E Commerce Analytics Demandware

©2010 Demandware, Inc. | www.demandware.com

eCommerce AnalyticsPutting Web Analytics to Work for Your eCommerce Business

Retail Practice Best Practices Guide

http://www.demandware.com


Executive Overview

As ecommerce becomes an increas-ingly important part of a retailer’s overall business strategy, it is critical to have a plan in place to measure, track and monitor your shopping website performance. This will enable you to understand your customers better, do more to personalize their shopping experience, identify opportunities for improvement and make sure you are doing everything you can to enhance conversion rates and improve online revenues.

Web analytics, specifically ecommerce analytics, help achieve this goal by transforming business data into action-able insights. This paper is targeted at growing ecommerce businesses (either independent or part of a larger retail

organization) that want to establish a more mature analytics practice within their organization.

The ideas and best practices outlined are not difficult or expensive to imple-ment and offer significant benefits. They are ideally suited for the Online Marketing Manager, who may be constrained by time and budget to al-locate adequate resources to establish a robust analytics practice. They also give you a head start by guiding you through the business and functional aspects of ecommerce analytics. Deep technical knowledge is not required, although a high-level understanding of the various technology components involved in an ecommerce site will be useful.

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To lay the foundation for some of the best practices detailed here, let’s take a quick look at some of the basic technologies that enable ecommerce analytics.

Javascript tagging is perhaps the most popular data collection mechanism used in web analytics. It’s as simple as pasting a small snippet of Javascript code in all your website pages. It then works as follows:

1. The customer enters the URL of your website.

2. As the web page loads, the browser executes the Javascript code, capturing the page view and other details about the visitor’s session, and sending it to a data collection server (usually maintained by your analytics vendor).

3. As the visitor navigates from page to page, the Javascript snippet captures data specific to the page and the overall session and sends it back to the data collection server.

4. The data collection server associates all data received from the customer during the browser session with a unique ID (called Session ID).

5. The session gets terminated when the visitor either closes the page, navigates to a different site, or there is no browser activity for a certain period of time (usually 30 minutes). It is important to understand the concept of cookies to complete this

technical primer. A “Cookie” is defined as: “A message given to a web brows-er by a web server. The browser stores the message in a text file. The message is then sent back to the server each time the browser requests a page from the server.” (Web Analytics Association)

Typically, there are two types of cookies set by any web server:

Transient Cookies exist only as long as the visitor is interacting with the website. They get deleted automatically when the session ends, i.e. – the user closes the browser or navigates to a different website. These are usually used to track events hap-pening within a single session and to map them together.

Persistent Cookies continue to live even after the session has ended. These are used to track repeat visitor behavior across sessions. These usu-ally have a pre-determined expiration date, ranging anywhere from 30 days to six months. There are some common concerns with cookies and Javascript-tagging that are important to be aware of as you consider ecommerce analytics.

• First-Party vs. Third-Party Cookies – Most popular vendors support first-party cookies, but if your vendor uses third-party cookies, your analytics code may get blocked by security settings and anti-spyware software running on your customers’ computers.

eCommerce Analytics – A Quick Technical Primer

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Useful Tools Google Insights (www.google.com/ insights/search/#)

Google Insights (or its relatively simpler peer – Google Trends) can provide insights into how favorably Google views your competitor’s site versus yours. You can also see how your keywords are trending versus your competition. While Trends is a simpler tool, Insights allows you to save your findings in a .csv format and export into a spread-sheet for further slicing and dicing of data.


http://www.google.com/insights/search/#

http://www.google.com/insights/search/#


• Disabled for Javascript – It is safe to assume that anywhere between 2-4% of your visitors have turned off Javascript in their browser. Depending on your vendor, you may still be able to tell how many such visitors arrived at your site in a given time frame. Gener-ally though, these visitors remain invis-ible to you.

