ModCloth’s Engagement Strategy Analysis

             ModCloth is an online clothing, accessories, and décor retailer.  It was founded by two high school sweethearts and built on a foundation of love for vintage and retro style.  In just a few short years, ModCloth has grown from a college dorm operation to a 300 employee business with offices in three cities.  Growing in popularity among women 18-34 and being an online-only retail vendor, ModCloth does everything online.  From internal web analytics to social media to digital advertising, ModCloth has an integrated online strategy.  The next few paragraphs will explore which analytics and social platforms are used, as well as how the data collected is put into action.

Gathering Information

            ModCloth gathers customer information in many ways.  First, ModCloth collects information provided by the customer.  This includes name, email, phone number, shipping address, billing information, and payment details.  This information is provided when making a purchase.  Related to purchases, ModCloth also stores purchase history, shopping behaviors and preferences, and membership information. Additional information could include location or geography through the mobile application, reviews on products, or social media interactions made through the ModCloth site.

              Second, ModCloth collects data through third-party tools, including Omniture Site Catalyst, Quantcast, and Google Analytics (ModCloth, 2013).  These tools automatically collect non-personally identifiable information from browsers based on cookies.  Information collected includes IP address, pages viewed, site navigation patterns, devices used, and geo-location information. 

            Omniture and Google Analytics are both web analytics tools that measure web site performance, such as visitors, traffic sources, devices, conversions, and much more.  The main difference between the two is that Omniture is an engine-independent paid service, with dedicated support.  Google Analytics is free, but is associated with Google and does not provide dedicated support (Yu, 2010).  Quantcast is a tool that measures audience and traffic data across millions of websites.  This tool is free and can be used by marketers to view data on their own website or to analyze competitor websites.  Below is an example of the demographic overview for LinkedIn.  Since ModCloth has their site monitored by Quantcast, they can (and have) chosen to hide their directly measured profile audience data from public view.

            Through these tools, ModCloth can monitor visitor traffic, audience demographics, devices used, as well as sales and conversion data on the site.  In addition to sales, ModCloth has many desired actions for their customers.  Actions include writing a product review, sharing products or purchases through social channels, and posting on the ModCloth blog.  Collecting this information provides ModCloth with valuable user behavior and preferences that can be used to improve performance.  All user and website data collected is used to improve the customer experience and ultimately increase engagement and sales.

Measuring Engagement

            ModCloth’s guarantee is to provide the best possible online shopping experience.  They have strived to create a community around their brand and have many touch points and opportunities for engagement.  They also pride themselves on their dedicated customer service.  Measuring engagement is measuring success for ModCloth.

            ModCloth allows its customers to reach out through multiple channels, including a unique twitter handle (@ModCloth_Care ) and two online chat channels, one for customer service and one for fashion style questions (ModCloth, 2013).  Both Google Analytics and Omniture report traffic to each of these webpages and monthly data can show if inquiries are increasing or decreasing over time.  Reviewing the details of these questions can bring popular issues to light, which can then be incorporated in the FAQ section of the site, decreasing the number of customer service requests.

            In a marketing blog, Kate Morris (2012) writes “they have great products, even better customer service, and their community really is what makes their business” (para. 2).  One of the things she included that sets ModCloth apart is its surveys.  Below is an example of a survey given to someone shopping on the site.  Rather than a boring questionnaire, it is simply a “which would you choose” fashion question.  ModCloth collects these user preferences and uses them to purchase new items.  What better way to find out what people want to buy?

            Another way ModCloth encourages and tracks engagement on their site is through the “Be the Buyer” program.  This program encourages users to browse sample styles and vote on the ones they would like to see sewn and sold at ModCloth.  Then users can browse items actually created through the program as well as items coming soon.  ModCloth uses this data to select which items it will buy and sell.  Through analytics, ModCloth can see engagement metrics and use those to optimize the experience.   

            ModCloth’s site is extremely integrated with social media.  Every product page includes the ability to share through Facebook, Twitter, Pinterest, or email.  ModCloth has even launched its own in-house Pinterest page.  Called “Style Gallery”, users can upload photos of themselves wearing or styling their purchases.  According to ModCloth cofounder, Susan Koger, “This is the place where she comes to buy stuff but also to be part of the community and feel part of the brand” (Gannes, 2012).  Building an online community around the brand is an important goal for ModCloth.  Measuring the traffic, time spent, pages per visit, and percentage of new visits through Omniture and Google Analytics can provide insight on how engaged users are with the site, and which pages are most engaging.

