HSN.com E-Commerce Redefined

The Home Shopping network (HSN) based out of Saint Petersburg, Florida is a multi-channel retailer of jewelry, electronics, fashion, shoes, handbags, beauty, kitchen, health & fitness, crafts and home goods. For the past fifteen years, shoppers not watching the live programming have been visiting and shopping on Hsn.com (Alexa.com, 2013).

The online and mobile business at HSN now up to $1.4 billion a year in sales, comprises 35-40 percent of total revenues (Froelich, 2013). According to the three-month Alexa traffic rankings, Hsn.com, which is part of the “major retailers” category, ranks in at #1,677 in the world (Alexa.com, 2013). Domestically, Hsn.com ranks in at #371 (Alexa.com, 2013). 

The goal behind analyzing e-commerce web analytics is to improve a user's website and marketing experience — help with product discovery, education, or even entertainment — and simultaneously achieve the marketer's goals whether those goals are to sell more products or increase interaction (Roggio, 2011). For a large multi-channel retailer like HSN, increasing conversion rates and socializing shopping have been key drivers for the business, and both have played a role in HSN’s transition to “boundary-less retail” (Fiorietta, 2013). 

HSN.com uses graphics, promotions, and content to tell the front-end story on the website, but the web metrics reveal the back-end successes and failures of their e-commerce platform. Currently, according to published metrics from Alexa.com, visitors to Hsn.com spend approximately eleven minutes per visit to the site and 52 seconds per page view (Alexa.com, 2013). Visitors view an average of 8.4 unique pages per day (Alexa.com, 2013). Unfortunately, a turn off for visitors is the slow (2.622 seconds) load time for HSN.com, with 77% of sites loading faster (Alexa.com, 2013). Daily traffic is 94, 529 with 841,308 page views (Webstatzone.com, 2013).

In an effort to learn more about their customers engaging with the website, HSN deploys many methodologies, which are stated in their online privacy policy. Information is collected automatically, which may or can include a customer’s IP address, a customer’s browser type and language, access times, the content of any undeleted cookies that a customer’s browser previously accepted, and the referring website address (Hsn.com, 2013). In addition, HSN tracks their customer’s online interactions with cookies. Further stating, “through the use of a cookie, we also may automatically collect information about your online activity on our site, such as the web pages you visit, the links you click, and the searches you conduct on our site” (Hsn.com, 2013). Another tracking tool the brand leverages are web beacons (gifs, pixel tags, or web bugs), which may be used to deliver or communicate with cookies, to count users who have visited certain pages and to understand usage patterns (Hsn.com, 2013). Third parties may use tracking technologies, such as cookies, to collect information about users who view or interact with their advertisements (Hsn.com, 2013). 

The repository for all captured web analytics data is housed in the IBM Coremetrics platform. Coremetrics is the industry's only Web analytics platform that captures and stores all customer and visitor clickstream activity to build LIVE (Lifetime Individual Visitor Experience) Profiles that serve as the foundation for all successful e-business initiatives (Coremetrics, 2012). 

Initiatives HSN might employ to increase overall conversions might include: A/B Testing, landing page optimization, email integration, search engine marketing, on-site search optimization, or cross-sell promotions (Coremetrics, 2012). 

On January 8, 2013 HSN.com debuted a new website after careful testing and analysis. The refreshed e-commerce site helped elevate the customer experience by making the retailer's platforms faster, more efficient, and even more social (HSN.com, 2013). HSN CEO, Mindy Grossman stated after the website release “We are committed to giving our customers the opportunity to experience HSN on her terms, whenever and wherever she chooses” (Froelich, 2013). The company's e-commerce motto is based around the three principles of Content, Community, and Commerce (Froelich, 2013).

Content

“In 2012, Google Inc. made more than 500 changes to the algorithm it uses to rank organic search results, but the main purpose of those changes was to provide consumers searching the web with the best and most authoritative answers” (Enright, 2013). Brands able to produce content that Google thinks matches a query well will show up higher in results than sites Google finds less meaningful (Enright, 2013).

Conductor Inc., an SEO strategy company helps HSN with their search engine strategies. Seth Dotterer, Vice President of Marketing and Product at Conductor Inc. encourages brands like HSN to “Create new and relevant content regularly” (Enright, 2013). To create original content, Dotterer recommends spreading responsibilities for SEO and content creation across the organization, rather than keeping it as a strict marketing or technology function (Enright, 2013).

