Author: Laurence Borel

French primaries: Sarkozy leading online conversations

This weekend, the French will vote in the primaries to nominate their Republican nominees for the 2017 Presidential elections. Anyone can vote in both the  Socialist and the Republican primaries.

This is a first in the history of France, and a strategy used to ensure not only more transparency in the election process, but also to tackle the rise of the dreaded National Front, who managed to get through after the first round of elections in 2002.

But what do online conversations tell us about the candidates’ online popularity? Conversations around Sarkozy, Juppe and Fillon were analysed between 1st October 2016 and 9th November 2016 (I sadly did not have time to measure the other candidates’ share of voice). Additionally, I included Le Pen in the equation, given her increased prominence on the international scene of late.

Data shows that Sarkozy (35%), and Juppe (21%) received the greatest share of voice during the period, with Fillon (7%) lagging behind. Although Le Pen received the highest share of voice overall (37%),  50% of mentions occured on 9th November, but were mostly negative/ironic as seen below, resulting from her planned appearance on the Andrew Marr show.

Juppe, Sarkozy, Fillon

 

 

Next, I compared the total number of mentions around Le Pen in France, the UK and the USA. Being part of the Anglo-Saxon community on Twitter, I felt that Le Pen had been receiving a great deal of American support. Scrunity of mentions however show that Le Pen more frequently talked about in the UK than in the US for now. It’ll be interesting to see how these mentions evolve as we head into 2017.

Le Pen, UK, USA

Based on digital data, Clinton looks set to win the next Presidential election…

Back in June, I predicted that the Leave camp would narrowly win the Brexit referendum through digital data. The analysis looked at 3 data sources including demand, web traffic and social mentions, and showed a small lead for Leave both in terms of traffic and social media volumes.This begs the question: can we truly predict election results through digital data? 

The US Presidential elections offer the perfect opportunity  to test this methodology again, scrutinizing  a highly digitally literate market. In the US, 78% of Internet users in the USA had a social media profile in 2016, a 5% growth versus the previous year, reinforcing the importance of social media as a communication tool. Additionally, Internet penetration in the USA is estimated at 88.5% suggesting that the majority of US voters may have engaged with the Internet to inform their voting decision.

How are Trump and Clinton performing digitally in 2016?

Similarly to my previous analysis of Brexit, I looked at 3 digital sources: demand, traffic data and social data.

Findings show that Clinton has received a higher traffic share than Trump overall, and despite having a smaller social footprint, interestingly received a considerably higher share of social traffic to her site. It would appear that voters are cognitively engaged with her content, leading to clicks. Then again, the amount of social traffic would also correlate with the quantity of links shared throughout the candidates’ respective campaigns.

Although Trump wins in terms of volume of mentions, sentiment around the controversial candidate remains largely negative. Saying that, Clinton also received high levels of negative mentions overall. In terms of consumer emotions Clinton inspired ‘disgust’, whilst Trump was found to predominantly inspire ‘fear’… The private email servers saga certainly didn’t help Clinton’s campaign as seen through Google demand search terms and voters’ emotions. Overall, however, Trump received higher volumes of mentions from voters pledging their support (e.g. Vote Trump), although this could be down to Twitter bots.

In sum, Clinton was found to beat Trump in terms traffic data, website engagement and but also social media sentiment, whilst Trump had higher levels of voters pledging their support.

Thus, based on these data, it may be inferred that Clinton is set to win the Presidential election.

Take a look at the presentation below to view my findings.

The 1 years and 11 months PhD update: Sex, Drugs and SPSS*

I am officially 1 years and 11 months into my part-time PhD! Time to reflect on the past 11 months of the achievements and set backs of my journey.

February – April 2016: Determination and the art of coding 2,000 pieces of UGC without losing your sanity

At the beginning of the year, I set out to complete a significant content analysis of brand UGC… I manually identified and coded 2,000 pieces of brand UGC, whilst working 3-4 days a week. The whole process took 3 months and I ended up completely exhausted (try working 9 hours a day, and code the brand UGC after work in the evenings and at the weekend).