            According to ModCloth’s Social Media Manager, Natasha Khan, the three main social objectives are brand awareness, brand loyalty, and increased traffic to the site.  In terms of return on investment, she states “We measure brand awareness with virality and reach metrics; we measure brand loyalty with engagement and customer care metrics; and we measure traffic to ModCloth.com through tagging and tracking of links using Google Analytics” (Loomba, 2012).

            Overall, ModCloth uses multiple web analytics tools to measure website performance, audience data, and engagement metrics.  Using these tools, ModCloth optimizes its clothing and accessory collection, enhances its social media interactions, and increases engagement.  The data ModCloth collects varies from customer purchase information to browsing behavior and buying preferences.  This information helps to paint a more complete picture of the ModCloth customer and helps ModCloth customize its site to improve the customer experience.

            Since ModCloth looks at multiple pages for engagement metrics and has many social extensions, the Google Analytics application Ducksboard would be a helpful tool to combine all that data in an easy to read, high level dashboard.  Below is an example of the dashboard.  Ducksboard can integrate site performance, social media, customer service, conversion rates, and more through its customizable platform (Ducksboard, 2013).  This tool puts actionable data at a glance to quickly implement optimizations.

References

Ducksboard. (2013). Retrieved from http://ducksboard.com/

Gannes, L. (2012, November 19). ModCloth launches an in-house Pinterest. AllThingsD. Retrieved from http://allthingsd.com/20121119/modcloth-launches-an-in-house-pinterest/

Loomba, A. (2012, August 15). Exclusive interview with ModCloth’s social media team. Thoroughly Modern Marketing. Retrieved from http://www.thoroughlymodernmarketing.com/exclusive-interview-with-modcloths-social-media-team/

ModCloth. (2013). Retrieved from http://www.modcloth.com/help/privacy

Morris, K. (2012, August 28). Positive Outing: Review of ModCloth. Distilled [Blog]. Retrieved from http://www.distilled.net/blog/marketing/positive-outing-review-of-modcloth/

Yu, D. (2010, May 26). Google Analytics vs. Omniture: Independent analysis. AimClear [Blog]. Retrieved from http://www.aimclearblog.com/2010/05/26/blitzlocal%E2%80%99s-dennis-yu-on-google-analytics-vs-omniture/ 

Using Google Analytics to Measure Business Objectives

            Google Analytics has many features and reports that enable users to track and segment website performance.  A few of the most important features available are related to measuring a company’s objectives.  Before jumping into tracking conversions or measuring performance, a company needs to have clearly defined objectives.  These objectives should be measurable.        Once objectives are established, then goals can be created.  Goals are the specific strategies that are used to achieve business objectives (Kaushik, 2010).  In Google Analytics, a goal is a Web site page that helps generate conversions for your site (“Lesson 6”, 2013).  Some examples include a ‘thank you’ page after a user has submitted information, a purchase confirmation page, or just a particular page that is deemed valuable.  There are four different types of goals that can be set up in Google Analytics.  They are URL destination, visit duration, pages/visit, and events.  As we explore each goal in more detail, I will include my personal experience with utilizing these goals on my blog.

URL Destination

            The URL Destination goal tracks specific URLs within the site that marketers consider a conversion.  This type of goal is ideal for ‘thank you’ pages, confirmation pages, or PDFs (Lofgren, 2013).  To gain more experience on how this goal tracks, I implemented it within Google Analytics for my blog.  I chose one blog post URL to track.  So far it does not have any conversions, which means no one has ventured to that page yet.  My goals were only set up a week ago, so I hope to see improvement over time.

Visit Duration

            Visit duration helps marketers understand visitor behavior on the site.  Google Analytics tracks visit duration across the site and it is a dimension that can be used when segmenting data.  Using visit duration as a goal allows marketers to establish a benchmark to view collectively how visitors are interacting with the site.  When setting up this goal, marketers can choose any length of time, including hours, minutes, and seconds.  They also decide whether the goal should trigger greater than or less than the specified amount of time.  If a company has refreshed their website or changed the functionality, this report can help them understand if users are interacting with more or less pages.