Hugo Guzman, HSN Senior Manager of Online Marketing has directly benefited from stakeholder buy-in for SEO opportunities. For example, Guzman states, Google recognizes the press releases the public relations department puts out for company news and earnings reports as highly authoritative, and that helps boost search engine optimization for HSN more broadly (Enright, 2013).

Content creation is just one part of the equation. Guzman further highlights that at HSN “We use Conductor to find terms that show for queries that show internally consistent trends to inform merchandizers about what we are not stocking and how they can use that information to improve their product line" (Allen, 2012).


Community 

Even though, Coremetrics provides holistic metrics of the Hsn.com customer, niche platforms are also integrated and analyzed by third party platforms and in-house web analysts.

Mindy Grossman, CEO states that on the community side, “that means engaging consumers on their own terms, with personal and flexible experiences.” One way the brand has realized her vision is by partnering with Mass Relevance, a social curation solution provider that collects and shares consumer insights, which are then released back across social networks in real time (Fiorietta, 2013). Customer feedback — such as reviews, questions and favorite product finds — is cross-published from Facebook, Twitter, Pinterest and Instagram directly on to the HSN e-Commerce site (Fiorietta, 2013). 

“To keep up with consumers who want to browse and shop online with their web-enabled mobile devices and share comments and other content with family and friends, the new design also includes key mobile and social media updates as well” (Brohan, 2013). Since social media is a key business driver for HSN.com the marketing team marketers should leverage a platform like Hootsuite to manage and measure their network of engaged followers. 

Commerce

In 2012, HSN partnered with Foresee Technology to measure mobile customer experiences (Foreseeresults.com, 2012). According to Larry Freed, President and CEO of ForeSee "Even though HSN scores extremely high in the Top-100 Index, they are showing their commitment to consumer satisfaction by expanding its focus to include measuring mobile to better understand its multi-channel, multi-device customers even better ” (Allen-Short, 2012). 

As Hsn.com continues to reinvent their digital platforms, their web analytics team needs to keep current with emerging web analytics trends and platforms. One holistic platform like Coremetrics might not be the best platform to track all key performance indicators. In the case of Pinterest, Pinfluencer might be the best platform of choice to leverage. 

Hsn.com has all the tools necessary to continue to define themselves as a top of mind multi-channel retailer. The brand should continue to use web metrics as a benchmark to support any future business goals and platform improvements. Instinct alone is not enough in the retail world. 



Resources

Allen, Jonathan. (2012). How seo metrics impact hsn’s merchandizing strategy at conductor #c3ny. Retrieved March 3, 2013
http://searchenginewatch.com/article/2206738/How-SEO-Metrics-Impact-HSNs-Merchandizing-Strategy-at-Conductor-C3NY

Allen-Short, Sarah. (2012). HSN uses foresee technology to measure mobile customer experience.
http://www.prnewswire.com/news-releases/hsn-uses-foresee-technology-to-measure-mobile-customer-experience-165563786.html

Brohan, Mark. (2013). HSN infuses social elements into a major e-commerce site redesign. Retrieved March 3, 2013
http://www.internetretailer.com/2013/01/18/hsn-infuses-social-elements-major-e-commerce-site-redesig

Enright, Allison. (2013). Content is kind in a fast-changing SEO world. Retrieved March 3, 2013
http://www.internetretailer.com/2013/02/11/content-king-fast-changing-seo-world

Fiorletta, Alicia. (2013). HSN transitions to ‘boundary-less retail’. Retrieved March 3, 2013
http://www.retailtouchpoints.com/cross-channel-strategies/2284-hsn-transitions-to-boundary-less-retail

Froelich, Paula. Fashion’s new homepage. Retrieved March 3, 2013
http://www.thinkwithgoogle.com/insights/featured/fashions-new-homepage/

Retrieved March 3, 2013
http://www.alexa.com/siteinfo/hsn.com

Retrieved March 3, 2013
http://globenewswire.com/news-release/2013/01/15/516565/10018137/en/HSN-Debuts-Complete-Digital-Redesign-That-Makes-Platforms-Stronger-Faster-and-More-Social.html

