Week 7: Online retailer

Online retailer: Brownells

I chose Brownells, the world’s largest supplier of firearm accessories, gun parts and gunsmithing tools, for this week’s blog post due to the recently increased regulations regarding gun ownership and the success the company has had since it developed an e-commerce website in 2002. Located in Iowa, Brownells has provided products and services to the firearms industry for over 70 years, and by fully embracing its web presence, it has more recently become a leader in digital marketing and monitoring.

According to Spin Industry (2012), a company that worked with Brownells and Adobe in integrating web analytics into its website, Brownells uses Omniture to learn more about their customers and serve them better.

Techniques
“Brownells monitors and tracks the performance not only of its sites—Brownells.com, PoliceStore.com and SinclairIntl.com—but also competitors’ sites to make sure it remains ahead of the pack. Brownells uses “SmartBear Software’s AlertSite service to monitor the performance and load times for itself and its competitors, and to generate alerts should something go wrong on any of its own sites. The retailer uses the collected data to benchmark performance and to suggest improvements” (Enright, 2012).

Brownells has also focused on reducing page load times by 30 to 40 per cent in recent years by improving the programming for its e-commerce sites. The retailer has also pinpointed where slow-loading vendor services were slowing page load times (Enright, 2012).

In addition to Omniture and SmartBear, Brownells also uses AlertSite data to benchmark its own performance against leading e-retailers outside of its own product category (Enright, 2012). This led Brownells to recently start using a content delivery network, which further sped page load times to consumers around the globe with a series of web servers spread out geographically according to consumer locations. Clayton Whipple, Brownells’ director of e-commerce has said, “We don’t want to be as good as all the major online retailers. We want to better… Consumers may shop us, but they shop other sites, too, and, directly or not, they are comparing us to those experiences.” (Enright, 2012). These improvements have led to higher sales for Brownells simply due to giving “customers a faster, cleaner site,” which results in an increase in conversions, and that leads to dollars for Brownells (Enright, 2012).

Other systems Brownells uses for web analytics and to maintain monitor its digital presence were found within a Marketing Analyst job posting on Brownell’s website. The posting identifies the responsibilities to include web analytics and website optimization/testing platforms. Knowledge of platforms used includes Google Analytics, CoreMetrics, SiteCatalyst, Test & Target, and Discover. Other responsibilities include data analysis using statistical programs like SPSS, SAS, and STATA. Data visualization tool knowledge ranges from Cognos Insight, SAP Visual Analytics; and CRM software includes Salesforce, Oncontact, Sage ACT! (Careers, 2013).

Keywords
Brownells has nearly 40 keywords listed (WebStatZone, 2012) which include the company name with case variations as well as generic terms like gun, guns, firearm, firearms; and gun brand names and styles. The screenshot below gives an overview of Brownell’s Google PageRank, Site Rank, description, and other web stat information.


     WebStatZone.com (2012)

Use of data collected
Through its various data collection and analytical reporting capabilities, Brownells has learned that “65% of its customers shoot more than 25 times per year, in activities ranging from plinking to big game and varmint hunting” (Spin Industry, 2012). In 2011, Brownells further segmented and assessed its customers needs and announced that it would carry a full selection of quality, brand name ammunition in addition to supplying firearms parts, accessories and gunsmithing tools to armorers, gunsmiths and shooters worldwide.

According to the Brownells’ website privacy policy (2013), the company “may automatically collect certain information about your equipment, browsing actions and patterns, including details of your visits to our Websites, including traffic data, location data, logs and other communication data and the resources that you access and use on the Websites, and information about your computer and internet connection, including your IP address, operating system and browser type.” The policy explains that this information improves the website and delivers a better and more personalized service. The data allows Brownells to estimate its audience size and usage patterns; store information about user preferences; customize the Websites according to individual interests; speed up searches; and recognize users upon returning to their Websites.

The privacy policy also outlines disclosure of user information. Information about Brownells’ website visitors is aggregated but does not identify any individual; however, personal user information can be supplied to subsidiaries and affiliates;
to contractors, service providers and other third parties; and to a buyer or other successor (Privacy Policy, 2013).