            Visit duration is another goal I implemented on my blog to see how much time users were spending on my site.  Since my blog only has 5 posts, there is not a lot of content to consume.  I set my goal to trigger when users spend more than 1 minute on my blog.  While the traffic to my blog is low, and I only implemented the goal last week, I have had 2 visits last longer than 1 minute. 

Pages/Visit     

            The pages per visit goal triggers after a defined number of pages have been visited in one session (“Lesson 6”, 2013).  This goal measures the engagement a user has with the site.  Specifically for retail or e-Commerce clients, this can track how many pages of products users browsed.  For my blog, this was an insightful goal to implement so I could tell how many people were viewing multiple posts.  Since I only have 5 pages, I set my goal to trigger when someone viewed at least 2 pages.  This is an important engagement goal for my blog.  Since implementing, I have had 2 visitors view at least 2 pages.  Considering I only had 11 visits in that same time period that is almost 20% of visits viewing more than one page. 

Event

            An event goal tracks an action taken on the site, which is usually unable to be tracked by a unique URL.  Events can track external links on the site, downloads, social media buttons, or time spent watching a video (Lofgren, 2013).  I have not implemented event tracking yet, but will be experimenting with it in the future.

Goal Values

            An additional feature that Google Analytics provides with each of its goals is the ability to add a goal value.  For example, marketers could put a dollar value on a download or a submission form completion.  Google Analytics will assign the dollar value whenever a goal is completed.  To test this feature, I used a $10 goal value for each of my implemented goals on my blog.  As you can see below, my current goal value is $40 because I have had 4 goal completions.  My number is arbitrary, but this can be a great tool for websites to value actions differently.

Funnels

            A funnel represents the path marketers want visitors to take in order to complete an action or make a conversion (“Lesson 6”, 2013).  For example, to make an e-Commerce purchase, users would put an item in their cart, enter shipping information, enter billing information, review information before purchase, then complete purchase.  Each of those pages can be tracked in a Google Analytics funnel, which can help marketers visually see trends such as user abandonment.  Below is an example of a funnel report.

            I do not have enough content or conversions to warrant implementing a funnel on my blog, but I believe marketers should take advantage of this feature.  It is important to understand visitor behavior at each step a user takes to complete a desired action.  If the drop off is high on one particular page in the process, then marketers can focus on optimizing that page.  Once optimizations are made, marketers can use the funnel report to see if the drop rate on that page decreased.

Filters

            One last feature to discuss is filters.  Filters can be applied to the information in Google Analytics to report only on certain data.  Filters can be set up to exclude visitors from a particular IP address, to report only on a sub-domain, or to convert dynamic page URLs to readable text strings (“Lesson 6”, 2013).  An example of how I could use filters on my blog would be to exclude my personal IP address so my reports would not include traffic from myself.  This would make my reports more accurate. 

            Google Analytics goals, funnels, and filters are all valuable features that marketers can use to measure performance of a Web site.  Specifically, they can help measure business objectives and provide actionable data for optimizing specific URLs to conversion paths.  Implementing goals on my blog has helped me understand how users are interacting with my site.  As I post and promote more content, I will be tracking how my goal metrics change.

References

Kaushik, A. (2010, April 19). Web analytics 101: Definitions: Goals, metrics, KPIs, dimensions,   targets. Occam’s Razor Blog. Retrieved on May 29, 2013 from http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/

Lesson 6: Successful approaches in Google Analytics. (2013). P.I. Reed School of Journalism, WVU. Retrieved from https://ecampus.wvu.edu/webct/urw/tp0.lc5116001/cobaltMainFrame.dowebct

Lofgren, L. (2013). 4 Google Analytics goal types that are critical to your business. KISSmetrics [Blog]. Retrieved on June 30, 2013 from http://blog.kissmetrics.com/critical-goal-types/

Exploring Google Analytics Reports

            Google Analytics is a free web analytics tool that provides insight into website performance through measurement of multiple metrics.  Google Analytics data can be segmented into four groups; audience, content, conversions, and traffic sources.  Each group provides valuable, actionable data to improve site performance.  We will examine each group and the reports available in more detail.

Audience

            Audience data measures unique variables about the visitors to a website.  Some of the most important metrics in this section include visits, unique visitors, pages per visit, average visit duration, and percentage of new visits.  These metrics can shed light on the level of engagement users are having with a site.  For example, pages per visit measures how many pages on average are being viewed during a visitor’s session.  If this number is increasing over time, users are viewing more content on the site.  If this number is decreasing, then users are not exploring multiple pages and ways to increase engagement should be explored.