Retrieved March 3, 2013
http://www.prnewswire.com/news-releases/coremetrics-client-summit-dispels-the-voodoo-of-ecommerce-54275657.html

Retrieved March 4, 2013
http://www.webstatzone.com/stat/hsn.com.htm

Retrieved March 4, 2013
http://www.hsn.com/article/privacy-policy-8-21-2008/4542

Retrieved March 4, 2013
http://www.foreseeresults.com/news-events/press-releases/hsn-mobile-2012-foresee.shtml

Roggio, Armando. (2011). 10 web analytics solutions for ecommerce merchants. Retrieved March 3, 2013
http://www.practicalecommerce.com/articles/3062-10-Web-Analytics-Solutions-for-Ecommerce-Merchants

Goals, Filters, Funnels in Google Analytics

Every website on the World Wide Web is comprised of a series of single pages that all together form a series of steps. During a customer’s online journey, an individual typically navigates through a hierarchical structure of page views. Web Developers refer to a websites entire page-listing directory as a site map.

Without a clearly defined site map, navigation between pages would most likely be misunderstood and broken, which could result in a negative customer experience.

Depending on the website type, a customers action steps might vary. For a web analyst of an e-commerce site, conversion would be a metric goal worth analyzing. For a non-e-commerce site, such as my blog, data collection and site visits would be other metrics of concern.

By establishing goals, funnels, and filters using the tools in the Google Analytics platform, a web analyst, or a novice like myself, would be able to offer key stakeholders transparent metrics about what is and what is not working within the site map of a website. 

Goals

Forrester Research describes socially inclined consumers as the Groundswell, and understanding the impression a website has on these forward thinkers is vitally important to a brand now more than ever (Forrester, 2012).

In the case of web analytics, a goal is defined as a setting that counts each completion of a specific task on a website (Emerson, 2011).  Every task counted indicates how well a website is contributing to the overall company bottom line. Determining what tasks are desired and the action steps required by customers should be considered before any goals are established in Google Analytics (Emerson, 2011).

Once a decision has been made on the key performance indicators (goals), a Web Analyst would be able to define the following goals: URL Destination, Average Time on Site, Pages/Visit, and Event Goals. The maximum amount of goals per profile is twenty (4 goal sets, and 5 goals per set) (Gabe, 2012).

In the case of my school SEO/Web Analytics blog, I established three conversion goals types that included: Pages/Visit, URL Destination, and Pages Per Visit.

Pages/Visit is an engagement goal type that triggers a conversion when a user visits a certain number of pages (Gabe, 2012). This goal can be set to greater than, equal to, or less than a number of pages, based on what needs to be tracked (Gabe, 2012).

URL Destination is another engagement goal that tracks if a user visits a certain page on a website after completing an action (Gabe, 2012).

In an effort to increase referring traffic to my blog, I wrote a post for the WVU Student Blog with a call to action back to my personal blog. Based on that prompt, I noticed an up-tick in my goal completions for both URL Destination and Page/Visit.

One other area for my to leverage in Google Analytics is the event tool. By establishing an event on my blog would be a powerful way for me to holistically identify a specific visitors actions. The actions of an event could include the following: downloads, video views, clicks on specific links, button clicks, etc (Gabe, 2012).

Based upon the metrics pictured above, I need to continue to look for other opportunities to increase my referral traffic. One way to visualize the referral traffic coming from goals is by implementing funnels within Google Analytics.

Funnels

Funnels and goals can happen in tandem during the goal implementation process. “Funnels will restrict the amount of completed goals to only those who follow through the entire pathway”(Rocheleau, 2012). The benefit of adding funnels will provide much more purpose if chosen goals require a set of intended paths (Rocheleau, 2012).

In addition,“Another option for viewing funnel data is the Goal Flow report, which is in some ways similar to the Funnel Visualization” (Kissmetrics, 2012).

“Goal Flow is somewhat more flexible and detailed and does allow Advanced Segments, but it does not calculate a single funnel conversion rate metric and generally requires a bit more interpretation” (Kissmetrics, 2012).

Based on the image detailing my current goal flow, I am able to discern that I have successfully captured one visit by the blogger.com referrer. The next step of measuring success on my blog is by establishing filters.

