The Next Level for Online Retailer, Drugstore.com

Online retailers understand the importance of using web metrics to make informed decisions about their business and to enhance sales. Companies like Amazon, Sephora and Zappos typically collect a wide array of information from customers and prospects, including conversions, visit duration and referrers, to name a few.

One online retailer I’ve used to purchase hard-to-find health, beauty and pet products for the past three years is Drugstore.com. I’ve found that this retailer almost always has what I need – and typically at a good price – when I can’t find it in local brick-and-mortar stores.

But one of the most important things that keeps me coming back to this retailer is its desire to have an upfront and open relationship with it customers – as outlined on two pages of the company’s website: Terms of Use and Privacy Policy. Under Terms of Use, Drugstore.com details what it expects of its customers, including providing accurate account information, honoring copyrights and using the site for lawful purposes only. Under Privacy Policy, the company details what its customers can expect from Drugstore.com, including agreements with third parties, social media and email.

What I appreciate most about this company’s Privacy Policy page is Drugstore.com’s disclosure of what information it collects and how it will be used (1999-2013, para. 10):

We automatically receive and collect certain types of information whenever you visit our websites. For example, like many other websites, we use "cookies" and web beacons (described below) and obtain certain types of information when your browser accesses our websites. This information includes the Internet protocol (IP) address of your computer, your geographic location as determined by your IP address, your browser software and operating system, your web server, the date and time you access our site, session information (such as download errors and page response times), information about your viewing, search and purchase history, and information about the referring URL and the URL clickstream to, through, and from our websites. We use this information to monitor the usage and performance of our site, to enhance our customers' search and shopping experiences and to determine aggregate information about our user base and usage patterns.

While I don’t typically like businesses collecting information about me as a consumer, I do understand why they do it as a marketer. By collecting information about my online habits, the company can better target products, services, discounts and more to keep me coming back – what Drugstore.com refers to above as enhancing “our customers’ search and shopping experiences.” It also can help the company understand if its website has any issues, such as challenging processes or poor information, that keep me, and other customers, from seeing a purchase through to completion or creating an account – referred to as monitoring "the usage and performance of our site" and “aggregate information about our user base and usage patterns” in the company’s disclosure also referenced above.

Based on what I’m learning in my web analytics course at West Virginia University, I suspect Drugstore.com has set up several e-commerce goals for its websites, and tracks conversions and funnels, accordingly (if not, I would strongly encourage the online retailer to do so). I also suspect (and suggest) that some of the metrics Drugstore.com collects are focused on helping the company answer the following questions:

•  How do customers arrive at our website and what keywords are they using to find it? (i.e. referrals and SEO)
•  How often do customers return and how long in between their visits (i.e. frequency and recency)?
• What types of products are customers looking at and how many are they looking at (i.e. page views and page views/visit), and what are they purchasing (i.e. conversions)?
• Where are we losing customers? (i.e. bounce rates and funnels)
• How many visitors sign up for an account and/or make a purchase? (i.e. conversions)
• Are there are any parts of our account process that might be challenging and causing customers to leave? (i.e. funnels and conversions).

Just think of the wealth of information Drugstore.com could have at its disposals by combining its website metrics with knowledge gained from its social media sites, advertising and paid search: the “story” of the company’s online presence could really come to life – to the benefit of the business. Kaushik (2010, p. 357) explains:

The toughest challenges in online measurement are the touchiest. Gaining a Conversion is complex: a Visitor may visit your website multiple times and be exposed to multiple online marketing campaigns. And because we live in a “nonline” marketing world, the influences on a Visitor are not limited to online channels. We see television ads and billboards. Therefore, our Outcomes are no longer limited to online Conversions; we might do our window shopping online, but we convert offline.

For these reasons, Drugstore.com should consider using vanity URLs in its public relations, advertising and offline marketing efforts to assess how these elements can help drive online conversions. The company also should consider using unique coupons and codes in its offline campaign efforts to help determine effectiveness in reaching online ecommerce goals. And Drugstore.com should view traffic patterns online, when campaigns are running, to see what impact those efforts are having on the company’s online presence.

Additionally, Drugstore.com should look at the applications available from Google Analytics’ gallery. Two applications I suggest the online retailer should consider – and the reasoning behind those suggestions – are:

•  SessionCam. This application allows companies to record and replay user activity on websites, giving them the chance to observe the actual customer visits associated with the company’s web data. This application would be particularly useful in the company’s re-marketing efforts, as well as providing valuable conversion insights.
• Sprout Social. This tool is a “social media management platform that helps businesses effectively manage social channels and provide an exceptional customer experience. By integrating with Google Analytics, users are able to see their web traffic in relation to their social media activity on a single dashboard, (Google, 2011). Sprout Social can help Drugstore.com better understand how its social media activity is performing toward realization of online ecommerce goals.

