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Second, we look at the types of information they need to analyze. We can deploy a hybrid strategy, which can include page tags, direct data calls from servers, web logs, application logs, etc., that they can use to streamline data to our server for analysis. We can capture a lot of information directly from the servers. This is more in line with the newer technologies, including streaming media, Ajax, Flash Flex, and other Web 2.0 technologies. Q: What is the future of web analytics Upcoming trends you see A: Companies want to see multiple technologies that orchestrate together as well as understand the overall business impact of these various technologies. They want better ways of measuring the business impacts and outcomes of these technologies with regards to target audience. That is coming. Q: What headway is Omniture making in predictive analytics and predictive modeling A: There are a variety of methods for doing that. One is having a dedicated engine that chews on the millions of transactions that a customer gets. It identifies needles in the haystack. One product we acquired was TouchClarity. Whether you are a first-time visitor to a website or a loyal returning visitor, the system knows information about you through your web browser. Things like your screen resolutions, your IP address, time zone, keywords, and referring sites all get passed in. This is used to determine the content that is served up to an individual. We have a machine learning language that we use to serve content based on real-time user behavior. It relies on prior experience from a large user base to determine the outcome. The machine s brain and content-serving system work together based on previous content consumption patterns. How would you like to walk into a store and see everything in that store set up exactly as you would like it The customer sees this as a relevant, engaging experience. It doesn t rely on personally identifiable information (PII). It s simply to improve the website experience on a per-visitor level so companies can up-sell and cross-sell in a nonintrusive way. Q: Are specific KPIs applied to this predictive modeling engine A: Yes, it depends on the industry. For example, a media customer of ours wants to know the repeat visitor frequency and the velocity of specific types of content when a visitor returns to the site. What content are they looking at and, second, how quickly is that content driving them deeper into the website. What are some natural pathing interpretations they might discern from that to go out and sell highly targeted advertising space to advertisers
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CHAPTER 3: Analytics
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A media company has very different objectives from a financial institution, which is very interested in converting people to an online application for a product. Another application is the use of self-service online banking. A customer-satisfaction survey can show how well customers are able to complete their tasks online without a need to pick up the phone to call the customer service center. We want to avoid phone calls because they are expensive for the bank. Q: Have you seen unexpected uses of analytics A: An interesting trend I am seeing is with our large automobile manufacturers and online clothiers recognizing the efforts they ve put into their back office solutions such as ERP, supply chain management, etc., have reached their optimization peak. We know that several large automobile manufacturers are using our technology as a leading indictor of demand. For example, people go to these sites and use the automobile configurator to select a make, model, color, different options, and enter in their ZIP codes. We are feeding that information back into the supply chain management systems to help manufacturers make much more informed decisions about the most popular cars and configurations they should be building and which markets to target. The purchase at a dealership is tied back into the system to understand the results of our sales modeling methods. This provides our customers with a new level of intelligence on how to better optimize their businesses. For clothing retailers such as the Gap, they can do a preemptive launch to see what people are interacting with and understand what is most popular before launching an entire Spring line on what they think will be hot. They can use this information in two ways. First, they create in-store kiosks and displays that accurately represent how people will interact with the products. Second, they can tell their manufacturers what to make and how many items to make. This can prevent an after-season fire sale. The online channel gives you a much more reliable gauge of what your customers are looking for than many traditional testing methods such as focus groups. Q: What are your top three tips for analytics A: First, go for executive adoption, not just executive sponsorship. Second, integrate your different marketing technologies with your web analytics to get a single version of the truth. Third, make incremental improvements on your business by focusing on what really matters vs. everything that you can focus on. Take a strategic approach to determine what your business should act on first. Once those things are performing well, add additional areas that can be optimized.
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