Filters

In order to capture web metrics on a webpage, it is necessary to filter out any bias from the subsequent reporting data. By leveraging, Google Analytics filters, a web analyst could include or exclude the following:  a network, pay per click traffic, organic traffic, or sub domain traffic (Overland, 2009).

Google frowns upon setting up more than one filter because, “Adding more than one Include filter to a profile can cause data to not appear in your reports. To allow data to populate your reports again, Google recommends assigning a maximum of one Include filter to each of your profiles” (Alexander, 2011).

Best practices indicate that filters should not be applied to existing profiles. Instead, a new profile should be created in order to ensure that the proper data is captured (Alexander, 2011).

In the case of my Web Analytics/SEO blog, I setup a filter during week six that now filters out my personal network IP address.  If this filter had been established when I paired the Google Analytics tracking code to my blog I would have now be looking at unbiased metrics.

By leveraging the filtering data tool, I am now able to segment and manipulate any future data streams coming into my GA account.

In addition to filters, an e-commerce web producer should perform housekeeping on the site map to ensure that individual pages are named appropriately; otherwise page names will be unrecognizable in a goals report, and any subsequent data would not provide full transparency on traffic patterns (Emerson, 2011).

Every website is a living canvas that can always be updated, tweaked and enhanced. With the tools available in Google Analytics such as filters, funnels and goals, a web team would be able to continue to improve the hierarchy structure defining their web presence.

Resources

Alexander, Dorcas. (2011). How to use more than one include filter (without losing data). Retrieved February 24, 2013

http://www.lunametrics.com/blog/2011/06/24/more-than-one-include-filter/

Gabe, Glenn. (2012). A beginner’s guide to conversion goals in google analytics.

Retrieved February 25, 2013

http://www.searchenginejournal.com/a-beginners-guide-to-conversion-goals-in-google-analytics/42558/

Overland, Helen. (2009). Google analytics filter best practices. Retrieved February 24, 2013

http://www.searchenginepeople.com/blog/google-analytics-filter-best-practices.html

Retrieved February 25, 2013

http://empowered.forrester.com/groundswell/book.html

Retrieved February 25, 2013
http://blog.kissmetrics.com/conversion-funnel-survival-guide/

Rocheleau, Jake. (2012). A guide to: goals and funnels in google analytics. Retrieved February 25, 2013

http://www.hongkiat.com/blog/google-analytics-goals-funnels-tips/

Blogging is a march; measure the journey with Google Analytics

Just as brick and mortar stores capitalize on visual storefronts to entice customers, bloggers can follow suit by posting content and visuals to a themed online storefront. Any storefront whether online or on-site is just a facade for what lies behind the curtain. In the blogosphere, web analytics are the back-end of an interface providing structure and foundation to the front-end visual storefront.

According to Jay Baer, from the blog Convince & Convert, “Without a statistical measure of your blogging progress, adding content to your blog on a regular basis can be an incredibly lonely proposition” (Baer, 2010). In an effort to produce content for the masses, instead of content for a finite following, figuring out what metric to leverage is contingent upon the blog type. Baer suggests separating blogs into three distinct groups: content driven blogs, commerce driven blogs, and community driven blogs (Baer, 2010).

In the case of my Web Analytics and SEO blog, my goal is to build a sense of community around posted content with my audience. Baer suggests that I should pay attention to the following key performance indicator metrics: repeat visits, RSS subscribers, comments and refers from social outposts like Twitter or Digg (Baer, 2010).

By activating and pairing the tracking code supplied by Google Analytics (GA) to my Blogger account has provided me with transparent metrics on visitors interacting with my curated storefront.

Overview

One of the standard reports in Google Analytics (GA) is called Audience Overview. This snapshot overview captures the following metrics: visits, unique visits, page views, pages/visit, average visit duration, bounce rate, and % of new visits. Since repeat visitors are a key benchmark metric for community blogs to measure, GA provides a pie chart segmenting that seven return visitors (43.75%) have come back to my blog (Google.com, 2013). The average visit duration is three minutes and forty four seconds (Google.com, 2013). Forty-one page views have been accessed since the launch of the blog on January 18, 2013 (Google.com, 2013).

On a negative side, the current bounce rate is 56.25%, but “No matter how engaging your blog is, you can expect a high bounce rate for the very simple reason that bounce rate is defined as the percentage of visitors who leave your site after viewing only a single page, and blogs in general are designed for consumption directly on the main page rather than navigation to internal pages” (Fettman, 2012).