            The percentage of new visitors is also a useful metric, identifying new visitors compared to returning ones.  Measuring the number of returning visitors shows how much loyalty users have to the site.  Reports can also show other dimensions segmented by new or returning visitors, such as pages per visit and average visit duration.  This data could show whether returning visitors spend more time or view more pages than new visitors.  If returning visitors do have higher engagement, then focus should be on converting new visitors into returning visitors.

            Lastly, the audience segment includes a breakdown of the technology used to get to the site.  Visits can be segmented by browser, device, and network.  This information can be used to test how the website looks on each browser to ensure the user experience is as good as possible.  Device data can be used in multiple ways.  For example, when deciding to create a mobile site or application, data on which pages are accessed the most on mobile devices can be a great starting point for the content that should be included.  Also, if the majority of mobile traffic comes from iPhones, an iPhone application should be created with priority over the Android platform. 

Traffic Sources

            The traffic sources section provides useful information about how users arrive at the site.  Google Analytics has a great feature that displays a pie chart outlining where traffic came from bucketed into search traffic, referral traffic, direct traffic, and campaigns (or paid) traffic.  Then one can drill down to learn more specifics about each bucket.  For example, drilling down into search traffic will display the percentage of organic versus paid, as well as the keywords searched.  This data can help SEO efforts or be used to evaluate how well paid search is performing.

            Drilling down into referrals can help users understand what other sites are driving traffic to a site, including social.  The referral report can identify where users are sharing the site link on Facebook or blogs, and how many people are visiting from those sources. 

            The campaign traffic section pulls together any paid advertising a company is running.  It can track how display, video, mobile, or social advertising is driving traffic to the site.  In looking at all the traffic source reports, Kaushik (2013) states “you quickly end up with a robust understanding of all the things the company is doing and a detailed understanding of paid and organic search performance” (para. 17).

Content

            Content is one of the most insightful sections for understanding what pages are performing well and which ones need some improvement.  In this section, each page can be analyzed by the number of visits, pages per visit, average visit duration, and bounce rate.  One useful way to use these metrics is through the landing page report.  This report shows the top landing pages that users enter on a site.  Kaushik (2013) recommends starting by looking at the top 20 landing pages and analyzing bounce rate.  Specifically, the pages with highest bounce rate means the users came in on that page and left before exploring other pages.  Reasons for high bounce rate can include missing calls to action, broken links, or not enough content.  This is an easy place to see where optimizations should be made.

            The content reports can also identify which content has the most pageviews and which pages users are spending the most time.  Using these insights, a company can focus on creating similar content to the best performing pages.  Another metric under the content section is site speed, which can identify pages that are not loading quickly and could have a negative effect on visits and engagement.

Conversions

            The conversion section is one of the most important sections for measuring performance.  Goals can be set up in Google Analytics to track specific actions that a company wants users to take on the site.  These actions can include downloads, sign-ups, or registrations.  Goal reports can be very effective at tracking return on investment.  Once goals are set up, reports can show the actions leading up to a goal, number of completed goals, and the value of those conversions.  One metric that is often used as a key performance indicator with conversions is conversion rate.  Google Analytics makes it easy to view conversion rates across goals and can depict trends over time. 

            Another report that can help identify how users convert is the conversion funnel report.  This report can show the steps a user takes leading up to a goal.  Through this report, a company can identify where drop off occurs in purchases or conversions.  Not only can the pages leading up to the conversion be reported, but also the traffic sources.  Knowing that paid search visitors have a higher conversion rate than social referrals can help determine where budget should be applied to increase return on investment. 

            Overall, Google Analytics provides mountains of data, everything from visitor locations to highest visited pages to where quality traffic originates.  While there are at least 80 standard reports to view this data, Google Analytics also offers custom reports (Maisner, 2013).  Custom reports are a valuable way to analyze dimensions and metrics that are specifically relevant to a business.  Since goals, conversions, and KPIs are unique for each company, the custom report feature is a necessity to successfully analyze performance metrics.    

