The next step in Web analytics
Move beyond page views to really understand your most valuable Web visitors
As most people know, every click you make online can leave a virtual footprint. Those footprints are of great interest to marketers who want to know who you are, what you’re interested in and where you’re going on their Web site. SAS’ newest customer intelligence offering, SAS® for Customer Experience Analytics, helps marketers trace those footprints to learn about their customers and better leverage the Web channel.
Let me use an analogy to further elaborate. If you’re at the beach, you can see many sets of footprints along the shoreline. If so inclined, you could focus on a single set of footprints and follow them to the point at which they leave the beach, giving you a clue as to their destination. If they lead to the pool area of a resort, you could speculate that they were made by a guest of that hotel. If you were really curious, you could backtrack to see where those same prints originated. If they started at the public parking lot, you might deduce that they belong not to a resort guest, but someone loitering poolside.
This admittedly simple analogy illustrates how many organizations still rely on a common Web metric called a “page view.” This metric tracks when and how each Web page is accessed in order to determine how effective their Web site is at meeting the needs of their customers. Unfortunately, they’re missing the bigger picture.
If each footprint on the beach is a page view, the beach is a Web server. The page views stored on the Web server are pieces of a massive footprint puzzle which, when reconstructed, can help determine how customers interact with a Web site. While page views are a good indicator of popularity, they don’t convey other attributes that are important, especially to marketers. While it’s nice for the marketer to know he had 10,000 page views on the beachfront-room page, for instance, it’s even more useful for him to understand the 75 customers within those 10,000 page views who are frequent guests of the hotel chain.
A page view can tell you the area a person is interested in on your site, but it doesn’t tell you anything else. You don’t know anything about the person’s value to the organization as a customer. Is he a loyal customer? What are his personal preferences and attributes?
Organizations are marketing and selling to people, not page views. Consequently, marketers are increasingly looking to bring in the human component so that Web analysis is more meaningful.
To really create customer insights from Web data, a marketer must:
1. Capture all interactions occurring within the browser at the moment they occur.
Instead of looking at footprints on the beach after the fact, you’re actually “videotaping” how patrons interact with the beach. Do they stop? Do they swim? Did they bring a cooler? For the hotel marketer, how long did the customer stay on the site? Is it a repeat visit? Are there sections of the site the customer is more interested in than others?
2. Transform online data into a customer-centric data model.
While it’s nice to know that 15 people walked from the beach to the pool, it’s even nicer to determine who those people are and recognize who among them are the paid guests. Similarly, for the hotel marketer, how many clicks are associated with known, profitable customers as opposed to those simply browsing?
3. Analyze, forecast and report using enterprise business intelligence capabilities.
Just as a hotel wouldn’t use historical footprint counts in a spreadsheet to project how many patrons will be on-site next holiday season, marketers can’t rely exclusively on counting last year’s bookings after a holiday promotion to predict how this year’s promotion will perform. Instead, you need to pull in current data and predictions that take market changes into account.
The tangible results organizations can reap from this three-step approach are compelling. A number of large organizations are using SAS to understand the quality of customers being driven to their Web sites – and to target their marketing accordingly.
For example, a financial services company using SAS learned that out of 10,000 page views generated on their Web site via a Web banner ad, fewer than 10 were attributed to actual, valued customers. Advertising formerly thought effective was, in essence, “pulling loiterers into the pool.” Since that time, the organization has changed the allocation of its advertising budget and how it measures the effectiveness of expenditures.
Whether it’s understanding how customers use your site, or simply sifting out the loiterers from your true customer base, SAS for Customer Experience Analytics is delivering insights for organizations whose Web sites are key drivers of their business.
Bio:
John Bastone is a SAS Product Marketing Manager.
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