• Too much Javascript – On the other end of the spectrum, if your site is too heavy on Javascript (think modal windows, overlays and non-flash visual effects), the analytics snippet may conflict with other libraries on your pages and throw Javascript errors on the page, causing a poor browsing experience.

• Data ownership – Since your data may be sitting on a server maintained by your analytics vendor, it is possible that you may not get access to all the data in its raw form to run your own analysis. It may be possible to get some data exported, but only at aggregate levels.

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In the beginning, it may be difficult to decide what to tag with Javascript and what not to. You may be tempted to adopt a “tag everything you can see” approach and leave for later the process of deciding what you want to understand about your site. Avoid this mistake if you can. It is important that

you start by making a list of what you want to understand about the visitors and their experience with your web-site. The screenshots below represent some of the basic events and/or visitor touchpoints that should be tagged to get some actionable data out of your system.

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Deciding What to Track

Home Page 1. Home Page Load

3. Category Menu Click

2. Search Button Click

The table here provides a quick summary of the screens that follow:

# Page Events/Actions

1 Home Page Page View or Home Page Load

2 Home Page Search Button click

3 Home Page Category Menu click

4 Category Page Item/Product click

5 Category Page Sub-Category Menu Option click

6 Product Detail Page Add-to-Cart click

7 Cart View Page Start Checkout click

8 Cart View Page Cross-Sell Item click

9 Cart View Page Alternative Payment Methods click

10 Shipping Information Page Continue to Next Step click

11 Billing Information Page Continue to Next Step click

12 Order Review Page Submit Order click


©2010 Demandware, Inc. | www.demandware.com 6

Category Page

5. Sub-Category Menu Click

4. Item/Product Click

Product Detail Page

6. Add-to-Cart Click



Cart View Page

Shipping Information Page

9. Alternative Payment Methods Click

7. Start Checkout Click

8. Cross-Sell Item Click

10. Continue to Next Step Click



Billing Information Page

Order Review Page

11. Continue to Next Step Click

12. Submit Order Click



Standard analytics tools provide a laundry list of metrics that can be tracked. If you are just starting out with ecommerce analytics, then it is critical to distill this list down to the most important ones – i.e., true “Key” Performance Indicators (KPIs). Below is a starter list of essential KPIs that you should track for your ecommerce site. Look to build on this list as your internal practice evolves and as you understand your site and your customers better. The KPIs are split into three differ-ent categories – Acquire, Engage and Convert. Each category provides unique insights into the function and effectiveness of your site in reaching its business goals.

Acquire – Metrics that help measure site traffic and its quality

Engage – Metrics that help understand how visitors are interacting with the site once they are on it

Convert – Metrics that help track the ROI for the site from various perspectives

Acquire1. Visits – This metric may also be referred to as Visitors or Total Visitors, depending on what analytics tool you are using. Visits measure how many times people visit the website during a given time frame. Technically speak-ing, this is the total count of browser sessions for a given time period.

2. Unique Visitors – As the name suggests, this metric identifies the

number of unique visitors to the website during a time period. The key difference between Visitors and Unique Visitors is the former is a count of number of times people visited the website, while the later is the count of number of people who visited the site.

3. Referrers – While it is good to know how many visitors are coming to your site, it is equally important to know where they are coming from so that you can focus your marketing dollars effectively. There are two good sources of referral information – referring web-sites and key search phrases used by visitors referred from search engines. This information tells you where the visitors came from, and what they were looking for. Engage4. Page Views – A page view is sometimes also referred to as depth of visit. It measures the number of pages viewed on the website during a visitor session. This can also be used as a proxy for customer engagement; i.e., if a visitor is viewing more pages on the website, then the content is probably more engaging to them. It is important to understand that if you are running a Flash or Ajax heavy site, no matter how deep those user experiences are, they will get reported as one page view (per session).