References

Kaushik, A. (2013, January 2). Google Analytics tips: 10 data analysis strategies that pay off big. Occam’s Razor [Blog]. Retrieved on June 23, 2013 from http://www.kaushik.net/avinash/google-analytics-tips-data-analysis-reports/

Maisner, R. (2013, May 23). 9 downloadable custom Google Analytics reports. iMedia Connection. Retrieved on June 24, 2013 from http://www.imediaconnection.com/content/33968.asp

Advertising Made Easy

            Google and Facebook are great places for brands to start advertising.  Both platforms have self-service ad interfaces that are easy to use and manage in-house.  Google search accounts for 66.5% of search share, out of 20 billion searches a month (McGee, 2013).  Using Google Adwords is a quick and easy way to start showing up in desired search results.  Facebook is also a great place to advertise.  As of the end of 2012, the average time spent on Facebook a month was 6.75 hours (Fox, 2012).  With consumers spending so much time on Facebook, it is a perfect place for marketers to reach consumers. 

            Both platforms offer easy self-service interfaces and have no minimum spend requirements.  Additionally, both Facebook and Google ads work because they are native ads. “Native advertising is advertising unique to a particular site or platform” (Macdonald, 2013, para. 2).  This is why Google and Facebook ads are successful.  The ad format is similar to the design of the content on the page or platform.  This type of ad is unobtrusive is more likely to be viewed than an ad that would disrupt the content and look out of place.  For example, if you Google “landscaping”, the paid ads look similar to the organic results that populate.  On Facebook, the ads that appear in the newsfeed are formatted to look similar to ordinary posts.

            When using Facebook to advertise, it is important to keep in mind how Facebook ranks its content.  Facebook uses their algorithm, called Edgerank, to rank posts featured in the newsfeed.  Edgerank is based on three primary factors: affinity, weight, and time decay (Al-Greene, 2013).  Affinity measures the relationship between the user and the content creator.  The more a user interacts with that person, the higher the score.  Weight is based on the type of content posted.  Facebook gives more weight to photo and video posts than plain text updates.  Finally, the time content is posted is factored into the equation.  As a post ages, it loses value, so the newsfeed focuses on the most recent information.    

            Due to Edgerank, only 16% of fans will see a post on average (Al-Greene, 2013).  This is an extremely low percentage of fans that will see organic posts.  Facebook ads allow brands to target fans, friends of fans, or users based on other specific interests.  With this targeting, ads are able to reach a larger percentage of users.  Without Facebook ads, most brand organic posts will never be seen.

            Facebook is not the only platform to use an algorithm.  Google uses a unique algorithm to rank search results, for both organic and paid.  Google’s ad rank is based on two factors: quality score and bid.  Bid is the maximum cost-per-click a brand is willing to pay.  Quality score is a measurement of how relevant ads, keywords, and landing page are to a person seeing an ad (Google, 2013).  A higher quality score can lead to lower prices and higher ad positions.  For example, even if Brand A has a higher bid, but Brand B has a higher quality score, Brand B’s ad will win the auction and secure a higher position for a lower cost.

            Overall, both Facebook and Google are great places to implement targeted, relevant ads that reach consumers in a non-obtrusive way.  With the easy-to-use interface and no minimum spend requirements, any business, small or large, can immediately take advantage of these advertising opportunities.    

References

Al-Greene, B. (2013, May 7). What is Facebook Edgerank and why does it matter?. Mashable. Retrieved on June 9, 2013 from http://mashable.com/2013/05/07/facebook-edgerank-infographic/

Fox, Z. (2012, November 28). This is how much time you spend on Facebook, Twitter, Tumblr. Mashable. Retrieved on June 9, 2013 from http://mashable.com/2012/11/28/social-media-time/

Google. (2013). Adwords support. Retrieved on June 9, 2013 from https://support.google.com/adwords/answer/140351?hl=en&ref_topic=24937

Macdonald, R. (2013, January 2). Why native ads matter. Digiday. Retrieved on June 9, 2013 from http://www.digiday.com/publishers/why-native-ads-matter/

McGee, M. (2013, May 15). Bing rises above 17% search market share as Google slips [comScore]. SearchEngineLand.com. Retrieved on June 9, 2013 from http://searchengineland.com/bing-rises-above-17-search-market-share-as-google-slips-comscore-159746 

Can There be Conversation Without Content?