All of these are suggestions Drugstore.com should consider using, if the online retailer isn't already doing so, to enhance realization of the company's ecommerce goals. This information taken together – from suggested questions and their associated metrics to integration of on- and offline behavior to tools that can enhance understanding and reporting – can help Drugstore.com predict the future online behavior of its customers, allowing the retailer to identify unrealized opportunities and drive growth. Rogers, principal at ConvertClick, explains in a blog (Puri, 2013, para. 8) why retailers need to use predictive analytics to improve online shopping experiences:

Generally speaking, analytics is about improving the decision-making process. The goal of predictive analytics is to analyze past and present behavior patterns to predict trends before they happen and build sound business strategies. That’s the next level for online retail.

I could not agree more with Rogers’ about the next level for online retail – actionable insight – and believe this is absolutely necessary for Drugstore.com to take full advantage of its multichannel analytics. What about you? Is there an online retailer you patronize regularly that you believe is drawing actionable insight from its online presence? If so, why and how do you think that retailer is doing this?

References

Drugstore.com. (1999-2013). Retrieved Dec. 7, 2013, from http://www.Drugstore.com/

Drugstore.com (1999-2013). Terms of use. Retrieved Dec. 7, 2013, from http://drugstore.custhelp.com/app/answers/detail/a_id/512

Drugstore.com. (1999-2013). Privacy policy. Retrieved Dec. 7, 2013, from http://www.Drugstore.com/drugstore/qxc148674

Google. (2011, July 5). Sprout Social. Google. Retrieved December 4, 2013, from http://www.google.com/analytics/apps/about?app_id=1240001

Kaushik, A. (2010). Web Analytics 2.0. Indianapolis, IN: Wiley Publishing, Inc.

Wauters, R. (2011, March 24). Boom! Walgreens buys online retailer Drugstore.com for $409 million. Retrieved Dec. 7, 2013, from http://techcrunch.com/2011/03/24/boom-walgreens-buys-online-retailer-drugstore-com-for-409-million/


 

Goals and Funnels and Filters – Oh My!

Last week, I wrote about a variety of metrics I looked at to determine the effectiveness of my blog – such as recency, bounce rate, referrers, traffic and time spent on page, to name a few – given its eight unique visitors. While that analysis was interesting, I know it was very limited given the low number of individuals who are visiting my blog. However, I’m happy to report that my blog has picked up another five unique visitors in the past week for a total of 13 and that, while I know I have a long way to go, growth in unique visitors does give me hope I’m going in the right direction.

This week, I’m going to look at some of the reports and features I’m didn’t address last week – specifically goals, funnels and filters – and talk about how I am starting to use them. I’m also going to discuss the actionable insights I can gain from the data collected using these traffic parameters.

Goals

Google Analytics (GA) allows me to set up 20 goals for my blog. As P.I. Reed (Lesson 6, para. 2) explains, a “goal is a Web site page that helps generate conversions for your site (with some extra code, they can even be file downloads or on-page actions).”

With blog objectives of thought leadership and interesting content, I’ve decided to set three goals:

Visit duration. My first goal focuses on boosting average visit duration from 3.08 to 3.5 minutes. The reason I’ve chosen this visit characterization metric is because it offers insight into how long my visitors are spending with my blog during each session. If I’m providing interesting and relevant content, I should be able to increase the amount of time my visitors spend with my blog. As of the time I posted this blog, I had no completions for this goal.

Page Views/Visits. My second goal is to increase the number of page views/visit from 2.61 to 3 or greater. This visit characterization metric allows me to see how many pages my visitors are viewing during each visit, which gives me an idea of how engaged they are with my site (P.I. Reed, 2013, Lesson 6). I’m particularly interested in this metric since my hope is that my visitors will visit more than one page, finding my content engaging and interesting. It will be interesting to see if I’m able to tie this goal to new versus returning visitors when analyzing my data next week. Again when I posted this blog, I had no completion information to share related to this goal.

Share/Social Connect. To boost visitors to my blog, I’ve selected share/social connect as another goal. This engagement metric allows me to see how many of my visitors find my content interesting and relevant enough to share, helping me determine if my objective to establish myself as a thought leader is working. Presently, I have achieved three goal completions as of the time I posted this blog, yielding a goal conversion rate, which is sum of the conversion rate for my three goals, of 7.14 percent.