5. Time on Site – The most frequent use of time on site is to measure en-gagement. The general assumption being that if the website is more engaging to the customer, then they should be staying on the site for a longer time period. Not all analytics

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8 Metrics You Should Always Track

Useful Tools

Google Alerts (www.google.com/alerts)

Google Alerts sends frequent email updates of the latest Google search results based on your choice of keyword query or topic. You can use this to monitor the industry, a specific competitor, and even your own company and website.


http://www.google.com/alerts


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tools provide this metric out-of-the-box and you may need an analytics professional’s assistance in setting up this metric in your reports.

6. Bounce Rate – This measures the percent of traffic that saw just one page on your site and left. This is a great way to measure the quality of traffic arriving on your site. While a 0% bounce rate will be an unrealistic expectation, you should benchmark against your industry vertical.

Convert7. Orders/Revenue – Most analytics tools provide the ability to track orders placed online and the related revenue generated, out of the box.

8. Visitor Conversion Rate – For our purposes, visitor conversion is defined here as the percent of visitors who completed a transaction (order, return, exchange) on your website; - i.e. Total Transactions divided by Total Visitors for a given time period. eCommerce sites are measured, for the most part, by their ability to generate revenue and sales. This is a direct measure of busi-ness outcome. Be sure to know your industry’s average conversion rate and compare against it to benchmark your site’s performance with your competi-tion.



With the technical primer and key metrics as background, let’s look at some best practices that you can put to work right away to better under-stand your customers, improve their shopping experience and increase conversion rates.

1. Don’t track analytics in real time.It may be tempting to place a test order on the site and immediately log in to your analytics tool to track that order, but unfortunately, most analytics tools don’t work that way. If you are using a service that is running inter-nally in your data center, that might be a realistic expectation. If you are using an analytics vendor that is making the tool available via software as a service (SaaS), it may take anywhere between 2-6 hours for your order to become visible in the various reports. And that’s okay. Real-time analytics is only useful if you are trying to debug a set of events taking place within a specific session; but then, analytics tools are not meant to be used for debugging anyway.

2. Leverage benchmarking to gain effective insights.Benchmarking is important to be able to glean effective insights from your site data. Without actionable insights, data isn’t really worth much. Bench-marking against industry vertical averages and competitive sites allows you to look at your performance from a different perspective. The best part is that you are not making judgments based on just your own data! You will be able to look at your data in a neutral context, which is usually more conducive to better decision making,

especially with others in your orga-nization. Tools like Compete.com or Coremetrics’ Quarterly Benchmark Re-ports can be very useful in benchmark-ing your metrics with others in your industry. These tools also give you the opportunity to explore other metrics that your peers may be tracking. 3. Don’t try matching numbers from different analytics tools.At Demandware, we often see cus-tomers using Google Analytics or a similar free tool to get started with their analytics practice, and then upgrading to a paid tool as their needs evolve. They often upgrade to the new tool without letting go of the original one. This can create confusion - with more than one analytics/reporting tool being available to the team and data from one tool being compared with data from the other. The data from two different tools seldom match and can lead a team down an endless loop of debugging issues that may not exist in the first place. Different analytics tools function differently behind the scenes, and it is normal to see a 2-3% variance in the metrics reported in these tools. If the variance were to reach double figures and if they were to trend in dif-ferent directions at different times, then it is a cause for concern as it would indicate that one of your tools may not be functioning correctly.

4. Don’t stop at metrics. Include insights.Most dashboards are a collection of numbers and graphs. It’s up to the practitioner to interpret what the data means. Including a section for insights in your ecommerce analytics report

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Do’s and Don’ts of eCommerce Analytics

Useful Tools Compete (www.compete.com)

The free version of this tool allows you to com-pare basic profile data of up to three websites. Site profiles include Unique Visitors, Visits, Page Views and Compete’s Internal Rankings for these sites. Before you start querying your competitors’ sites, it is important to understand how the data is provided. The service leverages a sample of over two mil-lion Internet users. These users have granted Com-pete.com permission to analyze the web pages they visit and ask them questions via surveys.


http://www.compete.com


allows the intelligence from the ana-lyst to percolate at the highest levels and helps executives and colleagues understand it better. If possible, also include a section for recommended actions. This keeps readers from focusing on poking holes in your analysis and puts more emphasis on making decisions and taking action.