May – July 2016: And there were tears…  and Andy Field’s SPSS Statistics, Sex, drugs and Rock n’ Roll became my saviour (kind of…)

All my data was finally coded, which led to a moment happiness and relief. All I had to do was to analyse my data in SPPS, produce a good draft of my research and I would be flying onto my second study. Or so I thought…

SPSS is not exactly my best my friend, and as much as I like the idea of quantifying data, my dyscalculic demons were unleashed. The challenge was not so much learning how to use SPSS; the challenge was to understand how to perform a chi-square. The struggle was real, and the months were flying by, so I took the decision to enlist the help of a private stats tutor. All was well, until said tutor started shouting at me for not having clear hypotheses to analyse my data. I kid you not! Clearly upset by the ordeal, I burst in tears… but he was right. I had to up my game, and develop clear hypotheses.

On a more positive note, one of my mini successes was passing the dreaded annual examination back in June. Whilst the annual examination can be worrisome for some, I was confident that my proposal was strong, largely down to the fact that I was exempted from all exams in my first year, and thus had more time to focus on writing a strong literature review and methodology.

September 2016 – October 2016: Finally published, and a minor set-back

September was a month of wins. First, the book chapter I had co-authored with my supervisor towards the end of my MRes was finally published. It’s quite an amazing feeling to see your name printed in a book. Even more excitingly, the research paper we wrote of the back of my MRes thesis was finally accepted (Hurray!). The paper will be downloadable from any good database in the near future 😉

As for the minor setback, despite my best attempts at writing a succinct and academically engaging paper, my content analysis draft looked like much more of a dysfunctional series of analyses, than the highly cited academic masterpiece I had hoped it would be, dashing my hopes of an academic holiday conference in Tokyo

Note to self: You should reject the null hypothesis when p<.05. Damn you brain!

September 2016 onwards: Here we go again!

Given the struggles in developing a succinct, non-dysfunctional paper based on my first study, my supervisor advised me to start working on my second study, with a view of developing an academic masterpiece (or something along those lines) supported by primary research at a later stage. The idea here is to use primary data (qualitative interview), to inform the direction of my initial content analysis.

As I type, I am currently in the recruitment phase of my research and would be keen to talk to people who share user-generated content such as selfies online. Intrigued? Fancy helping a poor PhD candidate? Find out more about my research here.

Until next time, keep writing!

*The title of this post is inspired by a book witten by Andy Field… just in case you were wondering!

Thumbnail photo via

The Routledge Companion to Contemporary Brand Management

The Routledge Companion to Contemporary Brand Management I am pleased to announce that the book chapter I co-wrote with my supervisor at the end of my Masters has finally been published. The Routledge Companion to Contemporary Brand Management offers a comprehensive collection of texts from leading scholars around the world on various issues facing brands and their managers in our digital age. The book is divided in  5 sections and 37 chapters covering the following topics and issues:

Section A: What is a brand and how do we measure its market performance?

