Poor Apple. Again.

This time last year, Apple launched a new operating system that had numerous technical problems, as well as a mapping app that was so inaccurate that it became the target of many jokes.

Fast forward to this year and, once again, Apple’s recent product launches (including 2 models of iPhone 6, the Apple Watch and Apple Pay) have been followed by criticism and jokes. Many jokes. Not even the gifting of U2’s album to iTunes users escaped:

PoorApple1

And, as if to add insult to injury, @BBCTech quickly posted instructions on how to delete the free U2 album, here:

PoorApple2

Ah, Apple, Apple. What happened to you?* #PoorApple.

Can anything be done about this negative opinion?

Research conducted by Muthukrishnan and Chattopadhyay** (here, but paid access only) shows that comparing the brand with other options (for instance, saying product A is faster than product B) is not a very effective way of reversing consumers’ negative opinions, even if the comparison is favourable and it’s made by a trusted third party. This is because making explicit comparisons about some attributes makes buyers question performance across the other attributes not included in the comparison (for instance: yes, A may be faster than B, but B has more accessories / lasts longer / etc than A). Instead, to revert negative impressions, marketers should avoid comparisons with their competitors.

The problem with Apple, at the moment, is that they can not avoid comparisons: the iPhone has been compared with Samsung phones, the Apple Watch with Sony’s SmartWatch3, and so on.

To break this cycle, Apple really needs to change direction – just like when it changed the focus from laptops to mobile devices (first the iPod, then the iPhone). Like McDonalds is doing with food sourcing, or Google with self-driving cars. Better still would be for Apple to connect at an emotional level, as Coca-cola has done with the Share a Coke campaign.

What do you think? Can Apple turn the negative opinion tide, and go from #PoorApple to #AppleWin?

* For me the tipping point was how Apple reacted to the iPhone 4’s signal problem (i.e., blaming the users for holding the phone on their left hands). Oh, and iWeb, whose users were completely abandoned by Apple (Can you feel the bitterness?). And the appalling working conditions in the components’ factories in China. The sky-high prices. The copyright fight with Samsung…

** Muthukrishnan, A.V. and Chattopadhyay, A. (2007). Just Give Me Another Chance: The Strategies for Brand Recovery from a Bad First Impression. Journal of Marketing Research: May 2007, Vol. 44, No. 2, pp. 334-345

Book review: Social Media Explained

Social Media Explained – Untangling the World’s Most Misunderstood Business Trend” is the latest book authored by American business consultant, speaker and educator, Mark W. Schaefer, who also runs the extremely helpful blog {grow}.

Having read other books and work authored by Mark, I was expecting this book to do just what “it says on the tin”. And, indeed, the book, which is aimed at business executives, considers how social media helps organisations understand the market, connect with customers and stand apart from competition. Moreover, the book does so in a very clear and engaging style, which is why I am adding it to my course syllabus.

But that is not all.

This book is also very relevant for those of us using social media as individuals, rather than representing an institution, and who are unsure how to derive value from Facebook, Twitter, YouTube, blogging and so on. And this is why.

 

SM Explained book

Social Media Explained – for businesses executives
The book is organised in 3 sections. In the first section, the author outlines the key changes in the business context and why these require organisations to engage with social media. For instance, as more of us turn to the social web for product discovery and education, and as we increasingly resist blunt sales approaches, so organisations need to populate the web with helpful content that answers potential customers’ questions and drives them to the company’s website. In addition to identifying the challenges, Schaefer discusses how organisations can address them – for the example discussed (i.e., product discovery), the book discusses how organisations can identify and answer customers’ questions, and disseminate the content in ways that will get it noticed by customers at key stages of their journey.

In section two, Schaefer addresses common questions raised by those grappling with social media. The questions considered range from “Do I need Social Media?” to “How do I handle negative comments?”, and the if-I-got-a-coin-everytime-somebody-asks-me-this-question-I-would-be-a-millionaire issue of “What’s the ROI of Social Media?”. The questions are discussed very pragmatically and, I think, the answers provided will help you face the most sceptic of CEOs or CFOs.

In the third and final section, the author provides a brief overview of the main social media platforms, with emphasis on ‘brief’. This section tells us what platforms are out there, their relative advantages and disadvantages, and the uses for business. This is not a detailed ‘how to guide’, however and any one expecting that will be disappointed (though, Schaefer has also authored guides on Twitter and Blogging which you may find very helpful).

The book is written in a really accessible style, with minimum jargon. It has plenty of examples and case studies from various countries and a variety of business scenarios. And it is very reasonably priced. Overall, this is a great resource.

