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May 9, 2002

Over the Wall

You need your Web analytics to be scalable; how can you be sure they'll grow enough?

By Richard Winter

Web analytics has delivered enormous business value in practice and has even greater promise as it and related technologies mature. Web analytics is the process of inferring the answers to important business questions from the behavior of visitors to a Web site — and delivering the results in a time frame and form that enables valuable business actions.

Without Web analytics, all visitors to a Web site are treated pretty much the same: Without detailed knowledge of who visitors are, what they want, and how they tend to buy, there isn't much opportunity to personalize the customers' experience. That's true whether the customers are visiting the Web site, the call center, the store, or any other channel. (See the sidebar, "Web Analytics: A Multichannel Strategy," below right.)

But there's a problem: Web activity for many companies generates too much of a good thing. That is, successful Web sites produce such enormous clickstreams that their managers soon encounter the brick wall of insufficient scalability. After making a big investment in CRM, many companies can lose it all when they outgrow their analytic capability or otherwise simply can't get to useful business results.

Executive Summary

Richard Winter

The value of Web analytics has been proven in cases where it was well executed. Part of good execution means ensuring the solution can keep pace with rapidly expanding volumes of data. Here's how to evaluate products so that your solution will still bring you value at least three years down the line.

Web Analytics: A MultiChannel Strategy

A Story About Educational Financing

A financial services company introduced a new product to help finance the education of children expected to attend college for five or more years in the future. The product had attractive investment potential and tax treatment and was expected to sell briskly. The product manager began the campaign with a tried-and-true approach to promotion, targeting 5 percent of the firm's customers who had children and had purchased long-term investment products in the past.

The Route to Business Value

Before looking into scalability, let's first define what you need in a product for clickstream analysis. The type of Web analysis product that actually helps executives make business decisions is one that's all of the following:

Complete. You need a solution to your entire Web analysis problem: data extraction, extensive preprocessing, integration, loading, aggregation, analysis, and reporting.
Results-oriented. You need a solution that ultimately will answer your critical business questions; one that's planned from the ground up to deliver insights into key business questions, rather than just count page hits.
Timely. Answers are based on sufficiently fresh data. The knowledge has to come quickly after the behavior is exhibited. Only then can you get the powerful, positive feedback loop that results in effective action.
Flexible. The solution has to be adaptable to accommodate change, because opportunities come and go, customer appetites and market conditions change, Web sites are fluid, and most of the profits go to those who time their moves well.
Scalable. And, of course, the solution must obey the golden rule of modern commerce: Don't run out of headroom.

Scalable Web Analytics

But what really is scalability in Web analytics? In Web analytics, scalability means all of the following:

The entire solution grows as your business grows. You need to get all the way from 100 million page hits a day to meaningful insights about your business and your customers, as shown in Figure 1. These stages include:

Data gathering
Preprocessing and integration
Storage and aggregation
Analysis
Query and reporting
Action.

The ability to answer the hard (analytical) questions grows. Your solution needs to handle increasingly larger and more complex demands for data access and data analysis as your program progresses.

Handling growth in both database size and workload. The growth rate of both database size and workload tends to be rapid and more than linear, as shown in Figure 2.

Performance remains satisfactory. A scalable solution for Web analytics will continue to deliver satisfactory performance, even as the difficulty of queries, the number of queries, the number of users, and the size of the database continue to increase.

Throughput continues to meet requirements. For example, there may be a requirement to incorporate a day's worth of Web site activity into the database in four hours. In a scalable solution, throughput requirements will continue to be met, even as Web site activity, business focus, data volumes, and analytical activity grow, as illustrated in Table 1. In fact, as Table 1 shows, this combination of circumstances often causes the processing window to shrink, which induces tremendous pressure on the architecture's scalability.

Price/performance remains stable. Price/performance is the cost of a system per unit of work. A scalable solution for Web analytics will ideally exhibit stable price/performance as the system grows.

The system never becomes unmanageable. Manageability refers to the ease with which you can perform the routine day-to-day and week-to-week tasks associated with operating the system, monitoring its performance and availability, and so on.

What to Do

If you think you may need a solution — or a better solution than you have — for Web analytics, here's what I recommend:

Start with your business case and needs. Then define your requirements quantitatively. Next, define quantitatively how your requirements are likely to grow. Only then are you ready to ask your prospective suppliers probing questions about performance and scalability.

Be sure to ask the following questions in terms of your most demanding likely requirements two to three years after implementation. Ask how the vendor's proposed solution will:

Handle capacity requirements over time. What is the maximum capacity of the database that the analytics engine can handle?
Manage capacity requirements over time. What capacity management capabilities are inherent in the product? Can they be tailored to fit your analysis requirements? For example, do they have the flexibility to age out different types of data? Can those parameters be changed?
Allow you to determine space and hardware requirements for the Web analytics environment. Can the vendor forecast those needs over a two- to three-year time period?
Handle varied data resources for analysis. Does the data-import framework support multiple formats including log files, network sniffers, page dots or tags, and Web server plug-ins, including Netscape Application Programming Interface (better known as NSAPI) modules? Does it match your operational requirements?
Allow sampling of data based on the notion of a "user" that's defined by a given request rather than a sample that is just a percentage of the overall data stream.
Get your data into the database, including indexes and aggregates, on time.
Produce the standard reports, including the metrics you need to run your business, on time.
Respond to your typical queries in seconds.
Ensure that your data will be available when you need it, even in the presence of disk failures and human errors.

Once you've selected your vendor, insist on proof of performance and scalability sufficient to meet your needs. To have reasonable assurance that your requirements will be met, you need more than good answers. You need proof: You want references from companies that are doing today what you need to do in two to three years. If at least five such references, including some in your industry, aren't available, you must do a full-scale proof-of concept or competitive benchmark.