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/