Finding key metrics for a small e-commerce retailer

Lesson 2 covers basic web analytics terms, the categories they represent, and what each term/metric measures in return. As I am fairly new to the web analytics world, I am interested in learning which metrics carry the most relevance for analyzing customer behavior, and ultimately, the success of an e-commerce site.

Rouse (2005) has defined e-commerce as “the buying and selling of goods and services on the Internet, occasionally referred to as “e-business”, or “e-tailing” for online retail selling. As the term “e-tailing” makes me shudder, this post will reference e-commerce in specific relation to a small retail e-commerce site specializing in sport apparel and recreation gear. More specifically, the parameters of this post will focus on said e-commerce site that uses Google Analytics as its measurement tool and doesn’t really know what to do beyond that. While there is an array of available information offered by seasoned analytics, SEO gurus and other citizens of the Internet, my intention is to narrow down a few metrics that will provide the most effective measures of positive user experiences and a strong ROI for the site under discussion.

To know which metrics are your “must have darling[s]” Kaushik (2010) outlines four attributes of great metrics. Those metrics must be uncomplex, relevant, timely, and instantly useful (pp. 60-61). My focus for this post will keep those attributes in mind while focusing on the areas the e-commerce website is seeking to utilize and improve.

1) Internal site search 
Kaushik (2010) describes Internal site searches as the site navigational element visitors will use most often (p. 96). Furthermore, visitors who use site search end up converting at a higher rate than those that don’t (p. 100). The e-commerce site I am reviewing seems to have disregarded this element as an internal search for the term “winter jacket” produces one result. This is alarming due to over 100 winter jackets available for purchase from the site’s main page. Addressing the internal site issues can, in return, improve sales, increase conversion rates, increase site usage, improve customer retention and loyalty, and improve branding (Charlton, 2012)

A company’s Google Analytics account must be linked to the internal site search (Lofgren, 2012) before data can be mined; however, once completed, the search terms used will literally identify what visitors are looking for. The ideal outcome would be to create an optimized website so that “there should not be a need for people to search” (Kaushik, 2007).

2 ) Referrers 
As a small company trying to compete with larger e-commerce sites selling similar wares, the website utilizes affiliate marketing with nearby recreation areas, organizations, and non-profit organizations; however, analyzing the visits from referring websites often returns extensive, sometimes confusing results. Identifying the traffic source for the top 50 best selling products requires the creation of a number of custom segments (traffic source for product, visits with conversions, etc.). The trouble with this, according to Dlugozima (2009), is having to not only create a huge number of segments, but also analyzing the reports in a timely, efficient manner.

Kaushik (2009) advises creating a segment with all products and then checking them by source. In addition, one can add more data in the item fields for tracking for the top 100 products. Using filters to group things together is also an option, as shown below:

3) Segmenting
The third and final metric most important for this case is audience segmentation, something which the company hasn’t taken full advantage of. Fortunately, Peter Bourne, CEO of Spring Metrics offers helpful advice for where to begin: 

• Visit count 
• Time on site 
• Source (search, email, PPC, social, etc.) 
• Geographical location 
• Mobile / tablet / desktop 
• Conversion history 
• Clickstream (page visit history) 

To segment for greater insights, Bourne provides a nice little summary for the novice:

• Find a simple tool. Don’t get hung up with complicated tools. Find something that takes less than 30 minutes to install and delivers human-readable data. 

• Learn something small every day. Find a time slot that works for you, and spend 10-15 minutes every day looking at your traffic segments. In a week or two you’ll find that you’re developing a sense of where things are going well—and where they’re not. 

• Explore two segments. Pick one segment that is doing well and write down the top three attributes you think contribute to its performance. Next, pick a segment that is doing poorly and write down three ideas to improve its performance. 

• Focus on high-volume, underperforming segments. The greatest gains in conversion rates (and therefore revenue and margin) often come from increasing the worst-performing segments, not from further optimizing the best performers. 

• Test, learn and repeat. Adopt an incremental improvement mentality. If you can take a visitor segment with just 20% of your traffic and improve the conversion rate from 2% to 3%, you’ve got a 10% improvement to your site-wide conversion rate! Big results from small changes. 