In order to best leverage the overview report, Baer suggests setting up goal benchmarks within the report (Baer, 2012). Micro-goals could be an excellent starting point for me and my benchmarks could include: downloading an eBook, signing up for an RSS feed, or successfully sharing my blog with a social network (Baer, 2012).

Content Overview

A total of four blog posts have been shared on my blog and the most recent post amassed the highest page views with 14.63% (Google.com, 2013). In addition, to the content overview section, the In-Page Analytics drop down quantifies the clicks a visitor made by color code. It is intriguing to see that the Blog Archive feature, which I felt was unpleasing to the layout, was leveraged by visitors and should be kept as part of the interface.


Traffic Sources

The all traffic report under traffic sources provides insight on the source/medium of all the traffic coming to my blog. Direct traffic currently accounts for 31.25%, and referral traffic is 68.75% (Google.com, 2013).

Referrals have been a key traffic driver. Other student bloggers have been my top referrers, but no activity is currently coming from social outposts like Twitter, or Facebook. In an effort to widen the referral search pool for my blog, I should post my content across all viable social networks.

In order to improve the low direct traffic numbers on my blog, I should add meta keywords to any future posts. In addition, I should add a meta description to the page source so that when it is crawled by search bots my blog would likely appear higher in a natural search.

Social Sources

The social sources report within the traffic sources drop down is a helpful tool in pinpointing brand advocates sharing my content. In addition, this report tracks the stickiness of shared content across social networks.

Baer is a strong advocate for this report because he believes “The data inspires informed action” (Baer, 2012). Since I currently do not have RSS subscribers, comments, or social shares, I should proactively work on improving this portion of my blog. 

Marcus Sheridan, from thesaleslion.com believes in the concept of stirring up the pot. “You do not have to be over the top, a ‘gentle’ stir is all that is needed to initiate some great conversation” (Sheridan, 2012). In future posts, I should pose a question to help spark conversations within the blogs comments section. In addition, I need to follow the lead of other successful bloggers and start commenting on other blogs. If I start commenting on my classmate’s blogs I would begin to establish a dialogue with future blogging commentators.

With the help of Google Analytics, I will be able to holistically examine the back-end of my website. The data provided from the reports will help me to make front-end storefront improvements.

Baer advises infant bloggers, like myself “Blogging success is a slow march, not a mad dash” (Baer, 2010). With each step I take toward improving my community blog, I will need to keep in mind the goals and objectives I established at the beginning of my blogging march.


Resources

Baer, Jay. (2010). How to match 10 key success metrics to your blogging strategy. Retrieved February 18, 2013
http://www.convinceandconvert.com/web-site-analytics-and-metrics/how-to-match-10-key-success-metrics-to-your-blogging-strategy/


Baer, Jay. (2012). Google analytics social reports provide huge metrics edge. Retrieved February 18, 2013
http://www.convinceandconvert.com/social-media-measurement/google-analytics-social-reports-provide-huge-metrics-edge/

Retrieved February 18, 2013
http://gatipoftheday.com/expect-a-high-bounce-rate-for-your-blog/

Retrieved February 18, 2013
https://www.google.com/analytics/web/?hl=en&pli=1#report/visitors-overview/a38385524w67012327p68931161/

Sheridan, Marcus. ( 2012). 10 ways to get tons of massive comments on your blog every time.
Retrieved February 18, 2013
http://www.thesaleslion.com/ways-get-tons-massive-blog-comments/

Producing Ads of Interest on Google & Facebook

Facebook and Google might be top of mind companies for social networking and searching, but both brands also offer worldwide-recognized advertising networks.

For advertisers looking to leverage either networks, the following ad differences should be closely examined: reach, revenue/growth, advertising performance, targeting, and ad formatting.

Ad Reach

“Facebook is the world’s largest social network comprising over 845 million monthly active users” (Ecommercecircle.com, 2012). Facebook is able to reach 51% of all Internet users (Ecommercecircle.com, 2012).

“Google is the world’s largest online display advertising network, comprised of Google properties including Youtube, Blogger, Gmail, plus 2 million other websites” (Ecommercecircle.com, 2012). Google is able to reach 90% of all Internet users (Ecommercecircle.com, 2012).