            The advertising and marketing industry has gone through many changes over the last decade or so due to the rapid growth of technology.  Brands used to be able to produce a great commercial and reach the masses with TV advertising.  In today’s fragmented world, the same commercial would reach only a fraction of the audience.  Due to this fragmentation, brands are segmenting advertising, targeting unique sub-sets of its audience through targeted online channels.  Overall, this shift has moved brands from broadcasting to engagement marketing.  It is not enough to just have the content created, consumers need to be interacting with it, talking about it, or sharing it for the content to truly be effective.  Social media is where the majority of this engagement is taking place.

            Social media is the channel on which brands can share content with an audience.  Millions of people are having conversations and sharing content across multiple social platforms, and brands can benefit from getting involved.  How does a brand get consumers to share and talk about it?  It starts with content.  Not just any content, but rich, compelling content.  According to Novak (2010), good content “has action, emotion, and personal experience, and those are the key ingredients to starting a conversation” (para. 5).  It must be valuable to the consumer and interesting enough that they feel the need to share it with others. 

            In the debate of which is more important between content and conversation, I would have to say they have equal importance.  Greenberg (2009) stated “without content, there is not a whole lot to talk about” (para. 4).  Content breeds conversation.  One does not exist without the other. 

            For example, HBO posts a new trailer for the upcoming season of True Blood on Facebook.  Within 24 hours, the post has been shared a couple thousand times and has a few hundred comments.  HBO replies to the comments and maybe even asks users for their favorite scene from the last season, continuing the conversation.  Users might share images or video clips of their favorite scenes from the last season, posting more content and breeding more conversation.

            While both content and conversation are important, conversation is what deepens the relationship with consumers.  Having a lot of good content is beneficial for brands, but it is the conversation driven by the content that creates a connection with consumers.  That connection is where the future of marketing is headed.  Relationship marketing is “a strategy designed to foster customer loyalty, interaction and long-term engagement.  It is designed to develop strong connections with customers by providing them with information directly suited to their needs and interests and by promoting open communication” (Olenski, 2013, para. 1).  Relationship marketing creates brand trust, which leads to brand loyalty.

            Creating good content should be the foundation for any engagement plan.  Content breeds conversation, which is crucial to developing connections with consumers, including current and non-current customers.  Conversations are the key ingredient in relationship marketing, fostering customer trust and loyalty.  Marketing is no longer a one-sided conversation.  Brands need to engage with consumers, through content-driven conversations to make those lasting connections. 

References

Greenberg, M. (2009, October 20). Content is king of social marketing. MultichannelMerchant.com. Retrieved June 9, 2013 from http://multichannelmerchant.com/social-media/1020-content-social-marketing/

Novak, C. (2010, July 27). Why conversation, not content, is king. SocialMediaToday.com. Retrieved June 9, 2013 from http://socialmediatoday.com/wordspring/152636/why-conversation-not-content-king

Olenski, S. (2013, May 9). This is the most important word when it comes to relationship marketing. Forbes. Retrieved on June 9, 2013 from http://www.forbes.com/sites/marketshare/2013/05/09/this-is-the-most-important-word-when-it-comes-to-relationship-marketing/

Lights. Camera. Action!

            The goal of Web analytics is to produce actionable data.  Online marketing is the first channel that can provide marketers with volumes of data in real time.  The key to using Web analytics is to filter out the important data with which marketers can take immediate action.  This ability for immediate action doesn’t exist in the other channels of advertising.  For example, when a TV buy is placed, a marketer must wait until the actual ratings are published to see how many people “watched” their commercial.  If they wanted to measure awareness or brand lift, research that could take weeks or months would need to be done.  There is no ability for a marketer to take action until the campaign is over.  The ability to optimize digital performance in real time is what makes digital unique.

            When deciding where to start with the data, marketers should first look at their key performance indicators (KPIs).  KPIs are metrics that help a marketer understand how they are doing against their objectives (Kaushik, 2010).  These metrics are usually unique to the company and directly tie into the business objectives.  This is where actionable data can be found.

            The KPIs should be established from marketer’s business objectives.  These objectives should be “DUMB: Doable. Understandable. Manageable. Beneficial.” (Kaushik, 2010).  It is critical for a company to have business objectives defined up front because they clarify what marketers hope to accomplish with their site.  Defining those specific objectives helps web analysts decide whether to focus on visitor data or conversion data, for example. 

            Once a marketer has clearly defined objectives, goals should be created.  Goals are the specific strategies used to accomplish business objectives (Kaushik, 2010).  Goals should be 100% measurable.  This is where optimizations will come in.  KPIs will reflect metrics that are related to specific goals.  For example, a goal could be to increase sign-ups.  Therefore, the KPIs could be number of sign-ups, sign-up conversion rate, or bounce rate on pages within the sign-up process. 