While Brownells does not name the subsidiaries or affiliates, it does not take a mental giant to assume at least one of those affiliates is the NRA (National Rifle Association).

Third-generation CEO Pete Brownell is a member of the National Rifle Association board, and the company is a high-dollar donor to the powerful gun-rights organization, giving between $1 million to $4.9 million since 2005 (Eller, 2013). Most Brownells site visitors may not have worry about their information being shared, as most websites use this practice, but some users may not want a frequently debated organization such as the NRA having access to their information.


Additional tools, data collection methods, or metrics for improved efforts
Available research shows that Brownells is highly effective in gathering data, collecting intelligence and using a variety of web analytics tools. The information in this blog is not exhaustive of Brownells procedures and is only based on publicly reported information. If not already performed, Brownells could improve its efforts with metrics containing geographical mapping of user locations in consideration of state gun laws. This technique would be useful to determine how legislation impacts sales in those areas. In the same vein, collecting and comparing data from states with heavy citizen gun ownership versus minimal gun ownership would be useful in pinpointing potential audiences.

References 

Brownells. (2013). Careers. Retrieved March 2, 2013 from http://www.brownells.com/aspx/general/careers.aspx?postingid=127&catid=1

Eller, D. (2013, February 2). A look inside Brownells, Iowa distributor of firearms accessories. Des Moines Register. Retrieved March 2, 2013 from http://www.desmoinesregister.com/article/20130203/BUSINESS/302030032/A-look-inside-Brownells-Iowa-distributor-firearms-accessories

Enright, A. (2012, March 7). Brownells takes aim at site performance. Internet Retailer. Retrieved March 2, 2013 from http://www.internetretailer.com/2012/03/07/brownells-takes-aim-site-performance

PI Reed School of Journalism. (2013). Lesson 7: Advanced Google Analytics. Retrieved March 2, 2013 from ecampus.wvu.edu

Spin Industry. (2012). Case study: Brownells. Retrieved March 2, 2013 from http://www.spindustry.com/aspx/casestudydetail.aspx?id=2

WebStatZone. (2012, September 22). Brownells.com – Overview. Retrieved March 2, 2013 from http://www.webstatzone.com/stat/brownells.com.htm

Week 6 assignment: Traffic parameters

For this week’s assignment, I set up three goals on my blog. The first goal measured visitors to a specific page (last week’s post); second was visit duration over 30 seconds; and third was pages visited. My rationale for these goals stemmed from measuring the popularity of new content; whether that content was interesting enough for visitors to feel engaged; and whether the content interested visitors enough to visit other posts and read more.

For my new position at a community bank, I am interested in creating traffic parameters for an online banking page on our website, which is currently being built. To start off, I believe measuring URL destination and traffic sources will be most important for understanding the effectiveness of related marketing campaigns. Enlisting funnels will allow me to determine the success of the user experience through the process and filters will pinpoint if users are coming from the locations I would like or expect them to be coming from (Sparks, 2010).

Goals

The first goal will be to measure sign ups for the online banking service. Success will be measured by setting up a URL destination goal for the “confirmation” or “thank you” page, which users will be directed to after completing the signup process. An increased number of online banking signups will result in “sales” in the form of increased deposits and decreased printing and paper costs of statements formerly mailed to account holders. Ideally, enquiries from prospective clients will also be generated if users landed on the online banking page from an organic search or from an email marketing campaign. How current and prospective clients found the site can be tracked by setting up a funnel process in Google Analytics. If the minimum amount required to open an online account is a $15 deposit, I can enter $15 for the goal value to get an overall value. To measure the goal value of other pages like newsletter signups, I would need to evaluate how often the visitors who complete the Goal become customers (Google Analytics, 2013). If account managers can close 10% of people who sign up for a newsletter, and the average balance is $500, I would then assign $50 (i.e. 10% of $500) to the Newsletter sign-up Goal (Google Analytics, 2013).