 

Social Media Explained – for the rest of us
All this advice is very nice and good, but what do you do with it if, like me, you are active on social media as an individual, as opposed to representing an institution? Is this book still relevant for you?

Well, we may not have a clearly defined competitor. But, with the average millennial spending 5.4 hours a day with content created by their peers, we certainly need to do a good job with our posts, pictures and videos to get attention from our followers and connections.

Likewise, we may not have a profit and loss statement to complete but, when we are ‘doing’ social media alongside our jobs and/or family commitments we surely need to make very difficult decisions about how we use our time, technical resources and, indeed, money.

And while we may not have a CEO or group of shareholders to report to, many of us will have faced scepticism and impatience from relatives, colleagues or employers – Tell me again why you are (wasting that time) doing that social media thing?!

We may not have a product to trade, but we are putting our ideas and experiences out there for others to scrutinise.

We may not have a market with well-defined segments, but we are under no illusion that there are different groups of people connected with us online – e.g. relatives, former class mates, current colleagues, people that we never met but that share an hobby or other interest with us, and so on. We connect with each group on different platforms, at varying frequencies. And each group will value different content.

And, instead of money, the value that we get from pouring our hearts and souls into this, could take the form of attention from a targeted audience (e.g., a potential employer or literary agent), or social contact with and advice from other individuals in similar circumstances (e.g., living with a chronic disease, moving to a foreign country or raising a large family). It could also take the form of feedback or input that helps us to develop an idea (e.g., for a book), or simply be a repository for content (e.g., a collection of personal memories or of examples for teaching).

Once we make these adjustments to the basic business terminology, the lessons from this book are just as relevant for individuals struggling to use social media effectively, as they are for business executives considering a social media strategy for their organisations.

Instead of… Think…
Industry competitors Competition for attention
Profit and loss statement Your limited time, technical resources and money
CEO or group of shareholders Sceptic and impatient relatives, colleagues or employers
Product Ideas and experiences
Market segments Different groups of people with whom you connect online
Sales and profit Attention, social contact, feedback, input, or content repository

This book is a great addition to my library. I read it twice already, I have been recommending it far and wide to business connections and students, and I foresee that I will be referring to this little book over and over, again, in my work and as a user of social media.

 

Have you read this book? What do you think?

August round-up

August = school and family holidays. Therefore, it is no surprise that this was a somehow unproductive month.

Joana summer

 

For me, August included the following highlights.

Researching

As I am working on a paper on using social media for customer insight, I spent some time catching up with literature on this topic. I have also been reading about the technical aspects of analysing social media data, including analysing visual data, and working on a bid for a small research grant.

 

Writing

I submitted a “chapter” to the Book of Blogs, a book about using social media for social sciences’ research, edited by the NSMNSS. The book covers topics as diverse as the technical aspects of using various social media platforms, application to specific social sciences’ fields, or ethical concerns; and is original in that its content consists of crowd sourced blog posts. The book will hit the ‘virtual’ shelves this Autumn.

 

Oh, and I got the physical copies of the Research Methods book. It’s all very exciting…

Book is here

Teaching

Not much teaching this month, only a session on Digital Marketing. But lots of marking, and supervision of dissertations.

 

Learning

As I was planning to submit a paper to a special issue of a journal that I am not very familiar with, I spent some time learning about the writing style and key themes in that journal. Eventually, I did not manage to finish the paper on time (a deadline of August 31st… Seriously!?), but I did learn a lot about this journal and the community that writes for it. It’s a great resource and I have now added this title to the list of journals I check regularly.

 

SM Explained bookStill on learning, I finished reading the excellent book ‘Social Media Explained’ by Mark Schaefer. I learned a lot and shall be reviewing the book here on the blog, very shortly.

 

What were August’s highlights for you?

Of burdens and black dogs

oCaptainMany years ago, I had a student that was really, really difficult.

He was unpleasant. Disruptive. Challenging. And he openly said that he did not like me. I am not going to lie: I was very happy when the semester was over!

 

One year later, he showed up at my class door. He wanted to tell me that, in the previous year, he had experienced a very traumatic episode. That episode left him scared and angry. He felt confused. He was hurt. And he explained that, in the process of dealing with all that pain, he had been really nasty to those that were trying to help him.

 

I don’t know what is made of him, now. You see, this happened long before LinkedIn or Twitter, and I completely lost contact with him. But I never forgot him, for he taught me a very important lesson: that the person standing in front of me – student, colleague, random stranger in the street… – may be carrying a very heavy burden, or struggling with the black dog named depression.

