Does my Data look big in this?

 What is ‘Big data’?

It is considered to be the application and usage of data gained from the growing volume, velocity and variety that is now available given the multiple channels and platforms availableTracking and analysing these data means marketers can dig deeper into the minds of the consumer and understand finer details about their preferences and behaviours.

 Data is growth at the rate of approximately 40% per year -McKinsey Chief Marketing & Sales Officer Forum, 2014

 What are the 3 V’s?

Volume is the growth in data coming from online platforms including social media

Example #1 
Online shops can analyse heatmaps to track consumer behaviour, they know their most sought after item based on trackpad or mouse behaviour.
They may not have a high conversion rate, but the heatmap allows businesses to narrow down what the barrier to conversion could be.  Previously, the only data available to physical shop-owners is their own interpretation of what seems popular.heatmap

 

Velocity is the speed in which markets can access data, real-time results are considered to be essential in current analysis.

Example #2
Restaurants can monitor social data and detect certain ‘buzzwords’ during a service period and remedy the issue. A consumer could tweet
‘hate when the service isn’t friendly #disappointed’
and the marketer can receive this in real-time and tell their waiter to be more friendly.

Variety covers the new types of more ‘unstructured data’ (Chaffey and Ellis-Chadwick, 2016) that now exist.

Example #3
An event manager could post an event on Facebook and monitor the responses through comments and shares to determine who the consumers want to share the event with. Trends could be something as simple as special dinners resulting in primarily women tagging men on the platform.

big-data
Growth of Big Data. Source: Soubra (2012)

Is Big Data actually a new idea?

Word Cloud "Big Data"Some researchers argue that the ‘Big Data’ concept isn’t new, it’s simply a term used to push businesses to outsource data-mining and analysis.

This theory is unlikely though, any internet user knows the depth of information available and how specifically targeted some areas can be. This massive amount of information directly relates to the consumer data gathered.

Privacy

The concern of privacy arises regularly when Big Data is concerned. Although websites and platforms have privacy policies to cover them from a legal perspective, there remains ethical issues. Data storage, management and relativity are important from an operational side. Other issues include the level of targeting, purpose of targeting and tracking of personal details.

Big Data is more than an analytical tool for marketers, it also means consumers receive better content that is personally interesting. The mutual benefits align with the growth of a semantic web and mass personalisation.

 

References

Chaffey, D, Ellis-Chadwick, F. 2016, Digital Marketing, 6th Edition. Pearson (Intl), VitalBook file, P. 651

Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly36(4), pp.1165-1188.

McKinsey Chief Marketing & Sales Officer Forum, (2014). Big Data, Analytics, and the Future of Marketing & Sales. USA: Createspace Independent.

Soubra, D. (2012). The 3Vs that define Big Data. [online] Datasciencecentral.com. Available at: http://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data [Accessed 10 Sep. 2016].

Steve, L. (2012). The Age of Big Data. 1st ed. [ebook] New York: The New York Times. Available at: http://s3.amazonaws.com/academia.edu.documents/34393761/2_The_New_York_Times_on_The_Age_of_Big_Data.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1473636025&Signature=gSGK1i1w6tIlZwxUAXgW6aIWh3U%3D&response-content-disposition=inline%3B%20filename%3D2_The_New_York_Times_on_The_Age_of_Big_D.pdf [Accessed 10 Sep. 2016].

Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data.IEEE transactions on knowledge and data engineering26(1), pp.97-107.

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Thinking outside the square: Innovation in business

Dell’s business model through innovation

Dell established themselves successfully in the 1990s by making PCs available for Ansoff-matrixpurchase online. This grew their revenue triumphantly through to the millennium and they have acted creatively to ensure they continue to hold a competitive advantage.

One of the easiest ways to understand a company’s growth strategy is to look at each initiative in terms of Ansoff’s Matrix.

 

Three main initiatives were implemented by Dell 

1. IT consulting service | In addition to hardware and software, Dell looked into the customer service and consulting arena to further their reach to customers. The program was successful and has moved into data storage and management, communications and mobility for flexible IT solutions.

Where does it sit with Ansoff? Market penetration

2. B2B Marketplace | A business to business marketplace where discounted goods could be sold. Although the initiative did not succeed in being a sustainable source of revenue, the concept to provide existing products to a new market was complimentary to the other two innovations.

