The Top Ten Nastiest Problems to Solve

With representation from enterprises, vendors, consulting groups, and analyst firms, Jim put the attendees to work by asking them what they thought were the Top Ten Nastiest Web Analytics Problems.  The audience quickly blew past the 10 limitation and came up with almost 40.  However, they clustered into a smaller number of issues:

1. Site Complexity -- Site and product complexity; site segmentation; usability and accessibility analysis; privacy; benchmarking
2. Technology -- People expect expect answers but just get a tool; need multiple tools; difficult implementation and setup; complexity of delivery of analytics reports; non-traditional browsers
3. Resources -- Not enough humans, etc./resources; have tools but no analyst; attributing value to the Web (allocating budget); cost of visitor support
4. Politics -- Inaction; internal politics; lack of executive education and sponsorship; no Chief Web Officer (no coordination); from reactive to proactive; dependence on IT to get things done; "more is better"
5. Metrics -- Identifying TCO and getting surprised; using metrics for strategy optimization; clear links between strategy, objectives, and tactics to metrics; identifying KPIs; KPIs are hard to record; getting rid of legacy metrics; measuring value of content; how to score leads
6. Data Integrity and Quality -- data collection integrity and consistency; inconsistent tools and processes and numbers; cross domain analysis (single view of the customer); onsite to offline data and lead gen and back; timely access to data; relevant data to the right people; expectations of accuracy; data overload; integrating data (e.g., clickstream and surveys); people are deleting or not accepting cookies

Stories from the Front Lines

Throughout the conference, enterprises talked about their Web analytics strategies and processes:

Amazon.com, one of the few Internet success stories, is now a Fortune 500 company and has over 41 million active customer accounts.  Ever mindful of the corporate goals of low prices, convenience, and a wide selection of merchandise, the company continually monitors and improves its six Web sites.  For example, the company has set per minute site revenue goals, and rings automatically rings pagers to pull personnel out of meetings if those bounds are violated.  The Data Mining and Personalization Group helps the company decide on site changes largely through the use of A/B tests.  By randomly showing alternative treatments (e.g., a new home page design, different feature locations) to visitors, the group is able to discern whether the change is statistically for the better.  It does not require a large percentage improvement to have a decisive bottom line impact:  for example, if Amazon.com is able to improve shopping cart conversion by 1%, it gains additional revenues of $50 million.  On any given day, Amazon.com will be running four or five tests simultaneously.

The Web analytics group at Avaya, a provider of communications systems with offices in 50 countries and fielding 800+ Web sites, described how it consciously morphed itself from a Web analytics group to a Web optimization group.  By shifting the emphasis from "analyze" to "optimize," the group made its work more action-oriented and was better able to explain its value to the corporation at large, thereby gaining senior management buy-in and increased usage of Web metrics.

Carat Interactive, a large interactive advertising agency, described several client engagements where the following were key:  (1) clarifying the appropriate metrics to develop and track, (2) segmenting customers as a way to optimize the site for high-spending customers, and (3) taking a phased approach.

Hewlett-Packard, maintaining 1,500 Web sites and receiving 30 million unique visitors a month, discussed its Web analytics philosophy and infrastructure.  Confronted with legacy systems and processes (the result of DEC being bought by Compaq and then Compaq being bought by HP), the Web analytics group has concentrated on deploying common metrics and analytics tools worldwide.  Clickstream, survey, order, 800 call data, media, and firmographic data is all consolidated in a data warehouse, which then serves as a data source for dashboards, standardized reports, ad hoc reports, and predictive modeling for the business.

InterContinental Hotels Group offers 530,000 hotel rooms through its Crowne Plaza, Holiday Inn, and InterContinental brands.  The company, generating 10% of its room revenue from the Internet via 25,000 online bookings a day, utilizes a central analytics group to help the business understand Web site visitor behavior.  This 23-person group leverages a wide variety of tools -- clickstream analysis, online surveys, usability testing, and competitive intelligence -- to ascertain how to best optimize the site to meet visitors' goals.  One example of a customer-driven change was InterContinental's realization that visitors wanted to be able to see hotel rates at a glance when shown a list of hotels within a specific geographic area, rather than have to click on each individual hotel entry to get pricing.

SAP, the third largest independent software supplier with revenues of 7 billion Euros, manages 55 country sites and maintains 75,000+ Web pages.  With business goals such as branding, education, lead generation, and sales improvement, SAP asks questions such as, "What content drives or influences conversion?", "How do customer segments differ?", "What is the health of our lead qualification process?", and "What attributes describe our best customers?"  In the course of answering these questions, the company discovered that no one tool can do it all, using Clickstream Technologies for clickstream data collection and analysis, SAP Business Warehouse for data management, mySAP CRM for lead management, VBIS for visual interpretation of traffic, and WebEx as a way to share best practices and intelligence.

SmartDraw.com, an online provider of business graphics software, uses four systems to help it understand Web visitor behavior:  (1) log file analysis to monitor software downloads, (2) an in-house developed system for tracking marketing expenses and experiments, (3) Urchin for general traffic metrics, and (4) ClickTracks for page navigation analysis.  continued...

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