Ad Revenue/Growth

In the first quarter of 2012, the Google Display Network had $2.9 Billion in revenue, which excluded 7B in revenues from Google Search (Ecommercecircle.com, 2012).

The first quarter 2012 Facebook revenues were $1.06 Billion, which was 6.5% lower than the fourth quarter of 2011 (Ecommercecircle.com, 2012).

Advertising Performance

The difference between Facebook and Google Adwords all comes down to the click through rate. “The average CTR of an ad on the Google Display Network is 0.4%, which is almost ten times as high as a Facebook Ad” (Ecommercecircle.com, 2012).

Ad Targeting

Facebook is the better platform for advertisers to leverage if a brand needs to gain visibility, or interest with a new customer base. Once a brand forms a “like” presence on Facebook, a brand tribe forms.

On the other hand, Google Adwords is better for advertisers selling specific items because people turn to search engines for specific solutions (Thompson, 2012). If Google Adwords was leveraged, advertisers would be able to target the people looking for their products and services (Thompson, 2012).

Ad Format Differences

Facebook offers advertisers two ad format choices, either a Facebook Ad or a sponsored story. Google, on the other hand, offers advertisers options, which include: text ads, image ads, ads in videos, and ads in mobile web or games (Ecommercecircle.com, 2012).

Once a platform is chosen, marketers should focus on the goals behind the advertisements. Howard Luck Gossage offers this sound advice to online marketers, “The real fact of the matter is that nobody reads ads. People read what interests them, and sometimes it is an ad” (Thompson, 2012).

By closely examining both networks, a brand would be able to choose the platform that best suits the interests of their viewers. “The goal of advertising is not to gain the most visibility; it is to attract the most attention” (Thompson, 2012). Brands able to leverage an advertising networks full capability would be able to produce ads of interest instead of ads for the sake of visibility.

Resources

Thompson, Alexis. (2012). Facebook ads or google adwords: which one’s for you?

Retrieved February 4, 2012 from

http://www.problogger.net/archives/2012/07/26/facebook-ads-or-google-adwords-which-ones-for-you/

Retrieved February 4, 2012 from

http://www.ecommercecircle.com/files/facebook-vs-google-display-network.png

Break down existing content and conversation silos with SoLoMo (Social, Local, Mobile) marketing

We live in a society dependent on technology. Today’s consumers rely on social, local, and mobile systems to seamlessly perform multiple actions (Horton, 2013). Brands now more than ever, need to participate and integrate content and conversations happening across a SoLoMo (social, local, mobile) landscape.

“In years past, social media marketing, geo-local marketing, and mobile marketing (which until recently largely comprised of SMS text marketing to feature phone users) lived in discrete silos” (Horton, 2013). Breaking down long held traditional silos means marketers need to dethrone the belief “Conversation is king, content is just something to talk about” (Novak, 2010).

According to Chris Horton, Content Creator/Digital Strategist for SyneCore Technologies, brands should instead, “Get Social. Think Local. Spend on Mobile” (Horton, 2013). Horton believes content and social messaging should be coordinated because “Content shared on social media amplifies your brand’s online presence while transparent social exchanges project its authenticity, fostering longstanding connections with new prospects and existing customers” (Horton, 2013). Brands unable to leverage SoLoMo by marrying content and conversations will be powerless to the consumer, who is now the king of their own social and mobile technologies.

SoLoMo might be a new marketing buzzword gaining traction, but many brands have begun to meet the demands of technology minded consumers.

Mashable.com

The New Responsively Designed Mashable.com

“Mashable, the largest independent news site, likes to keep its finger on the pulse of how people connect online” (Wildfire, 2012). In 2012, the brand launched a new responsively designed website, which has allowed Mashable to deliver better experiences across every device (Cashmore, 2012). The new website interface focused on three categories reflective of their existing audience’s needs: mobile, social, and visual (Cashmore, 2012).

Mobile

By leveraging the latest responsive technology, Mashable sets the bar high for other brands to deliver a seamless user experience no matter the device used.