Where does it sit with Ansoff? Market development

3. Ideastorm | An interesting addition in 2007 which coincided with the beginning of user-generated content (UGC). By allowing users to contribute with ideas and improvements Dell could do multiple things.

  1. Track patterns in improvement suggestions and adapt accordingly
  2. Utilise user’s creativity to grow their product line
  3. Test ideas within an interested and active focus group

Where does it sit with Ansoff? Diversification  

Other Innovation Strategies

Lego ideas

Screen Shot 2016-09-06 at 9.49.41 AMA similar concept to Dell’s Ideastorm site, Lego Ideas encourages users to engage and interact with the brand through a digital medium. The benefits are mutual. Users get the chance to stretch their creative legs and contribute to a community they are involved in, and Lego are able to monitor ideas for future product diversification.

This concept of engaging entrepreneurs and users as idea generators is no uncommon. In fact a multitude of companies have workshops, think-tanks or programs that target small start-ups to help generate ideas.  Some examples are:

 

GE | Ecoimagination Challenges Cisco | Entrepreneurs in Residence Program Google | Entrepreneurs program
Coca-Cola | Accelerator Program Microsoft | Ventures Program Turner/Warners Bros | Media Camp

‘Ideas are the currency of the 21st century’

Try. com

Dell lead the charge in terms of retailers using an online store. They were strategic and knew the tangibility of their product was not the highest priority for consumers.

Unfortunately, clothing retailers do not have the same luxury. There are some some aversions to purchasing online without being able to take the item into a change-room and make sure it looks good.  This means brands need flexible return policies, accurate sizing charts, detailed description of fabric and care.. the list goes on.

A site called Try.com has tackled this issue and partnered with some large retailers to give consumers the chance to literally try before they buy. Zara, Asos, Barneys and Reformation have jumped on board to target the market afraid of the unknown in online shopping.

Screen Shot 2016-09-06 at 9.45.09 AM

References

COSCARELLI, A. (2016). [online] Refinery29.com. Available at: http://www.refinery29.com/try-com-online-shopping [Accessed 4 Sep. 2016].

Dell.com. (n.d.). IT Transformation and Consulting Services | What we offer. [online] Available at: http://www.dell.com/en-au/work/learn/by-service-type-it-consulting#What-we-offer [Accessed 3 Sep. 2016].

Ideas.lego.com. (n.d.). LEGO Ideas. [online] Available at: https://ideas.lego.com/ [Accessed 5 Sep. 2016].

Ideastorm.com. (n.d.). Idea Storm | About. [online] Available at: http://www.ideastorm.com/idea2AboutIdeaStorm?v=1351322692099 [Accessed 5 Sep. 2016].

Lindegaard, S. (2014). 15 Examples of Open Innovation between Big Companies & Startups. [online] Innovationexcellence.com. Available at: http://innovationexcellence.com/blog/2014/08/13/15-examples-of-open-innovation-between-big-companies-startups/ [Accessed 4 Sep. 2016].

Smart Insights. (n.d.). Ansoff matrix – Smart Insights. [online] Available at: http://www.smartinsights.com/marketing-planning/create-a-marketing-plan/ansoff-model/attachment/ansoff-matrix/ [Accessed 4 Sep. 2016].

 

 

Online Consumer Experience

Discuss consumer online customer experiences, using the elements proposed by Rose and Hair ( textbook p. 77 figure 2.13)

What is OCE?

Consumer experience (CE) in the past has been applied across a range of industries Online-shoppingincluding retail, hospitality and other service industries. In more recent years this concept has been applied the online version of these businesses and its known as online consumer experience (OCE).  The experience of a consumer no longer includes a physical involvement, online activities are required to encompass suggestions, social networks and trustworthy reviews from multitudes of users.

