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Analyzing Social Media Interaction in Supermarkets
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Background Study

The current technological advancements have elevated the collaborative communication between businesses and their consumers in a way such that, business engage in various technological platforms such as the social media to effect more penetrative and convictive communication to their consumers (Hanna, Rohm & Crittenden, 2011). More specifically, the social media allows corporations, organizations, and even individuals to create, exchange or share information, career interests, pictures, ideas, links, and videos in virtual communities. Consider the statistical report by Kietzmann et al. (2016) that provide that Facebook emerged the leading and most popular social network. The latter has up to 1 billion registered member accounts and up to 1.59 billion active users in every month. This has given Facebook a high probability of boasting small and starter or large and well established business organizations once integrated in the day-to-day business operations (Harlow, 2012). Such a report illustrates just a general case of the potential impacts that, Facebook, the leading social media platform lays to the entire business industry. However, what exact impact could the latter be pounding on an individual stream of business? How exactly, do social media interaction affect and individual industry of operations?

To respond more swiftly, the paper selected supermarkets as the most suitable industry of consideration. This imminent consideration was based on a number of factors that singularly characterize the supermarket industry. These factors include:

  • Supermarkets have the largest consumer base within any basic social setting.
  • A “word of mouth” spread by the consumers has an immediate and widespread effect to the overall performance of the industry.
  • Supermarkets deal in sale of widely disturbed set of consumer brands. A survey acquired for supermarkets imply direct impacts all the other brands.

Pearce et al. (2008) argue that with Facebook in play, supermarkets are empowered to talk more explicitly to the general masses, including their clients and other potential customers. Facebook also helps the industry to spread news for upcoming events, new launches, offers, and many more in just a few minutes. The greatest factor that boast Facebook’s impact on the supermarket is, once a consumer or the firm share something on Facebook timeline, it equates to a face-to-face recommendation to multiple consumers (Hennig-Thurau et al., 2010).

Hypothesis

This paper analyses how some thirty three supermarkets engage with their users and measures how effective this engagement across the various channels. We analyze the engagement through shared links, general status post, video, photo, events, and offers. The aim of this analysis is to suggest how supermarket brands could better target their users effectively. The analysis covers data collected between January 1 2016 and July 7 2016. The data comprises of engagement data for status posts of different kinds from thirty three supermarkets.

Analysis

The most effective Channel

To understand the overall effectiveness of different channels concerning engagements, we carried out an Analysis of variance of the mean shares and likes for the different engagement channels. The results of the analysis are tabulated below.

The results indicate that there is a statistically significant difference in the mean likes for different channels. This means that some channels will have more engagement than others. The order of the influence is given below.

Videos, generally have more likes than the rest of the channels (mean = 1026, SD = 3886). This is followed by posts with photos (mean = 235, SD = 809). The channel with the least engagement is plain status.

There are fewer events and offers in the dataset to measure their overall influence.

The chart below shows pairwise comparison of the different channels.

The pairwise comparison of the data shows that video and offers provide a larger influence on the likes than any other combination of channels. Videos and photos have the least effect because they are rarely used together. This shows that people respond more to a combination of offers and events, offer and a link, and video and offer, photo and offer, and link and offer. Offer seems to have a large influence on engagements. Top themes across different charnels

We also wanted to find out what different themes were used in the different channels and overall for the supermarkets.

The table below shows the term frequency of the top 15 words

TERMFREQUENCY
DAY253
GET200
NEW190
RECIPE149
WEEK131
MAKE129
STORE120
TODAY119
GREAT115
NOW105
JUST100
LIKE94
ONE89
FREE88

Visually, these can be seen from the word cloud below.

As can be seen from the wordcloud, some of the themes and top words include recipe, yoga, delicious, favorite, fresh, and week amongst other words. This does show that most of the words brands are using are meant to make the user feel special with words such as enjoy, happy, love, win being some of the words used. There are also some words used to describe products such as fresh, delicious, green, good, and favorite, adjectives that show most brands project their products positively. Additionally, with some words such as family also appearing amongst the top words, this could be an indication that most brands are projecting their products as family friendly.

Conclusions

The analysis shows that the most effective channel that leads to higher user engagements is video, followed by photos. Pairwise, if a video is coupled with an offer, then the engagement is also quite high.

This shows that brands could use these two channels to reach out to most of their customers as they respond more to these.

Also, based on the analysis of the terms, brands could use positive adjectives to position their brands and also make their brands appeal to families.

Bibliography

Black, D., Clemmensen, N.J. and Skov, M.B., 2010. Pervasive Computing in the Supermarket: Designing a Context-Aware Shopping Trolley. International Journal of Mobile Human Computer Interaction (IJMHCI), 2(3), pp.31-43.

Cormode, G. and Krishnamurthy, B., 2008. Key differences between Web 1.0 and Web 2.0. First Monday, 13(6).

Golbeck, J., 2007. The dynamics of web-based social networks: Membership, relationships, and change. First Monday, 12(11).

Hanna, R., Rohm, A. and Crittenden, V.L., 2011. We’re all connected: The power of the social media ecosystem. Business horizons, 54(3), pp.265-273.

Harlow, S., 2012. Social media and social movements: Facebook and an online Guatemalan justice movement that moved offline. New Media & Society, 14(2), pp.225-243.

Hennig-Thurau, T., Malthouse, E.C., Friege, C., Gensler, S., Lobschat, L., Rangaswamy, A. and Skiera, B., 2010. The impact of new media on customer relationships. Journal of service research, 13(3), pp.311-330.

Kietzmann, J.H., Hermkens, K., McCarthy, I.P. and Silvestre, B.S., 2016. Social media? Get serious! Understanding the functional building blocks of social media. Business horizons, 54(3), pp.241-251.

Libai, B., Bolton, R., Bügel, M.S., De Ruyter, K., Götz, O., Risselada, H. and Stephen, A.T., 2010. Customer-to-customer interactions: broadening the scope of word of mouth research. Journal of Service Research, 13(3), pp.267-282.

Pearce, J., Hiscock, R., Blakely, T. and Witten, K., 2008. The contextual effects of neighbourhood access to supermarkets and convenience stores on individual fruit and vegetable consumption. Journal of Epidemiology and Community Health, 62(3), pp.198-201.

Waters, R.D., Burnett, E., Lamm, A. and Lucas, J., 2009. Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public relations review, 35(2), pp.102-106.

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