Monday, 17 February 2014

Meeting Consumers Needs in e-Commerce: The OCHN

Meeting consumers needs has been a key focus of every business for many years. However, the rise of e-commerce has opened up businesses to a whole new section of consumers with different wants a needs.

The Online Consumer's Hierarchy of Needs (OCHN) is a framework developed by Valacich, Parboteeah and Wells (2007) in order to create a standard framework for e-commerce businesses so that they can adequately meet the needs of their customers.

Developed from Maslow's highly regarded Hierarchy of Needs, the OCHN divides online consumer's needs into three distinct categories; Structural Firmness, Functional Convenience and Representational Delight (Valacich, Parboteeah and Wells, 2007).

For each category, there is a minimum level of compliance that must be reached in order for consumers to use the website in question and this makes up the horizontal section of the framework and is named the 'Zone of Intolerance'. The remainder of the framework is divided into the same three categories, however this section is not essential to a consumer purchasing, but rather increases the satisfaction consumers have with the website or web page (see Figure 1).

Figure 1       The Online Consumer Hierarchy of Needs
Source: Valacich, Parboteeah and Wells (2007)

The theory is expanded upon further through the consideration of differing websites. These are classified as Utilitarian sites (sites designed to be practical rather than attractive), Hedonic sites (sites designed for attractiveness) and Hybrid sites (sites that require to both be attractive and practical) and the distribution of these three competencies differ depending on the type of website it is applied to (See figure 2).

Figure 2       The OCHN for differing websites
Source: Valacich, Parboteeah and Wells (2007)

While utilitarian sites are more heavily reliant on structural firmness, hedonistic sites benefit more heavily from improved representational delight. Hybrid sites, depicted in figure 2 as a even split, are in actual fact dependant on their exact positioning, which can be more closely related to either utilitarian or hedonic.


The OCHN framework, while not comprehensive, give an indication to e-commerce business on the driving factors behind their consumers motivation to use their site above their competition, and so can be a useful tool when deciding where exactly to invest when re-designing or updating their online platform.

For more information on the OCEN read Valacich, Parboteeah and Wells (2007).
Reference: Valacich JS, Parboteeah DV and Wells JD (2007) “The online consumer’s hierarchy of needs”, Communications of the ACM, Vol 50, No 9, p84-90


Thursday, 28 November 2013

Email Review - Asos

So I have been asked to critically evaluate an email from my inbox today and I have chosen to look at an email I got from Asos.


I often end up opening all the emails I get from Asos, both due to my affinity with the brand and the fact that the subject lines are intriguing, often showing savings or time exclusive offers.

Below is a screenshot of the email shown when opened.
  




As you can see the subject line shows a 30% off deal as an incentive to open, however the subject line is in no way personalised, as a matter of fact, there is no personalisation in the entire email (other than sending make the male version). It could be beneficial for Asos to consider adding some form of personalisation to their emails in order to achieve a more personal feel with their customer base, which is believed to increase brand loyalty among consumers.


I also found it strange that this 30% deal is not available above the fold of the email, which is odd when compared to the emails that I would normally receive such as the example below, where the subject line directly reflects the main deal in the email itself.




Other than this flaw the email is both relevant and laid out effectively. It highlight consumer behaviour for the time of year, showcasing Christmas gift ideas and winter clothing and is attractive with a simple layout.



Liked areas of the email are clearly defined by placing them inside boxes and using clear CTA's which are underlined to refelct hyperlinked text. these link through to relevant pages that accurately reflect both the look and content of the email, sharing similar page layouts, product types and headers. 



Thursday, 7 November 2013

Google analytics and AdSense

So today I started playing around with the analytics i set up about a week ago via google analytics, while confusing at first i found i really useful blog which features a ton of useful information right the way from a beginners guide to using the tools all the way to interpreting results and what actions to take if your stats start to drop.

The blog is created by Simply Business and you can find it by clicking here.

So far I have played around with the different metrics available, switched in and out of the real time feed and tried playing around with the different dates and displays. While its interesting to work out how all of these metrics work, I haven't had that many visitors yet and so the displays aren't overly interesting to analyse.

I've also decided to sign my blog up to Google AdSense in the hope I can earn a little bit of money. Im interested to see how it work but am currently waiting for web address to be approved.

Thursday, 24 October 2013

Data Science


In this article Provost and Fawcett (2013) put forward the idea of data Science, a concept that can be used in order to extract information from sets of data and relies on many processes, principles and techniques used got understanding phenomena using automated analysis.

The information can then be used for Data Driven Decision Making which in turn minimized the need for decisions to be made on speculation. 

The article goes on to address the movement from big data 1.0 to 2.0 and address the interactions between Data science and  Big Data.

The full article is available here: http://online.liebertpub.com/doi/pdf/10.1089/big.2013.1508


Reference
Provost, F., & Fawcett, T. (2013). Data Science and its Relationship to Big Data and Data-Driven Decision Making. Big Data, 1(1), 51-59.

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