 

Most of the time, I will not be aware of that burden, and I won’t be able to see the black dog. Or I will be unable to help despite my desperation to do so. Most of the time, the best I can do is to be compassionate.

 

In honour of all of those fighting their demons, and in memory of those that lost the battle, I climb on a table and say: O Captain! My Captain!

 

This is not a post about marketing. But it’s an important one.

Have a great day. And be compassionate.

Analysing photographs and other visual input

20140810-141554.jpgWith photos and videos representing an increasing proportion of the content shared online, I am very interested in their potential for my own research. However, I struggle to incorporate visual data in my work because qualitative analysis software (at least the ones that I am familiar with) can only process alpha-numerical data. This means that I have to analyse visual data manually, which is a slow process.

 

The paper by Hu et al (2014) that I mentioned in my last post (you know, the one about cats not ruling the Internet) describes a computer-assisted approach to analysing photographs. This is what the authors did, as described in section 3.2 of the paper:

Coming up with good meaningful content categories is known to be challenging, especially for images since they contain much richer features than text. Therefore, as an initial pass, we sought help from computer vision techniques to get an overview of what categories exist in an efficient manner. Specifically, we first used the classical Scale Invariant Feature Transform (SIFT) algorithm (Lowe 1999) to detect and extract local discriminative features from photos in the sample. The feature vectors for photos are of 128 dimensions. Following the standard image vector quantization approach (i.e., SIFT feature clustering (Szeliski 2011)), we obtained the codebook vectors for each photo. Finally, we used k-means clustering to obtain 15 clusters of photos where the similarity between two photos are calculated in terms of Euclidean distance between their codebook vectors. These clusters served as an initial set of our coding categories, where each photo belongs to only one category.

 To further improve the quality of this automated categorization, we asked two human coders who are regular users of Instagram to independently examine photos in each one of the 15 categories. They analyzed the affinity of the themes within the category and across categories, and manually adjusted categories if necessary (i.e., move photos to a more appropriate category or merge two categories if their themes are overlapped). Finally, through a discussion session where the two coders exchanged their coding results, discussed their categories and resolved their conflicts, we concluded with 8-category coding scheme of photos (see Table 1) where both coders agreed on, i.e., the Fleiss’ kappa is κ = 1. It is important to note that the stated goal of our coding was to manually provide a descriptive evaluation of photo content, not to hypothesize on the motivation of the user who is posting the photos.

Based on our 8-category coding scheme, the two coders independently categorized the rest of the 800 photos based on their main themes and their descriptions and hashtags if any (e.g., if a photo has a girl with her dog, and the description of this photo is “look at my cute dog”, then this photo is categorized into “Pet” category). The coders were asked to assign a single category to each photo (i.e., we avoid dual assignment). The initial Fleiss’ kappa is κ = 0.75. To re- solve discrepancies between coders, we asked a third-party judge to view the unresolved photos and assign them to the most appropriate categories.

 

Hum… sounds like I a need to get a Computer Sciences degree to be able to do this :-( Plus, the process described still relies heavily on manual analysis to refine the coding scheme and to do the actual categorisation. Still, it sounds like a promising ‘starting point’ to develop an inductive coding scheme. So, I am adding a note to my diary to look into this during my sabbatical (one can always dream big!)

 

Do you use visuals in your research or work? How do you analyse them?

 

References

Lowe, D. G. 1999. Object recognition from local scale-invariant features. In CVPR.

Szeliski, R. 2011. Computer vision: algorithms and applications. Springer.

It’s official: cats don’t rule the Internet

Quick. Answer this question: What is the most popular category of photos on Instagram?

 

I thought it was food, but I was wrong. And if you thought that it was cats you were wrong, too.

 

According to this paper by Hu, Manikonda and Kambhampati, nearly a quarter of content posted on Instagram are selfies. This is closely followed by pictures with / of friends. Pictures of pets are the smallest category!

 

IG paper

 

 

The proportion of selfies and friends photos was pretty much stable across different type of users and levels of engagement (defined as the number of photos posted by a user). In contrast, there was high variance for pets and fashion postings – some people posted lots of photos in these categories, most posted none at all.

IG paper2

 

Source of picture: Hu et al, 2014

The study’s authors conclude that Instagram is mostly used for self-promotion and for connecting friends. I agree with this, but would take the analysis further and suggest that:

  • These findings show that Instagram has broad appeal and is well past its niche stage
  • The data and, particularly, the variance for categories other than selfies and friends, also shows that we can segment and target Instagram users based on their revealed interests
  • Cats don’t rule the Internet :-)

 

Surprised with these findings?