Funnels

By knowing “which steps of the process woos customers” (Goals, 2013), I can understand where customers are entering and abandoning the signup process and create or tweak a more efficient process. For example, by analyzing the account opening funnel and removing some of the requirements fields (requesting the same information twice or including a captcha that is too difficult to complete (Ran, 2009), I can better understand where users are experiencing difficulty, which could lead to abandoning the process.

Goal funnels will only work if visitors are required to move through a series of pages. “Unless required, visitors seldom follow a clear path on your site and a goal funnel won’t help you make any sense of how your visitors move from page to page” Lofgren (2013).  Another useful tool is the Reverse Goal Path report, which indicates if visitors are reaching your goal page through a path that you did not anticipate (Lofgren, 2012).

Fortunately, an online account signup path is being constructed for the new website; however, if this were not the case, Google Analytics’ Visitors Flow report or another program such as Crazy Eggs’ Heat Map could track a user’s progress through the site.

While goals are important for understanding conversation, Funnels are “as essential” (Lofren, 2012), as they serve by themselves more as basic KPIs (key performance indicators) than as actionable starting points for conversion optimization.

Filters

Creating filters provide accurate reports that are not skewed by internal traffic or not relevant if coming from regions outside of the bank’s target area. For the online banking page, there are three necessary filters that should be created. The first would exclude internal traffic (employees and staff visiting the page); another would exclude traffic from regions and cities outside the bank’s target market; and yet another would be a Full Referral URL filter for affiliated sites that may provide multiple references and links to the bank’s website. Knowing which page visitors were linking from would show whether a storytelling content page from the affiliate site was more effective or if a URL link was providing the most traffic. Understanding which reference was more effective would be beneficial for tailoring future affiliate marketing initiatives. Including the “lowercase” filter is also important so that the reports are not perceived as two different unique views when in reality they are not (Nurelm, 2010).

Streiner (2012) suggests setting up a new profile or “at least one profile in your account that does not contain any filters” since Google Analytics does not provide a method to go back and track the data that was filtered out.  Creating a new profile each time a filter is added would provide better segmentation of results and allow for comparisons across filters or over time.

References

Goals in Google Analytics. (2013). Google Analytics IQ lessons. Retrieved February 23, 2013 from http://www.google.com/analytics/iq.html

Google Analytics. (2013). Conversions: About goals. Retrieved February 23, 2013 from http://support.google.com/analytics/bin/answer.py?hl=en&answer=1012040

Lofren, L. (2012). The Google Analytics Conversion Funnel Survival Guide. KISSMetrics. Retrieved February 23, 2013 from http://blog.kissmetrics.com/conversion-funnel-survival-guide/

Lofgren, L. (2013).  4 Google Analytics Goal Types That Are Critical To Your Business. KISSMetrics. Retrieved February 23, 2013 from http://blog.kissmetrics.com/critical-goal-types/

Nurelm. (2010, November 29). Four Google Analytics Filters You Should Be Using. Retrieved February 23, 2013 from http://www.nurelm.com/themanual/2010/11/29/four-google-analytics-filters-you-should-be-using/

PI Reed School of Journalism. (2013). Lesson 6: Successful approaches in Google Analytics. Retrieved February 23, 2013 from ecampus.wvu.edu

Ran. (2009, March 4). 10 must track Google Analytics goals. Web Analytics World. Retrieved February 23, 2013 from http://www.webanalyticsworld.net/2009/03/10-must-track-google-analytics-goals.html

Sparks, D. (2010, March 14). Google Analytics in depth: Funnels and Goals. Six Revisions. Retrieved February 23, 2013 from http://sixrevisions.com/tools/google-analytics-in-depth-goals-and-funnels/

Steiner, J. (2013, February 2). Google Analytics filters and filtering. More Visibility. Retrieved February 23, 2013 from http://www.morevisibility.com/analyticsblog/google-analytics-filters-filtering.html