1. Brand Definitions and Conceptualisations: The debate (Francesca Dall’Olmo Riley)

2. Measuring the Market Performance of Brands: Applications in brand management (Jaywant Singh and Mark Uncles)

3. Consumer Based Brand Equity (Sally Baalbaki and Francisco Guzman)

4. Brand Valuation: Principles, applications and latest developments (Gabriela Salinas)

5. Brands and the Self (Russell Belk)

6. Brand and the Society (Paurav Shukla)

7. Dead Brand Walking: On the paradoxes and perversities of branding (Stephen Brown)

Section B: Strategic Brand Management

8. Brand Architecture Design and Brand Naming Decisions (Choong Whan Park, Deborah J. MacInnis & Andreas Eisingerich)

9. Strategic Brand Alliances (Jaywant Singh, La Toya Quamina and Stavros Kalafatis)

10. Brand Extensions (Ceren Hayran and Zeynep Gürhan Canli)

11. A Brand Culture Perspective on Global Brands (Jonathan Schroeder, Janet Borgerson and Zhiyan Wu)

12. Positioning a Brand (Charles Blankson)

13. New Brands: Performance and measurement (Jaywant Singh and Malcolm Wright)

Section C: Managing Brand Communication

14. Brand Building via Integrated Marketing Communications (William Darley)

15. Sensory Aspects of Branding (Dipayan Biswas)

16. Building Brand via Corporate Social Responsibility (Adam Lindgreen, François Maon and Christine Vallaster)

17. Digital Branding and Analytics (Laurence-Helene Borel and George Christodoulides)

Section D: Branding to Different Audiences

18. Looking at the Future of B2B Branding (Johnny Graham and Susan Mudambi)

19. Towards a Better Understanding of the Ethical Brand and its Management (Katja Brunk)

20. Not-for-Profit Branding (Helen Stride)

21. Strategic Employer Brands: Current domain, future directions (Lara Moroko and Mark Uncles)

22. Internal Branding: Dissecting, re-analysing and re-directing the literature (Bill Merrilees)

23. Brand Culture, Halal and the Critical Islamic Imperative (Jonathan Wilson)

24. Branding the Entire Entity: Corporate branding (Stuart Roper)

25. Branding in the Emerging Markets (Suraksha Gupta, Shivani Garg and Kavita Sharma)

26. Branding in the Base of the Pyramid: Bases for country and organizations in Ghana (Stanley Coffie and Joseph Darmoe)

27. Guinness in Africa: Contemporary branding at the base of the pyramid (Samuel Bonsu Delphine Godefroit-Winkel)

Section E: Branding Different Entities/Products

28. Branding Higher Education (Bang Nguyen, Jane Hemsley-Brown and T.C. Melewar)

29. Political Branding: The case of the Scottish referendum 2014 (Camille Lannoy, Paul Baines and Roger Mortimore)

30. Arts Branding (Daragh O’Reilly and Finola Kerrigan)

31. From Nation to Neighbourhood: Branding and marketing places (Nicolas Papadopoulos, Leila Hamzaoui-Essoussi, José I. Rojas-Méndez)

32. The Challenges of Luxury Branding (JN Kapferer)

33. Retail Branding (Steve Burt and Leigh Sparks)

34. Service Branding: Enabling, making and delivering promises (Roderick J. Brodie)

35. Branding Financial Services (James Devlin)

36. Branding in Sports (Gerd Nufer, André Bühler & Simon Chadwick)

37. Franchise Brand Management from a Knowledge Perspective (Audhesh K. Paswan, Sua Jeon, Pramod Iyer, Retno Tanding Suryandari)

Find out more about the book here

In or out? A digital analysis of #brexit

Before we deep dive into the data, I’d like to clarify this post is solely intended as a quick analysis of the volume of conversations sentiment and traffic surrounding a vote that could significantly change the world we live in forever. This analysis looks at social media and traffic data from both the Remain and Leave campaigns.

Social Media data were collected during 1st October 2015 and 31st May 2016, when both the #voteleave and #strongerin hashtags started emerging.

Stronger In:

  • 208,943 mentions were recorded during period and peaked in May 2016
  • As we can see from the word cloud below, the key arguments posited by the camp appear to be around trade agreements, businesses, universities.
  • We can also see that those from the Brexit camp often intervene within these conversations, as demonstrated by the prominent #voteleave hashtag within the word cloud.

Stronger in volume and sentiment

Stronger in Word Cloud

In terms of digital channels. Stronger In are being smart with their PPC stategy. This is what happens when you Google ‘Leave EU’…

Stronger IN

#Voteleave:

  • Conversely, the #voteleave hashtag received 268K mentions during the same period, and appears to be following a very similar curve in terms of mentions as the #strongerin campaign
  • Key topics of conversations tend to be around taking control and stopping the EU/euro-scepticism, priorities and Brussels, but no other clearly identifiable themes of conversations emerge.
  • The mentions around the #voteleave movement peaked in May, with The Ordinary Man Twitter user, driving a large volume of RTs throughout the month

#voteleave sentiment and volume over time

#voteleave word cloud

Traffic analysis (April – June 2016)

Of course, the fact that there are multiple segmented movements for the Leave campaign does not help with their campaign traffic-wise… Stronger In however beats leave.eu with the support of a PPC campaign, which appears to have kicked off in April… Because the traffic significantly dropped in May, I would suspect that they have reduced their PPC investment significantly, with the aim of potentially increasing spend again in the final few weeks of the campaign.

Stronger in vs. leave

Scrunity of the Stronger In vs. Leave Take Control however depicts a different story… Vote Leave had a clear lead traffic-wise until April 2016, when the Remain camp kicked off their PPC campaign… As of May 2016 with significantly reduced levels of paid search investment, both camps are head to head. Remain vs. vote leave take control

Final stats as of 1st June 2016:

  • Remain traffic: 363,112 vs. Leave 372,912
  • Remain social mentions: 208,943 mentions vs. Leave: 268K
  • Remain social media count: 444,703 likes, 32,285 followers. vs. Leave social media count: 439,356 likes, 48,785 followers.

If we are to go by these numbers, the Leave camp marginally wins…