A Practitioner’s Guide to Web Analytics: Designed for the B-to-B Marketer

A Practitioner’s Guide to Web Analytics Designed for the B-to-B Marketer The University of Virginia, Darden School of Business Business to Business Marketing Reviewed by Professor Robert Spekman Written by Joshua Stein, Darden 2010 April 2, 2010 Research Summary Web Analytics has been gaining in popularity for years because it is a great source for B-to-B marketers to understand what customers are doing on their website and across the digital landscape. The complexity of Web 2.0 technologies combined with the sophistication of analytics vendors means that web analytics is more powerful than ever before, capable of unlocking great insights. This research paper is an overview of the most important aspects for a B-to-B marketer to know about web analytics. This research broadly covers the following topics; overview of web analytics, common marketing uses for web analytics, primer on the industry, progression of web analytics capabilities, key marketing decisions including selecting a vendor and an overview of the vendor landscape, budgeting for web analytics, and the common problems with and potential solutions for a B-to-B marketing looking to leverage the power of web analytics. For marketers planning to implement an analytics solution, they should read Avinash Kaushik’s book titled “Web Analytics 2.0.” Occasion for the Research Customers are spending more time on-line than ever before. While the vast amount of information on the web can often be overwhelming, finding the right information is incredibly useful. From a user perspective, it is critical to find what one needs as efficiently as possible. Therein lies the challenge for every website; customers are spending time on websites, but companies may not know how that is impacting their bottom line. Furthermore, more customers are using the web channel as a source of information. While sales channels may be different in a B-to-C context, buyers carry an expectation of a quality web experience from the personal lives (Webber, The New Competitive Priorities for B2B Web Sites, 2009). Most companies are currently spending lots of money on traditional forms of customer research and have likely already made large IT investments in their own website. Still, there remains a large opportunity to improve the customer experience on-line. In the B-to-B space, customers are spending lots of their time searching, consuming, and providing all sorts of information that can help companies gain insight into their behaviors and web usage patterns. It is no longer sufficient for IT professionals to make decisions that ultimately have a large impact on the customer experience; that responsibility now lies in hands of Marketing. Yet the question still remains: are companies using this information to drive towards their ultimate goal of increased sales through the web? Brief Description of the Terrain and Scope of the Research Web analytics has been growing in importance for years, largely driven by the “need to improve website usability and measure online marketing” CITATION Bri08 1033 (Walker, 2008). The significance of the web to B-to-B Marketers is two-fold; it is one of many channels through which to market to customers and it is a part of the sales funnel (i.e. customers can learn about, engage with, and buy products and services from a company’s website). This paper will address the latter by examining how web analytics is an important tool to use to improve a company’s website, which is an important sales channel and overall piece of the B-to-B marketing terrain. Web analytics is a way to monitor what customers are doing on-line in order to understand the decisions they are making so that the company can gain insight into why such decisions are being made. For example, web analytics can help gauge whether an updated product specifications guide is being reviewed and used by key end users. It can also help to gain insights into customer receptivity to different elements of a company’s webpage. Most importantly, web analytics can help companies understand how to better convert site visitors into sales. Now more than ever before, marketers can interact real-time with the customer and gain valuable information which provides a more complete and actionable picture of customer behavior, instead of waiting to gather this information from the sales force. “All of our marketing activity is structured to…drive prospects to our website. Web analytics helps us understand how to engage and re-engage the customer. We bring them into the website and start to build knowledge and nurture relationships. Companies need more efficient ways these days to accomplish their business objectives. The web is a very cost-effective way to do that, and analytics plays an important role in how well you can measure what it is you are doing” said Chris Ljungdahl, director of web and direct marketing at National Instruments (No Author, 2009). What is web analytics? Web analytics is simply an analytical tool to understand where customers come from on the web, what they are doing on a website, and where they go on the web when they leave. “From the first impression consumed on MSN.com, to the long and short tail search terms used in Google to research the proposition, all the way through to viewing the ‘thank you’ page at the end of a successful checkout process” (Wind-Mozley, 2008). “As a website develops it is vital to start using analytics, customer feedback and usability testing to fine-tune the site and ensure continual improvements are made,” said Harry Speller, web analytics manager at tourism body VisitBritain (Thomas, 2008). Perhaps the most valuable piece of analytics is to improve the operational efficiency of the site, moving potential customers as efficiently and effectively through the pipeline in order to increase desirable behaviors. Behind the scenes, through the use of cookies (privacy laws protect individual information), IP address identification, placing page tags onto each page on a website, login information into website customer profiles, and/or web server file logging, there is technology capable of tracking user web behavior at a general level or at a customer specific level. For example, it is possible to have the simplest form of aggregate data in order to make statements such as ‘The average customer spends 5.5 minutes on our website’ to more granular statements such as ‘segment X stops watching our online video, which explains how product Y works, half-way through.’ “We see an increased desire to analyze unique customer segments, not just broad segments but thin ones as well. People want analytics that allow them to easily define, isolate, and understand segment behaviors, and adjust site content and landing pages as appropriate” said De Young, Managing Director at a B-to-B SEO consulting company (Karpinski, 2009). The web channel is increasingly becoming more personalized, and as such web analytics plays an ever important role in allowing for micro sites, algorithm-based recommendations, and website customization (Walters, 2008). Common Marketing Uses for Web Analytics A/B and Multivariate Testing: This allows marketers to test multiple versions of a page to different users in order to find the optimal set-up. For example, one can test the format of the landing page with different versions, and through analytics decide on the optimal landing page which minimizes bounce rate and maximizes conversion. In fact, some vendors, such as Google’s product Website Optimizer, allow for many different combinations to be tested at once and will display the best combination of the various attributes tested. This is also helpful for merchandising in the cases where