Week 5 assignment: Valuable reports and measurements

I generated traffic to one blog post, “Content is definitely king” on Saturday, February 16 to 226 people that have me in their circles on Google+. The measurements of interest included: number of page views, content by title, bounce rate, traffic sources, referrers, traffic sources, and mobile devices. I chose these measurements to draw conclusions on ways to improve my blog’s content in relation to current and potential audiences. I am primarily interested in providing interesting posts that will keep viewers clicking-through to other posts (measured by page views, content by title, bounce rate) and understanding/catering to who my audience is (measured by traffic sources, referrers, and mobile device use). Mobile device use may not be of the utmost importance for the Blogger website, as it is optimized for mobile devices, but would be relevant if I needed to measure an e-commerce website’s engagement and conversion rates. For sites receiving higher volumes of traffic, keyword targeting and average session time would also be important metrics to measure the true results of one’s online marketing efforts (Hines, 2011).

Page views
I am interested in page views to measure my blog’s growth through Google+ promotion. Long-term measurement over weeks and months would return more accurate results but I received a whopping three additional page views through promotional efforts on Saturday. Kaushik (2010) says, “page views are dead” (p. 126); however, in this instance, I can directly measure the impact of promoting this blog in terms of effectiveness of reach. Promoting my blog on other social media channels would (hopefully) result in an increase in page views and provide the opportunity to measure trends regarding which channel is most effective for promotion. Gunelius (2013) also notes that measuring page views is an important statistic to provide potential advertisers, to watch for spikes in traffic, and to find the best time to post new content.

Content by title
Content by title is an interesting metric as it identifies the types of content that adds the most value to an ultimate outcome (Kaushik, 2010). In the content drilldown report, I can measure how one blog post is performing in comparison to others and create more content based on, and similar to, the most popular posts. While my blog is titled “IMC 642: Web metrics and SEO” the post I promoted was related to the importance of valuable content. Tailored posts relating directly to Web metrics and SEO could ensure audiences are finding the information they are seeking. For an e-commerce site, this metric would be useful in creating and promoting products similar to top-sellers, resulting in an increased ROI for a company.

Bounce rate
Kaushik (2010) advises that a high bounce rate can mean the wrong people are coming to your site (highlighting problems with campaigns, SEO, etc.); or the page itself is poorly constructed (missing calls to action, etc.); or otherwise broken. A high bounce rate could also mean the content is not targeted enough to a certain audience, which also relates to the content by title metric. Preparing more keyword-targeted and relevant content would decrease bounce rate and improve overall time on site and page views. Prior to Saturday’s Google+ post, my bounce rate was between 88 per cent and 100 per cent. This decreased to a 66 per cent bounce rate, which is not anything to write home about, but suggests that reaching a larger audience can result in acquiring viewers with interest in this blog’s content.

Traffic sources
The screenshot below shows the number of visits by blog has received since the first post. Of viewers visiting this blog, 26 visits were direct, two were Google/organic searches, one was referred from Google+, and one was referred from a classmate’s blog. The direct visitors statistic can be further segmented by the percentage of new visits, which is at almost 8 per cent. As 92 per cent of direct URL visitors consisted of my own visits to my blog, this information can be misleading as Google treats the traffic as direct when a referrer is not passed (Sharma, 2013). Furthermore, this could lead to crediting conversions and transactions to the wrong acquisition channel for a website or e-commerce site (Sharma, 2013).

Referrers
Analyzing referrers, or the amount of traffic from other sites, will provide information on not only where my traffic is coming from, but also what is most interesting and relevant to those visiting my blog. Kaushik (2010) states that receiving 20 to 30 per cent of traffic from referring sites is ideal. In excluding direct traffic, it is apparent that 50 per cent of my traffic comes from referring websites; therefore, I should focus on creating a balanced source of “quality traffic” (Chaffey, 2011) by focusing on search engines (for diverse organic traffic) and direct traffic (for visitor retention and loyalty).


