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Peer-Review Record

Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends

Reviewer 1: Anonymous
Reviewer 2: Anonymous
Soc. Sci. 2019, 8(4), 111; https://doi.org/10.3390/socsci8040111
Received: 22 February 2019 / Revised: 25 March 2019 / Accepted: 29 March 2019 / Published: 4 April 2019
(This article belongs to the Special Issue Fashion Merchandising and Consumer Behavior)

Round 1

Reviewer 1 Report

There is merit in the intent of the paper. Data generated by Google Trends and the additional metrics it is able to provide needs robust/accurate analytical tools, this idea is certainly research of value.

However, the article makes some broad generalisations about the data captured by the search engine and represented in Google Trends. These need to be addressed as there appears to be a general assumption by the author/s that the data Google captures through its searches is predominantly generated by online fashion consumers who are looking to shop. Further, peaks noted in the tracking of Google Trends are all attributed to a broad notion of ‘seasonality’ in fashion. These generalisations make discussion of the benefits of analysis here rather superficial. Some connection of fashion industry practices (such as international fashion weeks) as well as more nuanced view of consumer behaviour (for example, rise in comparison shopping online) would demonstrate a greater sensitivity to data being analysed.

The generalisations may be due to the fact the article uses 15 years (2004-2019) as a time period and because the study is focused on statistics. The author/s do not make it clear why this period has been chosen, this needs to be clarified. Insights could potentially be richer, if this research had been undertaken using a shorter timeframe with more granular analysis of the patterns identified.

The article lacks any discussion of how forecasting around the variables listed (predicting future fashion purchases, effectiveness of marketing campaigns and predictions of actual sales for a brand) is currently undertaken in the fashion industry. There is a well-established sector of the fashion industry dedicated to trend forecasting. Two global businesses in this field, WGSN and Edited, have developed business operations that provide analysis of big ‘fashion’ data for their clients. Arguments about the need for this paper would be strengthened by acknowledging that there are already fashion related platforms involved in tackling this problem and highlighting how this research on Google Trends would complement these existing platforms.


Author Response

Please see attached PDF file. Thank you.

Author Response File: Author Response.pdf

Reviewer 2 Report

Thank you for the opportunity to review your paper entitled ‘Googling Fashion: Forecasting Fashion Google Trends’, a topic area that is of interest to the research community. The paper is overall well written, yet there are some concerns that need to be addressed

 

Please see in the following suggestions and feedback that might help you to further strengthen your paper.

 

General comments

-       consistency in spelling Google Trends (e.g. line 44)

-       Line 51 ‘of’ missing

 

Introduction

This paper is interesting and the abstract provides a promising paper. However reading through the introduction, it remains unclear what the aim is of the paper and what research questions are addressed. Justifications are lacking for why Google Trends is of importance and why there is a need to look at it in details. Further concerns are related to the following questions:

 

-       How is big data defined and how is it linked to social media?

-       Why is there a need for research? Line 44

o   Better justification needed for why Google Trends is important

o   Is it already being used by companies? If not why is it not used?

-       Line 46 how is real estate linked to fashion?

-       Line 51 – why should stakeholders in fashion industry make more use of Google Trends? How is it different to what they look at currently?

-       Lines 55-61 summarise a lot of analysis techniques, yet do not state what they actually do, why they are important, and how they are used.

 

Googling Fashion

Whilst some interesting aspects are presented, some very bold statements are made that are not further discussed. It s still unclear How big data and Google Trends work together and what it is that would be offered by Google Trends that the fashion industry is not looking at through other forecasting tools. Overall this section is also rather descriptive and lacks critical insights.  

-       Does Google Trends only work for individual ‘styles’ and types of garments?

o   How is it measured?

o   Are external factors accounted for?

-       Line 85 – why is there no doubt?

-       Line 87 – why is this alarming?

-       Is this research focusing on a specific sectors of the fashion industry? Section 2.2.1 mentions fast fashion, section 2.2.2 mentions luxury

o   This is rather confusing 

 

Forecasting Models and Data

-       What do these models do? Why are they chosen?

-       What is the relevance of looking at the term Burberry?

o   Does this necessarily imply that people looked for fashion?

o   Could it also be negative press?

-       The graphs highlighted need to be better explained and it needs to be highlighted how they will help companies to predict trends for the future

 

Overall it is unclear what the theoretical underpinning is of the research and why it is of importance for fashion retailers. Limited discussion is provided and the conclusions are vague, thereby not highlighting enough theoretical and practical contributions. There is also an issue arising of ethics in terms of using data, as well as pointing out key limitations.


Author Response

Please see the attached PDF file. Thank you.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The amended manuscript is much improved, with the research and findings more clearly contextualised in fashion.


Author Response

Please see attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Thank you for the opportunity to re-review your work. It is apparent that you have dedicated a lot of time on the changes and incorporated the suggested feedback.

 

Whilst the article has improved and more clarity has been provided, there remain some minor comments that need addressing:

 

The title was changed to ‘Google Consumer Trends’ – should this be consistent throughout the text? Is there a difference between Google Trends and Google Consumer Trends?

P 1 – line 39 ‘fine example’ a bit too colloquial, think about changing to good example?

P3 – can you further outline how Google Trends has the potential to complement existing platforms (e.g. Edited, WGSN) – what does it do differently? Is there a different focus?

P4 line 1387-138 relating to Fashion Business Schools – this is a very bold statement and currently unsupported. Are there Fashion Business Schools? Is there really a lack of data scientists and quantitative researchers?

 

Consistency in spelling Google Consumer Trends.

 

Page 4 – line 147 – what does the quote mean? Is this in relation to the fashion context?

 

Page 7 – lines 255-256 How can Google Trends help with language changes?

Page 8 lines 269-271 quite a bold statement that is unsupported

 

You are explaining a key term on page 9 – ‘What is Google trends’, this should probably be done earlier, as the reader up until now is not fully aware what Google Trends data means

 

Page 10 line 322 – justification for Burberry needs to be earlier on

 

Page 10 – lines 336-340: How does not burning clothes make Burberry more sustainable?

 

Page 15 section 6.2 the first part of this section is not a discussion, but rather a review and should be added to an earlier part where WGSN and Edited are introduced.

 

The discussion section should link your findings with the literature.


Author Response

Please see attachment

Author Response File: Author Response.pdf

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