While I undoubtedly know more about measuring web analytics now vs. before writing this blog post, I would be interested in anyone else’s opinion who has started from the ground up in identifying what is most valuable for measuring the success of a small e-commerce website.

References 

Bourne, P. (2012, October 2). How to increase your website traffic conversion rates through segmentation. Smart Insights: Sharing advice for better marketing. Retrieved January 26, 2013 from http://www.smartinsights.com/digital-marketing-strategy/segmentation-ecommerce/ 

Charlton, G. (2012, July 25). Site search for e-commerce: 13 best practice tips. E-Consultancy. Retrieved January 26, 2013 from http://econsultancy.com/us/blog/10407-site-search-for-e-commerce-13-best-practice-tips 

Dlugozima, J. (2009, January 6). Re: Google Analytics maximized: Deeper analysis, higher ROI & you [discussion comment]. Occam’s Razor Blog. Retrieved January 26, 2013 from http://www.kaushik.net/avinash/google-analytics-maximized-deeper-analysis-higher-roi-free/#comments 

Kaushik, A. (2009, January 6). Google Analytics maximized: Deeper analysis, higher ROI & you. Occam’s Razor Blog. Retrieved January 26, 2013 from http://www.kaushik.net/avinash/google-analytics-maximized-deeper-analysis-higher-roi-free/#comments

Kaushik, A. (2007, October 16). Kick butt with internal site search. Occam’s Razor Blog. Retrieved January 26, 2013 from http://www.kaushik.net/avinash/kick-butt-with-internal-site-search-analytics/

Kaushik, A. (2010). Web analytics 2.0: The art of online accountability & science of customer centricity. Indianapolis, IN: Wiley Publishing.

Lofgren, L. (2012, April 2). The 8 Google Analytics features every site must have enabled. Kiss Metrics. Retrieved January 26, 2013 from http://blog.kissmetrics.com/8-google-analytics-features/

PI Reed School of Journalism. (2013). Lesson 2: Basic web analytics. Retrieved January 26, 2013 from ecampus.wvu.edu

Rouse, M. (April 2005). E-commerce (electronic commerce or EC). Search CIO Tech Target. Retrieved January 26, 2013 from http://searchcio.techtarget.com/definition/e-commerce

Authenticity as a weapon: Google's algorithm changes and impacts on SEO

Lesson 1 tells us that the components of a web site experience (i.e. content, distribution, and consumption) are continually evolving and the various web site optimization strategies that can help a company organically increase their web visibility are changing concurrently (PI Reed School of Journalism, 2013).

A prime example of these changes is apparent in this week’s Google announcement regarding updates to its search algorithm, with the changes projected to affect about 1.2% of all English-language queries (Sullivan, 2013). Each year, Google changes its search algorithm up to 500 – 600 times. While most of these changes are minor, every few months Google rolls out a “major” algorithmic update that affect search results in significant ways (SEO Moz, 2013).

The most recent Panda #24 update is designed to target pages that aren’t necessarily spam but aren’t great quality either (Stamoulis, 2013). In a similar vein, Google updates announced last year, named Penguin, enacted “important algorithm changes targeted at webspam” (Stamoulis, 2013). These updates, which were designed to improve the quality of Google organic results, have been called “game changing” by SEO blogger Sean Penson (2012).

At present, Google results are muddied with millions of artificial links, created to reach a high page ranking on Google search. “There is therefore a paradigm shift taking place in the way Google works as it attempts to move from its existing method of organizing information based on a document retrieval process to one based on semantics and understanding user intent (Penson, 2012). Penson (2012) also writes, “the days of link building to valueless and irrelevant sites such as directories and networks” are as good as done and dusted. The new focus will be on “a place where relevance is king” (Penson, 2012).

The future of the semantic web is based on understanding the user intent behind a search query with Google moving away from its previous lifeblood, the PageRank model. The new engine will make the search process easier by better understanding relationships, i.e. how one piece of content is improved by another on a related theme and by mapping the relationship between words and phrases to "entities" (people, places, etc), something that Apple’s Siri already has a bit of head start on (Penson, 2012).