Mobile devices
As previously mentioned, Blogger is optimized for mobile device use but I chose this metric due to the rapid increase of mobile users (myself included), which is projected to reach one billion by 2014 and due to mobile marketing being the next frontier of advertising (Abayomi, 2013). While my blog received 0 views from a mobile device, an e-commerce website, for example, would receive a great deal more. As a matter of fact, $1.2 billion worth of e-Commerce was conducted on mobile phones in 2009 (Abayomi, 2013). Companies should not overlook the importance of utilizing mobile analytics and should be certain their website performs well on mobile devices. Optimizing for mobile provides further behavior and event tracking opportunities as well as additional opportunities to drive user engagement through push notifications and cloud backup options (Abayomi, 2013).


By setting objectives and identifying targets, I have gained valuable insights from analyzing Google Analytics’’ metrics and measurements. While GA provides a plethora of reports to analyze online marketing efforts and effectives, the most important outcome for this blog, and arguably any other blog or website, is to measure the data that can be used to draw conclusions to help you continually improve (Lewis, 2012).

References 

Abayomi, T. (2013). How to Effectively Track 3 Types Of Mobile Metrics. KISSmetrics. Retrieved February 17, 2013 from http://blog.kissmetrics.com/mobile-metrics/

Chaffey, D. (2011, July 4). How balanced is your traffic mix. Smart Insights. Retrieved February 17, 2013 from http://www.smartinsights.com/digital-marketing-strategy/customer-acquisition-strategy/how-balanced-is-your-traffic-mix/

Gunelius, S. (2013). 10 blog metrics bloggers should track through web analytics tools. About.com. Retrieved February 17, 2013 from http://weblogs.about.com/od/addonsandplugins/tp/10-Blog-Metrics-Bloggers-Should-Track-Through-Web-Analytics-Tools.htm

Hines, K. (2011, October 26). How to set up goals and track conversions in Google Analytics. Sprout Social. Retrieved February 17, 2013 from http://sproutsocial.com/insights/2011/10/how-to-google-analytics-goals/

Kaushik, A. (2010, November 15). Beginner's guide to web data analysis: Ten steps to love & success. Occam’s Razor. Retrieved February 17, 2013 from http://www.kaushik.net/avinash/beginners-guide-web-data-analysis-ten-steps-tips-best-practices/

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

Lewis, A. (2012, December 21). Top 10 most important Google Analytics Reports – keyword rankings need not apply. Koozai. Retrieved February 17, 2013 from http://www.koozai.com/blog/analytics/top-10-most-important-google-analytics-reports-keyword-rankings-need-not-apply/

PI Reed School of Journalism. (2013). Lesson 5: Google Analytics. Retrieved February 17, 2013 from ecampus.wvu.edu

Sharma, H. (2013). You are doing Google Analytics all wrong. Here is why. SEO Takeaways. Retrieved February 17, 2013 from http://www.seotakeaways.com/google-analytics-wrong-why/#ixzz2LBSCv3Xs

Week 3 blog topic #1: Content is definitely king

Novak (2010) calls content without conversation “just broadcasting, or just advertising” but I have to disagree. Good content spurs discussion; therefore, conversation could be viewed as a by-product of content, much like a good advertisement will spur interest for a purchase. It could be argued that word-of-mouth is the most important element consumers use to make a purchase – because it is – (Cohen, 2012) but if a consumer hears a good review, goes to look at the product (or content) and doesn’t like it, what good was the review?

I can think of numerous real world examples to represent why content is of primary importance but popular books came to mind immediately. For example, the title, What To Expect When You’re Expecting, a well-known book preparing women for pregnancy, has spent 597 weeks on the New York Times Bestseller list. In comparison, popular celebrity and author Jenny McCarthy penned an insightful and informative book called, Belly Laughs: The Naked Truth about Pregnancy and Childbirth, which only spent a few weeks on the BestSeller list.

