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Marketing

Conducting various autoethnographic reflections has allowed me to gain an in depth understanding of ethnography as a research practice, and why it's important to observe what people do and analyse why they do it. Organisations and companies will always need to communicate their offerings or messages to their respective target audiences, and they can now reap the benefits of ethnography to help drive their marketing strategies.

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One of the big reasons why ethnography is a viable method to drive strategy is due to the evolution of marketing. Shifts in society and advancement of technology has provided new and improved ways for marketers to work. However, this has created a more level playing field as it isn't just the richest companies who are able to implement effective marketing strategies, businesses need to tailor their marketing efforts even more now than ever (Agrawal 2016).

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Relating specifically to ethnography, marketing has also rapidly changed due to the increased use of big data, which isn't just the large amounts of data that new computing technology can harvest. Big data also refers to the unique, qualitative information businesses can use to help facilitate their strategies. These big data insights are something that couldn't simply be read off an excel spreadsheet, this includes information about what consumers do and why in relation to a company and their product/service offerings. This is where ethnography really shines in marketing as businesses can use the research method to obtain these unique consumer insights.

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Referring back to changes in society and the advancement of technology, certain branches of ethnography have become relatively simple for marketers to undertake. For example, the prevalent use of social media platforms and smartphones can generate useful information as consumers often post about their experiences with a company as a part of their regular online behaviour (Burrows 2014).

 

This leads to the important discussion relating to using consumer information for marketing purposes, privacy and consent. Marketers deploying ethnographic research practices need to take this into consideration to avoid detrimental PR crises'. This is timely as the recent example of companies such as Facebook and Cambridge Analytica shows that companies obtaining, using and distributing data can be criticised by customers, Chang (2018) explains this case in further detail here. It can be difficult to adhere to privacy and consent when gathering information online as opposed to in person, where subjects can be provided with informed consent for example, but companies undertaking research online still need to be aware.

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This shouldn't deter marketers from using ethnography to benefit their marketing efforts, as the benefits of understanding what consumers do and why make the extra effort worthwhile. A specific method of ethnography that is commonly used to support marketing strategy is digital ethnography, in which 'digital' is described by Moore (2018) as something dialogical, easy to change, always in motion, easily overwritten and connected to processes and electronics.

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Digital ethnography is a way of researching the experience of reality being transformed or mediated by the digital through “theory and empirical observation” (Moore 2018). For marketers conducting ethnography, customers who have their experience facilitated by digital technology can be observed. For example, social media platforms allows consumers to share their opinions constantly and in real time, this provides fast feedback loops for organisations (Mitew 2017). This research experience would be very different if the digital element was removed. Consumers are viewed in a natural environment online and their responses are not influenced by the thought of someone conducting research on their behaviour, this the key benefit of conducting digital ethnography.

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Ethnography and digital ethnography have been used in a variety of instances to help businesses gain insights that will benefit their ongoing marketing campaigns.

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Business Team
Analyzing the data
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