5. Limit your report to one-page.With all the out-of-the-box reporting capabilities available in analytics tools, it’s tempting to include all the possible data points in your report. This dilutes the focus of the reviewers and deci-sion-makers and makes if more dif-ficult for them to focus on action items. Building a report that can be printed on one standard letter size page in a readable font size forces rigor in selecting KPIs and focuses your organization’s attention accordingly. 6. Assign an owner for every metric. Every metric in your report should have a clear owner in your organization. This ensures that action gets taken where necessary. Additionally, when you are reviewing your KPIs in a meeting, it will be clear who is responsible for resolv-ing specific issues, speeding decision making and action.

7. Treat analytics as “work-in- progress.”Web analytics relies on a collection of imperfect systems to collect, ana-lyze and report data. These systems include Javascript tags, cookies, new technologies that don’t get detected by existing analytics systems, etc. The result is a data set that is not perfect. In most cases, we need to rely on our judgment and experience to make decisions from this imperfect data. Get comfortable with a certain level of imperfection and move on with your decision making.

8. Segment!Reporting by numbers on their own is generally not very useful. Sometimes even reporting by trends doesn’t give us the entire context we need to gain the kind of insights that will drive good decision making. Let’s consider a simple example. A typical web report-ing metric is visitors to your site. Let’s say there were 100,000 visitors to your site last month. Do you know if that is good or bad? Now, if we trend this against the same month last year, and we find that the visitor count this year has decreased, does that give us sufficient insight to make actionable decisions? And, if we were to seg-ment the visitor traffic by referring sites and search keywords, and trend each segment with the same month last year, chances are you will see which source(s) is/are trending differently. This may indicate where you want to focus your acquisition dollars for next month. In most cases, the more you can segment the data, the more you can learn.

9. Don’t forget seasonality.Identify metrics that are affected by seasonality and factor that into your analysis. One way to ensure this is visible to the decision makers is to go a bit beyond the traditional calendar ranges. Do things like a 13-month trend, or look at 5 quarters or 8 days.

10. Include qualitative data in your analysis.Sometimes ecommerce organizations get stuck in clickstream analysis and don’t take the time to consider why customers do the things they do. There are various tools and techniques that can be used to analyze custom-ers’ online experience, including usability testing, customer satisfaction surveys and A/B testing. Try them out and you may be surprised at what you can learn.



Reporting Templates to Get Started

It’s not only what data you present, but also how you present it. Below we have provided a couple of simple templates that you can use to build your own unique ecommerce analytics reports. The first template represents a dashboard approach that a decision-maker would review. These do not

include space for the data that would need to be queried to create these charts. The second template is an example that an analyst might use to derive his or her daily observations.

Template 1



Template 2



About Demandware AnalyticsDemandware offers robust analytical tools that enable you to capture and interpret relevant information for your ecommerce business. Demandware uses web logs for analytics because it’s faster than pulling data from the database. The web logs represent all storefront web activities, for example, orders entered by consumers. They do not represent activities like order cancellations, order modifications and returns performed off-line by the merchant.

Key Differences• Since Demandware analytics servers reside within Demandware’s infrastructure, access to the web log files is always available (to the applica-tion, not to the business user). With a 3rd-party tool, the data would reside outside of your control and within the tool vendor’s infrastructure.

• Since it is not dependent on Javascript, Demandware’s analytics will work even on browsers where Javascript is turned off.

• Javascript can detect client-side metrics such as screen size, resolu-tion, bandwidth, etc., which a log based analytics tools may not be able to detect.