Both titles were recipients of a great deal of media hype, arguably more by McCarthy due to her active social media presence and regular appearances on television. McCarthy’s book has an Amazon rating of 4.4 with 729 mostly positive customer reviews. What To Expect When You’re Expecting has an Amazon rating of 3.7 with 581 mostly positive customer reviews. At a glance, it seems that McCarthy’s book was more popular and received more praise; however, the content of What to Expect When You’re Expecting landed it on USA Today's list of the 25 most influential books of the past 25 years. While many arguments could be made against why one book is more relevant or popular than the other, if you consider other classic books like, Huckleberry Finn, published in 1884, or Pride and Prejudice published in 1813, through the lens of their waxing and waning media hype during the past two centuries, you can deduce how I developed this opinion. These two books, in addition to What to Expect When You’re Expecting, provide content that is essentially better than its competitors, thus, feeding more conversation; and so goes the cycle.

Greenberg (2009) says, “Social marketing efforts need to be driven by content, not vice versa. Without content, there is not a whole lot to talk about.” He also says, “Have something to say. Say it often. Be interesting.” I agree with those statements, albeit with one exception. For social media, providing consistently valuable content often is important to stay relevant, but providing one piece of content that will remain perennially relevant is of equal importance (see classic book examples above). The difference is, it is easier to produce pretty good content fairly often than it is to produce one really great piece of evergreen content just once.

For a more closely related social media example, consider this: Hepburn (2009) relays a tale of two coffee vendors by analyzing content vs. conversation. Vendor A (Amy) is an extrovert who has gained a large online following by tweeting and conversing regular with friends and followers, even if the conversation is not always relating to coffee. Vendor B (Jill) is not an extrovert but creates content that educates and entertains coffee lovers: Video of a Best Barista competition, customer video notes about their favorite coffees, and a “Finding the Perfect Coffee to Suit Your Mood” PDF.

Hepburn (2009) says both vendors have used “smart moves to grow brand awareness” but by creating interesting content, Jill gave her audiences something more to talk about. To return to Novak’s Cornflakes and ferret discussion as an example, “I had cornflakes for breakfast” is not likely to generate any sort of conversation because it is boring. There is nothing groundbreaking about that statement. Incorporating a ferret into the conversation does spur discussion but is not providing any sort of useful content apart from a few statements of exclamation from her audience, much like Vendor A.

To paraphrase Hepburn (2009), conversations and relationships are only part of the social media picture that can be sustained for a short time. Content, like a good cup of coffee or a classic novel, keeps an audience coming back.

References 

Cohen, R. (2012, May 22). Marketing influence: The power of persuasion. Forbes. Retrieved February 2, 2013 from http://www.forbes.com/sites/reuvencohen/2012/05/22/marketing-influence-the-power-of-persuasion/

Greenberg, M. (2009, October 20). Content is king of social marketing. MultichannelMerchant.com. Retrieved February 2, 2013 from http://multichannelmerchant.com/social-media/1020-content-social-marketing/

Hepburn, S. (2009, December 21). A tale of two coffee vendors: Content vs. conversation. Media Emerging. Retrieved February 2, 2013 from http://www.mediaemerging.com/2009/12/21/coffee-social-media/

Novak, C. (2010, July 27). Why conversation, not content, is king. SocialMediaToday.com. Retrieved February 2, 2013 from http://socialmediatoday.com/wordspring/152636/why-conversation-not-content-king

Week 3 blog topic #2: Comparing apples to oranges -- what’s your favorite fruit?

(Kim, 2012)

In a sense, comparing Google AdWords to Facebook Ads is a bit like comparing apples to oranges; yet, both platforms seem to have a similar goal of becoming some sort of hybrid apple-orange that is everyone’s favorite choice of fruit.

Both AdWords and Facebook Ads offer fairly simple and straightforward platforms to create an advertising campaign for one’s business, website, or blog. AdWords does not require a minimum budget but a $5.00 activation fee is charged. Facebook Ads’ minimum requirement is $1.00 but does not charge an activation fee. The search results will both contain information like title, two lines of description, web address, and key words relevant to one’s campaign. Furthermore, Facebook’s ad placement of Sponsored Results relating to organic search queries is similar to Google’s approach (Constine, 2012).

