of hashtags in their posts. Furthermore, the study can help businesses to understand that the reach and impressions are different and also have different behaviors among the groups.
In general, the results of this research can be used to inform content strategy and help businesses and organizations more effectively use Instagram as a marketing tool. It can also provide insights for organizations on how to create a successful marketing campaign on Instagram, and how to increase the reach and impressions of their posts.