Social

“In addition to hosting a slew of engaging hangouts and posting fresh content daily, Mashable encourages its consumers to use social from within the site’s pages” (Wildfire, 2012). Instead of sharing an entire article on social networks, the new Mashable leverages a new approach called “microcontent sharing,” which gives readers the ability to share individual quotes, images, videos, or songs across social networks (Cashmore, 2012).

The comments section on Mashable.com was never an engaging or rich user experience. Since the new redesign debuted, Mashable.com has upped the ante by adding a rich-text editor, which allows readers to post photos from Instagram and Flickr, videos from YouTube and Vimeo, and songs from Soundcloud and Spotify (Cashmore, 2012).

Local

Even though, the Mashable brand has yet to tackle localized banner marketing, the brand is moving towards that direction by “making ads prettier, more fun, and more engaging” (Cashmore, 2012).

Horton encourages brands to adopt the PI principle (participate/ integrate) to ensure a brand is on the right side of the historical shift to SoLoMo (Horton, 2013). Brands currently leveraging the participate principle, like Mashable, already recognize that social and mobile are paradigm shifts. Brands unable to recognize and adapt to the changing landscape will not be able to meet the content and conversational demands made by SoLoMo consumers.

Download the free field guide for SoLoMo below by SyneCore Technologies.

Resources

Cashmore, Pete. (2012). Welcome to the new mashable. Retrieved February 3, 2013 from
http://mashable.com/2012/12/04/new-mashable/

Horton, Chris. (2013). SoLoMo field guide.
Retrieved February 3, 2013 from
http://engage.synecoretech.com/SoLoMo-field-guide?hsCtaTracking=f79c5649-4cf3-4afb-b09c-9bd40da00a46%7C4f36a08c-c7c8-4dba-953f-94edd02884fc

Novak, Catherine. (2010). Why conversation, not content is king. Retrieved February 3, 2013 from
http://www.wordspring.ca/2010/07/why-conversation-not-content-is-king/

Wildfire. (2012). Rethinking the funnel: how your brand’s marketing efforts should evolve for the new social customer lifecycle. Retrieved February 3, 2013 from http://www.thinkwithgoogle.com/insights/library/studies/new-social-customer-lifecycle/

Social Search in the World of Web Analytics 2.0

The social network and the media at large have been buzzing ever since Mark Zuckerberg announced his latest fore into the world of search. His new tool called Graph Search is putting a new spin on web searching. In the world of 2.0 web analytics, this announcement is creating a schism within the search engine network. 

Search engines such as Google, Bing, Chrome, Yahoo, and Facebook are all fighting for market dominance. Figures compiled by Experian revealed that Google’s share of the search market sector dropped to its lowest level in five years during 2012 (Loveridge, 2013). In comparison, the Microsoft Bing search engine’s year-on-year market share increased by 1.15 per cent from 3.84 to 4.99 per cent (Loveridge, 2013).

Bing and Facebook’s Graph Search tools leverage algorithms that help users socialize their search process. “Microsoft Bing could continue to erode Google’s market share lead due to its widespread device availability and the recent announcement that it was to partner with Facebook for its new Facebook Graph Search tool.” (Loveridge, 2013) “While Bing optimization should already be a basic component of most digital marketing plans, it often overlooked. Clearly, being found in a Bing web search is important now and may increase in importance as Graph Search is rolled-out to the masses.” (Wedu.com, 2013)

Mark Zuckerberg believes, “Graph Search and web search are very different. Web search is designed to take a set of keywords (for example: “hip hop”) and provide the best possible results that match those keywords. With Graph Search, you combine phrases (for example: “my friends in New York who like Jay-Z“) to get that set of people, places, photos or other content that’s been shared on Facebook. We believe they have very different uses.” (Wismer, 2013)

Graph Search puts the focus back on likes instead of metrics based outcomes. “If Graph Search is successful, it will be more important that your page is liked by the friends of a person searching for your product or service.” (Wedu.com, 2013) This is a vast change from the clickstream analysis Web Analysts currently leverage. Instead, of analyzing building block metrics such as page visit, sessions, and bounce rate; social search is more concerned with the tastes and whim of the social network, which is much harder to predict and analyze because of their unpredictable nature. Digital marketing as a practice will also have to adjust to accommodate the new social search enterprise.