The useful infographic (left) “grades” AdWords and Facebook on various features:

In my eyes, Google is primarily a search engine with social tools like “Google +, Gmail, Google chat, Picasa Web albums, etc.” (PI Reed, 2013) with 96 per cent of its revenue coming from advertising (Kim, 2012). Similarly, I consider Facebook primarily a social channel with advertising and integrated search tool options. However, Facebook does receive 86 per cent of its revenue from advertising, which shows its Sponsored Ad results are working well for the organization (Kim, 2012). While both platforms offer advantageous advertising options, elements of segmentation, reach and Click-Through Rates (CTR) are discussed below.

While Google has a highly sophisticated, highly refined ecosystem (PI Reed, 2013) that allows for extensive segmenting and targeting, the search engine will only display ads relevant to a user’s organic search terms. Facebook, on the other hand, allows advertisers to segment and target users with a number of filters like age, sex, likes/interests (religion, hobbies, jobs), relationships, language, education, companies, connections, friends of connections, application authorizations, and even targeting users on their birthdays. This filtering option is “one of the most powerful parts of Facebook advertising” (Facebooktutorial, 2010) that is not currently offered by AdWords.

This element of control allows advertisers to communicate with relevant segments and also towards segments that may be relevant in the future – all without an algorithm’s input. While having control over whom see what is powerful, Facebook’s search results will only direct users to pages on-site vs. off-site to the advertiser’s own domain (Constine, 2012), which may not be as beneficial for an advertiser seeking such traffic.

According to Kim (2012), the average CTR of an ad on the Google Display Network is .4%, almost ten times as high as a Facebook ad. The CTR for Facebook ads in 2010 was 0.051%, dropping from 0.064% in 2010, pointing to a downward trend. With 180 billion ad impressions served up by Google each month, advertisers can expect a 90 per cent reach of all Internet users compared to one trillion page views per month on Facebook, resulting in a 51 per cent reach of all Internet users (Kim, 2012).

Shifting focus, one option Facebook offers users is the choice to 'hide the ad', which pops up a question about whether someone hid it because it was ‘Uninteresting, Misleading, Offensive, Repetitive’ or one of a few more options” (Constine, 2012). This information could be beneficial for advertisers in tailoring messages for future campaigns.

Despite the differences and advantages of both platforms, Facebook Sponsored Results may still be a lot less helpful to advertisers than those that show up on Google Search due to the specificity of user searches on either platform.

Constine (2012) states, “when people search for an entity on Facebook, they’re typically looking for something very specific, such as a particular game or business, and might be more likely to bypass ads. People don’t usually search for ‘camera’ on Facebook and certainly not ‘where to buy a camera?’ Meanwhile on Google those are common queries from budding photographers looking to purchase new equipment. That means ads that could persuade them to choose a certain camera brand can command a high price for Google and sweet, sweet ROI for businesses” (Constine, 2012).

When comparing Google AdWords to Facebook advertising options, the clear winner in terms of reach, at least for now, is Google AdWords. It seems that to Internet advertisers at large, Google provides more opportunities for advertisement visibility and Click-Through Rates; however, Facebook offers greater tailoring capabilities to reach segments that Google algorithmically filters out.

References

Constine, J. (2012, August 22). Facebook officially launches “sponsored results” search ads. Tech Crunch. Retrieved February 3, 2013 from http://techcrunch.com/2012/08/22/facebook-search-ads/

Facebooktutorial. (2010, April 5). Facebook tutorial: How to advertise of Facebook [video file]. Retrieved February 2, 2013 from http://www.youtube.com/watch?v=8jOBDIql4y

GoogleBusiness. (2009, June 15). Getting started with Google AdWords [video file]. Retrieved February 3, 2013 from http://www.youtube.com/watch?v=tx2L6EGa9DY

PI Reed School of Journalism. (2013). Lesson 3: Social media analytics and advertising channels. Retrieved February 2, 2013 from ecampus.wvu.edu

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