products or services are sold on-line. Pathway Analysis and Optimization: This displays the common navigational patterns trough a website, such that greater insight can be gleaned about how various user segments navigate a website’s content and where in the process users may get caught up. For example, given that customers can begin using a website by entering from various paths, such as a search engine, that they can spend their time navigating the website in different ways and consuming different information, and ultimately that they can leave the website having done a wide variety of activities, it is important to understand some of the common ways that customers navigate the website and consume its content in order to better optimize the site to fit customer needs. Lead Generation Identification: With various entry points to a website (going to the site directly, using a search engine, or clicking on an ad or reference from another website) it is important for the digital marketing strategy to use web analytics to optimize lead generation strategies based on how customers begin their on-line experience. Digital Marketing ROI / Campaign Tracking: This type of analysis helps determine the effectiveness of digital ad campaigns and marketing communications, with the ability to adjust such campaigns based on actual user behavior. Customer Segmentation: By identifying common patterns in web usage, combined with known attributes about the user from offline data, a more complete customer picture can be created. Campaign Message / Product Placement Optimization: With web analytics, the messages that worked and product placement criteria that led to sales are known. By trying different combinations of content and messages throughout various parts of the sales funnel, it allows web analytics to find the optimal messaging and product placement. Test Environment for Other Channels: With the ability to understand effective messaging and different A/B test combinations, after determining successful strategies on-line through web analytics this can feed other channels, such as direct mail and email. The Web Analytics Industry Forrester Research claims that by 2014 US businesses will spend $953M on web analytics software, which represents a 17.2% CAGR. However, this is lower than the 27% growth in overall digital marketing spending. Of all businesses, only 27% are not using web analytics in some capacity. The industry averages spend per business on web analytics at only about $15,000 (Lovett, US Web Analytics Forecast, 2008 to 2014, 2009). Within the industry, it is dominated primarily by Google, with 38% market share (Hossack, 2008). There are a bunch of other players who focus on fee based analytics services, such as Omniture and Coremetrics. Most of the consultants in the space provide services such as analysis, needs assessment, measurement, and reporting, while fewer offer platform based services (Burns, 2007). Web 1.0 to Web 2.0 and Beyond “Today, it’s ‘what does user behavior look like on my website?’ Tomorrow, it will be about matching behavioral data of on-line customers with off-line phone, call center, and mobile phone interactions,” said Jim Sterne, founding president of the Web Analytics Association (Karpinski, 2008). With Web 1.0 technologies and the first forms of web analytics, companies focused mostly on simple count metrics, such as visits and click through. For example, “…[previously] analytics tells you that the average person is spending three minutes on your site,” said Gary Lee, client services director with analytics company Red-eye (Hudson, 2008). However, the industry has progressed and companies began to ask for more from their analytics. “If you know that 20 percent of your audience is leaving in less than 30 seconds, then you can see you have a problem that needs to be solved.” Marketers began to ask harder questions that the early versions of web analytics were not capable of answering. “Web 1.0 typically measured an entrance to and exit from a web page. Web 2.0 analytics focus on user interaction – where do users click, hover, look, or interact?” (Karpinski, 2008) This is not only because web technology has changed, but also because users interact with a company across the digital landscape, and integrating this information has become more complex. The web is now moving from “world of Lego blocks-a page view approach-to a world of Play-Doh when you can mix applications like colors on a single page” (Bannan, 2008). The current world of web analytics is a lot more robust, and able to deliver real value to the marketing organization. For example, as Web 2.0 technologies such as video, social media, and flash have become mainstream across the web, web analytics has kept pace by being able to provide support for these new technologies. Marketers have also become much more sophisticated in their use of analytics, as simple counts no longer suffice. A common metric now is customer engagement . Forrester Research defines engagement as “the level of involvement, interaction, intimacy, and influence an individual has with a brand or company on-line over time” (Webber, How to Take B2B Relationships From Indifferent to Engaged, 2009). Another similar metric is stickiness, which measures how effective a website keeps visitors on-line (Sen, 2006). “People know not just that someone came to the page but how long they looked at something, when a new pop-up is chosen [and] in what sequence choices are selected,” said Eric Hansen, president of Website optimization provider SiteSpect (Bannan, 2008). While the metrics and technology have developed, so too have the capabilities of web analytics vendors. For example, some are now capable of providing services for automatic site optimization, customer segment profiles, and marketing campaign ROI. In a world moving towards more personalization of the web channel to different customer segments, each user could be bucketed into a few different segments, which web analytics vendors can help with. For example, there are those visiting a website before a sale to be informed, those visiting a website to be converted to a sale, and those visiting a website for post-sales support (Webber, The New Competitive Priorities for B2B Web Sites, 2009). Each of these segments has different needs, thus leveraging web analytics to identify and pinpoint specific users into specific segments helps to measure and improve the experience for each segment independently. While this hits on a broader point of improving the overall web experience, web analytics helps by being able to get more specific information the Marketer, which helps to properly bucket the end user into segments. Analytics is not too far away from being able to automatically, not manually, customize landing pages based on specific customer segments and preferences. This will allow for a very personalized and unique web experience. Another capability which has already started to develop is linking web usage behavior into CRM systems, bringing together both on- and offline customer data to provide a full picture of customer behavior. In the B-to-B setting, this provides valuable information to sales reps about how customers interact with the web channel. Given that a B-to-B customer may have interactions with multiple channels, it is important to have a holistic picture of customer interactions with a company in order to serve their needs better. For example, if a sales person already knows what information a particular customer has downloaded from the website, then they are better prepared to have a much more specific conversation with that customer. Key Marketing Decisions Areas Marketers have three major decisions they can make with regard to web analytics. ,[object Object]