• Web log data can become unreli-able with high levels of page caching in the infrastructure. Pages served through an intermediate caching server and not through the primary web server may not get reflected correctly in the web server’s log files.

• While log-based analytics tools identify visitors using session IDs, Javascript based tools do the same using cookies. The inherent differences in these two approaches will ensure that there is always a difference in this metric between the two tools.

• With web-log based tools, your pages do not need to be “tagged” for analytics, but with Javascript-based tools, if you miss tagging a page, then it won’t be tracked.

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Difference Between Third-Party and Demandware Analytics

Additional resources to learn more about web analytics for ecommerce:

• Web Analytics Association (www.webanalyticsassociation.org)

• Occam’s Razor – Blog by Avinash Kaushik (www.kaushik.net/avinash)

• Kaizen Analytics (www.kaizen-analytics.com)


http://www.webanalyticsassociation.org

http://www.kaushik.net/avinash

http://www.kaizenanalytics.com


If you don’t have an internal analytics practice, then the insights and best practices outlined in this paper can help you start one. If you have an analytics practice or process within your organization or team, then you may want to analyze and prioritize your focus based on the ideas described here. What best practices are most important to your businesses success? What metrics concern you and your organization? Are you sure you are focusing on the KPIs that have the most impact on your business?

Demandware’s Retail Practice group has put these best practices into ac-tion for many of the world’s leading online retailers and consumer brands. We’re here to help you in any way we can. Contact your Client Relationship Manager to get started on putting these ideas to work for you and refin-ing your current ecommerce analytics practices to align them more closely with your business success.

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Putting eCommerce Analytics to Work for You

• Share this White Paper with your colleagues.• Evaluate your current ecommerce analytics practices against these best practices.• Identify the most important areas for improvement.• Plan and execute.• Contact Demandware if you need more information.

Vinod Kumar is a Solution Strategist at Demandware with primary focus on business analysis and web analytics. He is responsible for supporting clients and helping them grow their online business by leveraging consultative advice and service offerings to adopt best practices.

Prior to Demandware, Vinod managed Customer Success programs for multiple software vendors and worked with leading online brands such as Urbanoutfitters.com, Anthropologie.com,

Borders.com, CharlotteRusse.com and UnderAr-mour.com. His responsibilities included managing all aspects of the customer relationship and being the customer’s voice within the software vendor organiza-tion. Vinod has also worked with leading technology vendors like Sun Microsystems implementing their solutions at global companies like Vodafone.

Vinod has a Bachelor of Science in Computer Science and an MBA in International Business.

About the Author

Action Plan for Improving Your eCommerce Analytics



About Demandware, Inc.The trusted, global leader in on-demand ecommerce, Demandware revolutionizes how businesses deliver customized shopping experiences to consumers in the digital world. Only Demandware combines the on-demand ecommerce platform rated #1 by industry analysts, an open ecosystem of partners that extend the value of the platform, and measurable commitment by its employees to enabling client revenue growth. Demandware continually sets industry standards for market innovation and client satisfaction. Demandware clients include industry leaders such as Bare Escentuals, Barneys New York, Columbia Sportswear, Crocs, Frederick’s of Hollywood, Hanover Direct, Jones Apparel Group, Lifetime Brands, Michaels Stores, Pana-sonic, Playmobil and Reitmans.

The Retail Practice team at Demandware is dedicated to helping clients grow their online revenue. Retail Practice has three key areas of focus: revenue growth, retailer advocacy and industry thought leadership. The team consists of ecommerce industry experts across many different verticals with more than 100 years combined experience. Retail Practice members are product specialists skilled in the features/functionality of the Demandware application and know how best to optimize for revenue growth. The group’s expertise also extends to defining end-to-end solutions which includes merchandising, marketing (acquisition and retention) and design. Retail Practice team members are champions for the long-term value each client represents to Demandware, and act as the conduit in and between Demandware clients and the community.

© 2010 Demandware, Inc.


E Commerce Analytics Demandware

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