Because search is a key part of any company’s acquisition portfolio, Avinash Kaushik author of Web Analytics 2.0, is a proponent of pouring a lot of resources into optimizing websites to show up optimally in search engines for relevant queries (Kaushik, 2010). This is all well and good, but how will the schism between social search and web search affect a web analyst’s ability to improve search results for websites? Will web search be absorbed into social search, or will a web analyst have to navigate and improve results across two diverse search engines? Only time will help reveal these unanswered questions, but it seems that Web Analytics 2.0 is transitioning into Web Analytics 3.0.

Retrieved

Wismer, David. (2013). Zuckerberg: ‘FB’s graph search is really neat stuff, but will take years’ (and other quotes of the week). Retrieved January 28, 2013 from

http://www.forbes.com/sites/davidwismer/2013/01/20/mark-zuckerberg-facebooks-graph-search-is-really-neat-stuff-but-will-take-years-and-other-quotes-of-the-week/

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

Loveridge, Samantha. (2013). Google search market share hits five year low. Retrieved January 28, 2013 from

http://www.trustedreviews.com/news/google-search-market-share-hits-five-year-low

Retrieved January 28, 2013 from

http://blog.weduhosting.com/blog/wp-content/uploads/2013/01/wedu-fb-graph-search-infographic.jpg

Web Analytics 101

A website helps to facilitate an on-going dialogue between a customer and a company. In the ever-changing landscape of the semantic web, brands should now more than ever look for ways to quantify their web presence. 

Peter Drucker, the father of business management believed, “What gets measured, gets managed.” (Dykes, 2012) By making the financial investment in leveraging web analytics tools, a brand’s website would then be something worth managing. Having a website for the sake of having a website provides no return on investment if a customer is not able to successfully navigate the site. 

Instead, by establishing sound business objectives and key performance indicators, companies would be able to holistically examine both successful and failing web practices against web analytics data. Every decision regarding the state of a brand’s website should, in the age of the semantic web, come down to what the metrics reveal about a customers journey. The days of guessing and flying blind no longer exist and brand needs to leverage all the tools and resources available in the world of 2.0 analytics.

According to Avinash Kaushik, author of Web Analytics 2.0, “Metrics are the reason we call the web the most accountable channel on the planet.” (Kaushik, 2007) Metrics come in many forms, and Kaushik defines the building block terms as: page, page views, visits, unique visitors, new visitor, repeat visitor, and returning visitor (Kaushik, 2007).

The four attributes of great metrics, according to Kaushik should be uncomplex, relevant, timely, and instantly useful (Kaushik, 2010). Any metric revealed during a web analysis becomes part of a cyclical process where the analyst does the following: reports, analyzes, decides, acts, and reacts (Universem, 2013). 

Image from http://www.universem.be/en/our-solutions/web-analytics/

During the analysis process of a single web page, the bounce rate metric could reveal investment in flashy imagery and promotions might not be worth the time and investment. Kaushik refers to a high bounce rate as, “I came, I puked, I left.” (Kaushik, 2010)

A poor website experience would leave a bad taste in a customer’s mouth. By examining the bounce rate metric an analyst would be able to teach the brand valuable missed opportunities. Correcting page flaws is all part of the acting and reacting stage in the web analysis process. By partnering with a web analytics subject matter expert a brand would be able to move the needle further. Instead, of focusing on vanity metrics such as likes, or followers a brand should instead focus on outcomes. 

According to Kaushik, in this digital age, outcomes are the future of web analytics reporting (Kaushik, 2010). As new development technologies like responsive design continue to change the landscape of the semantic web, a website needs to be able to deliver engaging content across multiple devices. A website is still a catalyst for engagement but with the integration of social media a brand is constantly trying to predict the needs of their customers on an 24/7 basis. Web analytics helps to provide a road map that quantifies what needs to be managed and prioritized by an E-Commerce team. 





Resources

Dykes, Brian. (2012). 31 essential quotes on analytics and data.
Retrieved January 27, 2013 from
http://www.analyticshero.com/2012/10/25/31-essential-quotes-on-analytics-and-data/

Kaushik, Avinash. (2007). Web analytics standards: 26 new metrics definitions. 
Retrieved January 27, 2013 from
http://www.kaushik.net/avinash/web-analytics-standards-26-new-metrics-definitions/

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

Retrieved January 27, 2013 from http://www.universem.be/en/our-solutions/web-analytics/