Online vs Offline

  Offline Context Online Context Example vs. Example
Personal Contact High to medium Low Talking to the shop assistant about the weather while payment is processing vs. entering card details on computer or mobile device at home
Information Provision Varies in intensity over different media Intensive You’re in a clothes shop and there is a poster advertising a band (that you’re not interested in so you don’t take notice) vs. an ad while shopping online that suggests you buy tickets to the concert because person A, B and C are going
Time Period for interactions Dictated by Organisation Dictated by consumer (anytime, anywhere) Waiting for the late night shopping so you can purchase after work vs. buying at work or from the couch
Brand Presentation Range of tangible devices used to present brand Audio-visual A mattress can be up-sold because a consumer can feel the difference vs. difficult to up-sell when consumer can’t experience the product

There are three key main areas of information into the growth of OCE:

  1. Website quality: this focuses on the development of a site or app, its measurement abilities and performance.
  2. Customer Behaviour: this highlights consumer behaviour in relation to linked activities when searching or purchasing online
  3. Enquiry: The process of enquiring about information including banking, news, weather or travel arrangements.

Consumer Experience is founded in the need to highlight products in an over-saturated market. The difference between a physical product and the value of an experience is ‘the internal and subjective response customers have to any direct or indirect contact with a company’ (Meyer and Schwager, 2007). Majority of literature implies CE is an individual’s psychological state and therefore cannot be applicable to the masses.

The Online Consumer Experience

The process of OCE begins with antecedents or triggers for motivation of the consumer. It then passes into the online customer experience which generates an consequence.

Screen Shot 2016-08-29 at 9.35.17 AM

Antecedents

Information Processing: It is suggested that the information processing includes risk assessment, analysis of previous knowledge and evaluation of safety.

Perceived ease-of-use and perceived usefulness: Often considered the most important factors for online purchasing and include search facilities, site responsivity and accuracy of information.

Perceived benefits and enjoyment: Enjoyment while interacting increases the recognition of online mediums and have led to more interactive elements including games etc.

Perceived control and skill: The consumers ability to navigate the site and learn cognitive skills to improve the users cognitive ability. High levels of usage are linked to positive OCE implying skills are developed and applied to improve experience.

Trust propensity and Perceived risk: Strongly linked with previous customer-organisation relationships or personal recommendations. Higher levels of trust are needed in comparison to offline experiences.

Consequences

Customer Satisfaction: Defined by the level of satisfaction received by the consumer, which has a strong influence on future purchases and consumer behaviour.

Re-purchase intention: Generally a consequence when the consumer has a positive experience as they return to purchase from a specific retailer.

online-shopping2

References

Chaffey, D., Ellis-Chadwick, F. and Chaffey, D. (2012). Digital marketing. Harlow: Pearson.

Meyer, C. and Schwager, A., 2007. Customer Experience. Harvard business review, pp.1-11.

Rose, S., Hair, N. and Clark, M., 2011. Online customer experience: A review of the business‐to‐consumer online purchase context. International Journal of Management Reviews, 13(1), pp.24-39.

 

From web 2.0 to 4.0

The journey from Web 1.0 toward 4.0

In the 1990’s, Web 1.0 entered the realm of public interest.

Berners-lee page
Screenshot of original web 1.0 webpage (Berners-Lee, 1993)

It provided webpages filled with information to users who would read, understand and use. In 1996 this was enhanced by Google who gave users a forum to directly ask for webpages with specific information.

Fast-forward to 2005 and Web 2.0 is revolutionising business operations by transforming the web into a platform.  Companies became, and are still becoming more customer-centric by allowing customers and users to contribute, create and share content.  Because of this shift to e-commerce, marketers created a new digital realm that offered easily accessible, trackable and tangible marketing opportunities based around enhancing the user participation to empower consumers in internet marketing (Labrecque, et al., 2013).

In 2006 John Markoff floated the concept of web 3.0, also commonly known as the ‘Semantic web’ (Berners-Lee et al., 2001). This meant cross-platform integration, automation and data collection. It is still referred to as the Semantic Web which was defined by Berners-Lee et al (2001) as ‘an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation’.

Over the course of web 1.0 to web 3.0, users have become the generators and will continue to control the power over consumable content and information. All channels and site have reevaluated their purpose and are now angled towards creating positive user experiences to build relationships and loyalty globally.

From web 2.0 to 4.0 

Marketing in the Web 2.0 Era

Web 2.0 applications grew in popularity because of the advantages they offer, transparency, referrals, contact with users as well at their effect on customer power (Urban, 2004).  Businesses who recognised the effects of Web 2.0 on consumer’s decision making process as well the the motives behind the interest developed strategies to create a seamless buying experience across channels.  These two concepts have been considered the staples of web 2.0 marketing strategies and the effective application of web 2.0’s user-centric platform.

