Create a plan to become an opinion leader
PROFESSIONAL SKILLS When you have worked through this chapter, you should be able to:
• Manage online reputation using third-party tools
• Apply the search engines’ EU privacy removal process for unwanted content
1.1 INTRODUCTION The fast-changing digital landscape provides many opportunities for marketers. It is important to understand key concepts such as ubiquitous computing and how the pace of technology has changed. This chapter explains how traditional marketing models like Diffusion of Innovation are still valid and apply to online opinion lead- ers, as well as differences between generations.
We explore the meaning and impact of ‘digital disruption’ and ‘the Internet of Things’, with new business models emerging to understand how this applies to consum- ers. In a world where your personal information has value, you can discover more about ‘big data’ and privacy issues that affect marketing plans. The last part of this chapter considers bitcoin and blockchain and how this might influence the future of data management.
1.2 A NEW ERA The growth of digital marketing has changed the relationship between businesses and customers. Scholars and practitioners agree that organisations are keen to use digital marketing to engage with their customers and we have moved into a new era where things look different.
KEY TERM UBIQUITOUS COMPUTING The term ‘ubiquitous computing’ was originally coined by Mark Weiser, who was head of the Computer Science Laboratory at the Xerox Palo Alto Research Center (PARC) when writing in Scientific American in 1991 (Weiser, 1991). At that time Weiser commented that in the future there would be computers everywhere and we would not notice their presence; they would just be there.
Some decades later, we have computers at home and with us at university; they are embed- ded in our mobiles, wearables, in cars, in outdoor billboards – everywhere. We have reached Weiser’s vision that computers are integrated ‘seamlessly into the world at large’ (p. 94).
One of the reasons for these trends and the change in the digital landscape is due to the acceleration in the adoption of new technologies. It took more than 50 years for over 50% of US households to adopt telephones (imagine life with no phone!), nearly 20 years to adopt home computers, yet it took less than 10 years for the same group to adopt smartphones.
In a pre-digital age, you booked a holiday by visiting the travel agents on the high street. It was only on arrival at your holiday destination that you saw what the hotel really looked like. Today you will go online, read reviews, see ‘traveller photos’ or holiday snaps others have shared and ask questions of people who have actually visited the destination ‘IRL’ (= in real life).
THE DIGITAL MARKETING LANDSCAPE 5
1.2.1 THE PACE OF TECHNOLOGY SUBSTITUTION Writing in the Harvard Business Review, Ron Adner and Rahul Kapoor (2016) explored the pace of technology substitution and suggested that the speed of replacement was based on ecosystems. Old technology ecosystems may find product extension oppor- tunities whereas the new technology ecosystems need to counter these challenges. Within their framework there are four quadrants, as shown in Figure 1.1, which can be described as:
• Creative destruction, where there are few challenges to the new tech and few opportunities for the old tech, resulting in fast substitution.
• Robust coexistence, where the old tech fights back and brings out alternatives and a gradual substitution takes place.
• Illusion of resilience, where the new tech moves in with few challenges.
• Robust resilience, where old tech fights back and new tech challenges, bringing about a gradual substitution.
ECOSYSTEM EXTENSION OPPORTUNITY FOR OLD TECHNOLOGY
Y QUADRANT 3
ILLUSION OF RESILIENCE
STASIS FOLLOWED BY RAPID SUBSTITUTION
• GPS NAVIGATORS VS. PAPER MAPS
• HIGH-DEFINITION TV VS. STANDARD-DEFINITION TV
• MP3 FILES VS. CDS
• SOLID-STATE VS. MAGNETIC STORAGE (E.G. FLASH MEMORY VS. HARD DISK DRIVES)
• HYBRID ENGINES VS. INTERNAL- COMBUSTION ENGINES
• CLOUD COMPUTING VS. DESKTOP COMPUTING – IN 2016
• FULLY ELECTRIC CARS VS. GASOLINE-FUELLED CARS
• RFID CHIPS VS. BARCODES
• DNA MEMORY VS. SEMICONDUCTOR MEMORY
• CLOUD COMPUTING VS. DESKTOP COMPUTING – IN THE 1990S
• 16GB VS. 8GB FLASH DRIVES
• INKJET PRINTERS VS. DOT MATRIX PRINTERS
Figure 1.1 A framework for analysing the pace of technology substitution
Source: Adner and Kapoor, 2016, p. 66
It could be argued that there are limitations to this framework as the research was based on a five-year study in the semiconductor manufacturing industry and adop- tion of new products is not always based on product desire, but also availability. In some countries it is harder to get a landline phone than a mobile. The landline requires wires and major investment whereas a mobile network is simpler to deploy. At the same time, growth in landline telephone ownership is declining sharply, espe- cially in the G12 industrially advanced nations. Explore the latest statistics on the Telecommunication Development Sector (ITU-D, 2017).