Penson (2013) gives an example of this algorithm in action:

“So, let’s say I type in ‘what’s the weather today?’ At present Google might know where I am but would find it difficult to associate other content to that query. The reason I’m searching for it may well be because I want to know whether I can BBQ, or complete that landscaping project I’ve been researching online. 

Google can improve its results by ‘knowing’ why I’m searching for the weather so it can also throw up food offers or home improvement guides.” 

While that is all very well and interesting, the big question for SEO enthusiasts and marketers is, how do these changes ultimately affect us? While the updates are only impacting a small percentage of U.S. searches at the moment, Penson (2013) advises that search marketers remain aware that these updates can help explain changes in rankings and organic website traffic analysis.

Furthermore, Google’s updates are now emphasizing the importance of website “content quality” more than ever (Kumar, 2012) to deliver what it believes will be a more personalized and effective result.

Cazier (2013), the author of the PM Digital study outlining the updates, suggests 30 ways to move beyond traditional link building. From this study, Sullivan (2013) points out starting out at paying more attention to incoming links that are immune to future updates, such as the Better Business Bureau or the Chamber of Commerce. In addition, avoid violating Google's quality guidelines of  keyword stuffing, purposeful duplicate content, doorway pages/cloaking and link schemes as "current violators have been put on notice that their tactics must change” (Cazier, 2013).

As visitor engagement and high quality content are the current focus, marketers should ensure their sites offer valuable information to users to be aptly rewarded by Google’s future updates.

While researching Google’s algorithm updates, I was reminded of other changes in history that resulted from the public’s call for authenticity, namely in the advertising and public relations industries. While publics can be swayed, or even tricked with technologies and trends for a certain length of time, ultimately, one thing that has remained constant is a public’s desire for authentic, quality information that meets their needs. For example, the following, written by Edward Bernays in his 1928 piece Propaganda, still rings true today:

“While the public should appreciate the great economic benefits which business offers, thanks to mass production and scientific marketing, business should also appreciate that the public is becoming increasingly discriminative in its standards and should seek to understand its demands and meet them.”

References 

Bernays, E. (1928). History is a weapon: Propaganda. Retrieved January 25, 2013 from http://www.historyisaweapon.com/defcon1/bernprop.html

Cazier, C. (2013). 30 ways to move beyond traditional link building. PM Digital. Retrieved January 25, 2013 http://www.pmdigital.com/_asset/n74cw3/PMD_LinkBuilding_Report.pdf

Kumar, A.J. (2012, June 12). What Google's Panda and Penguin Updates Mean for the Future of SEO. Entrepreneur. Retrieved January 25, 2013 from http://www.entrepreneur.com/blog/223765

Penson S. (2012, August 27). Is Google afraid of the big bad Wolfram? Search Engine Watch. Retrieved January 25, 2013 from http://searchenginewatch.com/article/2200995/Is-Google-Afraid-of-the-Big-Bad-Wolfram

Penson, S. (2013, January 10). Semantic web and link building without links > the future for SEO? The Daily SEO Blog. Retrieved January 25, 2013 from http://www.seomoz.org/blog/semantic-web-and-link-building-without-links-the-future-for-seo

PI Reed School of Journalism. (2013). Lesson 1: Intro to web analytics. Retreievd January 25, 2013 from ecampus.wvu.edu.

SEO Moz. (2013). Google algorithm change history. 2013 Updates. Retrieved January 25, 2013 from http://www.seomoz.org/google-algorithm-change

Stamoulis N. (2013). Google Panda Update vs. Google Penguin Updates. Brick Marketing Blog. Retrieved January 25, 2013 from http://www.brickmarketing.com/blog/panda-penguin-updates.htm

Sullivan, L. (2013, January 25). Google's algorithm changes throw marketers, new study comes to rescue. Media Post. Retrieved January 25, 2013 from http://www.mediapost.com/publications/article/191919/googles-algorithm-changes-throw-marketers-new-st.html#ixzz2J6k3BivS