            One vital step that many marketers miss is setting up targets.  KPIs are specific metrics that can clearly define performance.  Once marketers have those metrics though, how do they know if the results are good or bad?  In order to know whether 125 sign-ups or 300 downloads is a success or failure, marketers need to have targets.  Targets are numerical values that a company pre-determines as indicators for success or failure (Kaushik, 2010).  Targets help marketers evaluate their performance metrics against another value.  For example, if your company decided the target for quarterly sign-ups is 200, you could use that number to evaluate your performance each quarter, as well as track pacing along the way.  Establishing targets for KPIs is essential to determining success.

            With these steps in place, marketers can optimize their websites from actionable data.  Business objectives and strategic goals paint the framework, while KPIs and targets provide numerical data.   Analyzing these metrics provide insight into actionable areas.  Knowing what metrics are KPIs ensures you analyze the right data.  With the overwhelming amount of data available, clearly defined objectives and goals keeps the focus on the most important data points.  Comparing performance to targets will determine success and the next course of action.  Using actionable data to optimize site performance should be a continuous process.

References

Kaushik, A. (2010, April 19). Web analytics 101: Definitions: Goals, metrics, KPIs, dimensions, targets. Occam’s Razor Blog. Retrieved on May 29, 2013 from http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/

How Unique are You?

           One of the first things a marketer does to begin the process of analyzing their website performance is to determine how many people are coming to their site.  Measuring unique visitors is one of the foundational web metrics available to marketers.  Ideally, this metric tells us the “number of individual people (typically having spiders and robots filtered from calculation), within a defined reporting timeframe, that visited a site.  Each individual is counted only once for a TBD reporting period” (“Lesson 2”, 2013).  This metric is foundational because it can be measured on its own or as the denominator in other web metric formulas.  While this metric is widely used, it comes with a few caveats that marketers need to keep in mind.

            While the definition quotes “number of individual people”, unique visitors really measures the number of unique “browsers”.  This is because people use browsers to access websites.  Unique visitors can be “influenced by browsers that don’t accept cookies or those that reject third-party cookies” (Kaushik, 2010, p. 39).  Most analytics tools use first-party cookies which are rejected less than third-party cookies.  First-party cookies are rejected 2 to 5 percent of the time, while third-party cookies are rejected 10 to 30 percent of the time (Kaushik, 2010).

            Another nuance to keep in mind, especially now, is how users are accessing sites through multiple channels.  Since analytics tools track unique visitors through unique browsers, they count each visit per device by the same person as a unique visitor (Gianoglio, 2012).  For example, I visit a website on my PC to shop for shoes while I am at work.  Later at lunch, I visit the same website on my phone to show my friends at work the shoes I want to buy.  Finally, when I am at home on my couch, I use my tablet to visit the site and purchase the shoes.  Although I am one unique person, because I visited the site through three separate devices, I would be counted as three unique visitors.

            Lastly, not only do different browsers and different devices qualify as a unique visitor, but so does a direct visit from a mobile application.  When a user is in Twitter or another application and clicks on a button to open a link in another page, that visit is counted as a unique visitor.  Even if the user accessed the website previously through their mobile browser, traffic from an application will come through analytics tools as a unique visitor (Gianoglio, 2012).

            Overall, the unique visitor metric is an important metric for all marketers.  Even though it may not be 100% accurate, it is the best indicator of the number of people that visit a website.  This metric can be used to analyze traffic on a daily or weekly basis, or any determined time frame.  It is not only valuable on its own, but helps create ratio metrics, such as visits per visitor or conversion rate.  The unique visitors metric builds the foundation for all web measures.  These important measures can be key performance indicators and provide vital actionable information for marketers to improve performance.  

References

Gianoglio, J. (2012, July 10). Unique visitors in a multi-device world. LunaMetrics [Blog]. Retrieved from http://www.lunametrics.com/blog/2012/07/10/multidevice-multibrowser-visitors/

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

Lesson 2: Basic Web Analytics. (2013). P.I. Reed School of Journalism, WVU. Retrieved from https://ecampus.wvu.edu/webct/urw/tp0.lc5116001/cobaltMainFrame.dowebct