Activity 1.1 Analyse Technology Change 1. Working in groups, use Figure 1.1, the framework for analysing the pace of technology substi-
tution, to analyse the types of technology changes that you have witnessed in your lifetime.
2. What were the greatest changes?
3. Why was this?
4. Are there any difficulties ensuring all four quadrants in the framework are included?
How do we learn about new products or what influences our judgement to adopt new technology? In 1944 sociologists and behavioural scientists Paul Lazarsfeld, Bernard Berelson and Hazel Gaudet conducted a study to see how mass media affected voters in the US election campaign for President Franklin Roosevelt (Lazarsfeld et al., 1944). The surprising result of their research was that it was influencers, or opinion leaders, not the media, that had the greatest impact. Influencers, who received the messages from what at that time were mainly traditional newspapers and radio, shared this with their ‘followers’.
1.2.2 TWO-STEP FLOW THEORY OF COMMUNICATIONS The research was further developed by Paul Lazarsfeld and Elihu Katz who named this
the two-step flow theory of communications (Lazarsfeld and Katz, 1955) where the
media communication was received by the influencer and then passed to other
There were limitations to the two-step flow theory of communications. It was based on one piece of research, which meant that it was not necessarily generalisable to other situations. It may be that this was a set of exceptional circumstances that could not be repeated. Another issue is that it was a simplistic binary model which assumed that this is how mass media worked. As a result of these limitations, the model was extended from two to multiple steps (the multi-step flow), which was developed by John Robinson (Robinson, 1976) and was used as a basis for other communications theories.
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A key aspect of the digital environment is that we have moved from two-step or multi-step to a totally different understanding of communications with newer models emerging, such as media richness (see Chapter 11, Social Media Management) and uses and gratifications theory (see Chapter 13, Digital Marketing Metrics, Analytics and Reporting), although at the same time some much older theories, such as diffu- sion of innovations, have remained valid.
KEY TERM DIFFUSION OF INNOVATIONS In 1962 Everett Rogers published a book entitled Diffusion of Innovations, which was based on the two-step flow of communications and explored the conditions that increased or decreased the likelihood of product adoption.
In this model, based on how a product gains momentum and spreads or diffuses through a group, Rogers proposed five adopter categories – (1) innovators; (2) early adopters; (3) early majority; (4) late majority; (5) laggards – which considered the time at which an individual adopted an innovation.
The five adopter categories were ideal types fabricated to make comparisons, and Rogers recognised these generalisations. There was criticism of the terminology – no one wanted to be considered as a laggard, which was perceived as being a negative label. Table 1.1 shows some of the general characteristics identified, which I have adapted to apply to digital marketing.
The one notable category is that early majority were seen as opinion leaders, an idea which was identified in the two-step flow theory of communications and which reverberates within digital marketing as organisations strive to seek those to influence product adoption.
Table 1.1 Adopter categories and general characteristics
Adopter category General characteristics % adopters of innovation
(1) Innovators Active information seekers, often buying the latest gadget – who in class has a pair of Snapchat Spectacles?
(2) Early Adopters Opinion leaders who are happy adopting new products, seeking information before others – whose opinion do you seek in class when buying gadgets?
(3) Early Majority Deliberate before adopting – active blog readers who like to gather evidence before deciding.
(4) Late Majority Sceptical and nearly the last to adopt – they may still own a feature phone.
(5) Laggards Suspicious of inventions and only adopt when no choice – perhaps the one remaining lecturer with no mobile phone!
Rogers generalised that opinion leaders (see Key Term) were more cosmopolitan than their followers. One prescient observation from Rogers was that opinion leaders needed access to mass media and had to be accessible. Think about those opinion leaders with mass followers on YouTube and Twitter – they meet these conditions.
KEY TERMS OPINION FORMERS AND OPINION LEADERS Opinion formers are formal experts. They work in this area, may be qualified or professionally trained and have significant specialist knowledge about the subject.
Opinion leaders are informal experts who carry out research and whose knowledge is valued amongst family, friends and followers.