Marketers must decide the vendor to work with who will run the web analytics. The vendor landscape is diverse, and there are distinct differences between vendors. An overview of some of these key differences is provided in Exhibit 1.

Marketers must decide the amount of internal resources to dedicate towards web analytics. Resourcing depends a lot on the current internal capabilities, but with any larger organization it is imperative that at least one person is dedicated to web analytics. Internal resources account for about 90% of the web analytics costs, while only 10% will come from the analytics tool and service vendor (Kaushik, 2010). The internal resource’s responsibilities could include running reports, looking at the data for insights, and building new analytical capabilities. It is likely that web analytics sits within the digital marketing team, as this is the analytical engine for the entire digital channel. Selecting a Vendor While the vendor landscape can seem diverse at first, there are only a few major players in this space. Since it becomes difficult to change vendors once data has been collected and reports have already been set-up, companies should view this as a long-term decision given the amount of work required and data lost if required to switch vendors. Capabilities will build from the analytics over time, further integrating the organization with that vendor. When choosing between the different analytics providers, a few criteria to consider are listed below. ,[object Object]

Whether this vendor should be able to provide a complete digital marketing solution (i.e. SEM, SEO, e-mail, social, …) or simply help with the web analytics

The need to analyze Web 2.0 technologies; mobile, social, video, and Flash

The kind of data received and the need for customization with data manipulation

Individual vs. aggregated customer data impacts the granularity of analysis

Real-time data vs. time-lag data

The need for historical data storage

Ability to export data to customer servers

The desire to have vendor customer support services

The need for sophisticated web analytics services, ranging from reporting to analysis:

Reporting: basic or highly customized data reporting

Analysis: web page optimization (A/B testing), digital marketing campaign management and ROI tracking, pathway analysis and optimization, conversion funnel analysis, customer segmentation analysis, integration with offline channel data into CRM systems

The level of internal IT sophistication at the customerThe needs across the above criteria for assessing vendors can be aggregated into four main types of web analytics buyers. These segments are listed below in descending order from least complex to most complex (Walker, 2008). ,[object Object]

Buyer needs product and campaign specific analytics

Buyer needs customized analytics capable of performing complex analysis

A Practitioner’s Guide to Web Analytics: Designed for the B-to-B Marketer

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