It’s important to note that goals also allow you to set a dollar value for each conversion. While Google Analytics (2013) strongly suggests using this feature for all visitor interactions, I wasn’t sure what “values” to place on each of my three goals, given my overall blog objectives of thought leadership and relevant content. If you have suggestions on how I might assign a monetary value to my goals, or have read good articles about how to do this, please share.

Funnels

Funnels, according to GA (2013), will allow me to look at the paths my visitors take on their way to my conversion goals, which I’ve established as sharing social content, page views/visit and visit duration.

Funnels can provide very useful information. Since I have no information in my funnels reporting section at the present moment, I decided to speak with my employer’s digital media specialist, Brian Donohue, to get a better understanding of how funnels can be used by businesses.

Where I work, Donohue uses an e-commerce conversion funnel for the company’s individual dental product. The ultimate goal, he explains, is to realize a sale of the product. There are several steps involved in the conversion process – demographic information, comparing and selecting a plan, proceed to checkout, creating an account, and payment/enroll.

By setting up a funnel that follows a visitor through each part of this process, Donohue (2013) says he can look at three things:

• What steps in the company’s conversion process are giving customers the most trouble
• What copy/language might be contributing to the customer’s decision to continue or leave
• What technical issues might exist that make it difficult for the customer to complete the conversion

The funnel, he says, allows him to see how customers are interacting with the company’s various channels, such as social email and organic search, as well as help him optimize marketing efforts to increase conversions.

To further enhance my understanding of how funnels can help me measure the effectiveness of my blog (so when I have data available I can best interpret it), I viewed a useful video from Google (2011) that explained how funnels are a lot like a basketball game – it takes more than one player, or channel, to secure a goal, or conversion. And each part of a funnel helps provide the information needed to show how each player (or channel) is, or isn’t doing, its part in securing a goal (or conversion).

Filters

According to P.I. Reed (Lesson 6, 2013), filters can be applied to the information in my GA account, allowing me to manipulate the data to enhance accuracy of reporting. Specifically, GA (2013) allows me to set predefined or customized filters.

Predefined filters include the ability to exclude/include information from specific domains and an IP address, and to a particular subdirectory,(Google Analytics, 2013). Google Analytics (2013) also offers five customizable filter types: exclude, include, lowercase/uppercase, search and replace, and advanced. Each of these filter types performs a specific purpose as outlined below:

Since I presently am not using filters for my blog, I spoke with Donohue to find out how he uses filters. He (2013) explains one of the pre-defined filters he uses regularly is to exclude traffic from the company’s IP address. By using this predefined filter, he can rule out data from employees looking for information to use in their jobs that can skew effective measurement of goals and conversions. Last year, Donohue also set up two filters specifically  designed to collect information on mobile and tablet technologies. By using these filters, he was able to see how many visitors were using mobile phones or tablets to visit the company’s website and make the case for responsive design.

Donohue (2013) emphasizes that if you use filters, it is always wise to maintain a profile with unfiltered data because once the data has been processed you cannot go back to the raw information.

Conclusion

Based on the above information, goals and conversions are the reports that will provide me with the most actionable information from my blog – information that is crucial in helping me understand if my blog is reaching its objectives – thought leadership and relevant content. If I achieve my three goals, I can gleam information about what should be repeated or enhanced in the future. If I miss my goals, then I will have information about what might need fixed, changed, or enhanced to increase the effectiveness of my blog, moving forward.

As for filters, I might want to consider setting up filters that allow me to look at information for only those visitors who come to my blog via social media channels, or to exclude all visitors who come from my place of employment.

Over the next week, I’d appreciate your help is driving some traffic to my blog so I can better understand how all elements are working – or not working – in helping me reach my goals,  so please consider sharing via Facebook; emailing my blog to a friend; or tweeting about it. And if you have suggestions for other goals or filters I should set up, I’d love to hear from you.

References

Donohue, Brian. (2013). How to use funnels and filters. In-person interview on Nov. 27, 2013.

Google Analytics. (2013). Beth’s blog. Retrieved Nov. 29, 2013, from https://www.google.com/analytics/web/?hl=en#report/visitors-overview/a45647041w76369387p78959657/

Perley Isaac Reed School of Journalism, West Virginia University. (2013). Lesson 2: Web Metrics & SEO. Retrieved Oct. 28, 2013, from WVU eCampus Web site: http://ecampus.wvu.edu

YouTube. (2011). Multi-Chanel Funnels in Google Analytics. Retrieved Nov. 29, 2013, from http://www.youtube.com/watch?v=Cz4yHOKE5j8