  • User Generated Content

User Generated Content (UGC) has become a key element for brand awareness as well as a direct way to collect consumer insights. This process of marketing has a multiplying effect as content can be shared to reach unknown consumers. Accessing untapped communities has been difficult in the past as brands need to gain the trust of the users, but in the world of UGC this process can be easily and often unintentional as influential users share their own opinions.

Example: Birkenstocks. They were never cool, not until late 2012 when replicas appeared in Giambattista Valli and Celine’s shows. The fashion bloggers of the world united and although many couldn’t afford the $850 needed for Celine’s fluffy slip-ons, they saw an alternative in Birkenstock. Similar style, high quality and never considered a fashion staple before. A Bloggers dream, to make something cool that has always been overlooked.

As the digital influencers wore more of the sandals, the phenomenon grew as their follows copied the look. Consumers knew the brand, but it was delivered to a new audience through a different and trust-worthy source.  

Screen Shot 2016-08-23 at 12.21.08 PM
UGC for Birkenstock using #birkenstock reaching 11.7k other users.  Source: @the_salty_blonde
  •  Consumer Behaviour

Shifting to user-driven platforms means the behaviour of consumers has the ability to change and demand more information from businesses. Nowadays users access recommendations, endorsements and reviews from trusted sources as part of their decision-making process. As McIntyre (2013) states, consumers distrust marketers and prefer to seek advice from their communities.

Despite this, user empowerment can be leveraged for marketing purposes. There are three main influences on a consumer’s empowerment experience to be considered to take advantage of the new behaviour.

  1. The ability to dictate the features of a choice
  2. Progress cues during the purchasing process and,
  3. Information on other consumers

(Wathieu et al., 2002)

Towards Web 4.0 and the marketing future

Although we’re barely comfortable with Web 3.0, many are looking for ways to begin incorporating Web 4.0 into their marketing strategy. The concept is the harmonisation between humans and machines.

Building on the marketing concepts implemented in Web 2.0, the 4.0 version will be infinitely more complex as channels and information will be shared seamlessly and act as a problem-solver. Total integration will be essential as the platform will become a secondary brain for finding and understanding mass amounts of information.

This process is slowly seeping into social media and other digital channels as the semantic web grows to understand each individual by providing content that has either been viewed by an influencer or is similar to something viewed in the past. Web 4.0 will see this become even more detailed and dynamic depending on user behaviour.

References

Berners-Lee, T., Hendler, J. and Lassila, O., 2001. The semantic web, Scientific American284(5), pp.28-37.

Choudhury, N., 2014. World wide web and its journey from web 1.0 to web 4.0. Int. J. Comput. Sc. Inf. Tech5(6), pp.8096-8100.

Constantinides, E. and Fountain, S.J., 2008. Web 2.0: Conceptual foundations and marketing issues. Journal of direct, data and digital marketing practice9(3), pp.231-244.

Labrecque, I. L., Esche, J. vor dem, Mathwick, C., Novak, P. T. & Hofacker, F. C., 2013. Consumer Power: Evolution in the Digital Age. Journal of Interactive Marketing, 27, pp.257-269.

McIntyre, N., 2013. How Has Technology Changed the Role of Marketing in the Past Ten Years, and how do you see it Changing in the Next Five. [online] Available at: http://www.mba-exchange.com/candidates/knowledge_article.php?kpo=285&session [Accessed 8 February 2014]

Khoo, D., 2014. How has the internet changed consumers over the past 10 years and how can marketers best adapt?, Brandbase [online] Available at: http://www.brandba.se/blog/2014/8/11/how-has-the-internet-changed-consumers-over-the-past-10-years-and-how-can-marketers-best-adapt, accessed 20 August 2016.

Urban, Glen L. 2004, “The emerging era of customer advocacy.” MIT Sloan Management Review 45.2 (2004): 77.

Wathieu, L., Brenner L., Carmon, Z. et al., 2002. Consumer Control and Empowerment: A Primer. Marketing Letters 13, 3, pp.297–305.