Which numbers are important, and what should you do when you've got them?
Recently in this column, I discussed the two types of e-metrics or Web analytics -- those that measure commerce and those that look at interactions with content. But these metrics, in the aggregate, may not be giving you the numbers you're looking for. You may need to get more specific to get the actionable information you need. This is important to understand because, for example, there are no "average" visitors. There are specific visitors from specific places, and, to maximize each visitor's value, he should be given specific treatment. To reach the required level of granularity, you should subdivide your macrometrics into their component micrometrics. By monitoring and optimizing these "conversion" metrics, you can begin to improve your results.
For example, on the content side, let's say your average visitor looks at three pages in a visit. However, what if you knew that a visitor who comes to you from Google looks at eight pages and one who comes in from MSN only looks at two pages? This information is crucial because it can directly impact your advertising strategy and profitability. It is always easier to develop your own winning edge -- just concentrate on the sources for getting the best visitors, and don't try to turn bad visitors into good ones. In this example, I might recommend cutting back on bCentral network banner ads and using the money saved to buy Google AdWords. This is how you optimize an ad campaign -- reallocating the money where you gets the best bang for the buck. Your strategy should be to buy low (cost per visitor, or CPV) and sell high (sales per visitor). The ratio that measures this is your conversion rate.
Of course, when we're looking at commerce, we want to know if these Google visitors are generating sales -- and if the sales per visitor are higher for Google than for MSN. Just because they view more pages doesn't mean they buy more products. So, before rearranging your ad campaign, use commerce metrics to confirm what you learned looking at content metrics. We may determine that a Google visitor not only views more pages per visit but also buys more products.
This can even be broken down further. Here's an example of some of the ways we can measure CPV:
Breaking numbers down this way gives you the information you need to optimize the campaign. If you see that your CPV for ad version 3 is better than for versions 1 and 2, you can establish a control. Then you can look at sales per visitor for your different landing pages and combine the two that achieved the best results. See how easily you can get bogged down in the details?
Previously, I wrote about how we can drown in the amount of raw data we collect from our Web analytics. Usually, the higher you move up in an organization, the more direct financial responsibility you have. For this reason, "C"-level execs and VPs are probably going to be most interested in commerce metrics (if you operate a commerce site) -- which give them a top-down view of the enterprise. They don't necessarily care about the eight pages per visit a Google visitor generates -- that's too much detail.
Still, the bottom-up (micro-) metrics all combine to create the top-down (macro-) metrics, so even though the top executives might not want to get detailed reports, people lower in the organization should. Why? Because a time will come when a C-level person will want to know why. Why is a certain macro-level metric falling or rising?
Let's use the Google/MSN example above. If the average page views per visit on the site fell during a certain month, one explanation could be that visitors from Google dropped while visitors from MSN increased. If you know a Google visitor both views more pages (content metrics) and buys more products (commerce metrics) than an MSN visitor, you can tell this C-level executive what happened and why. Then she's off to the ad guys to find out why they're driving more traffic from MSN than Google -- and she won't be breathing down your neck. Just because C-level people don't want micro-level reports doesn't mean it's not extremely valuable for somebody to get reports on the micro level.
This isn't that hard; certainly, it's not rocket science. With a little education, anyone can calculate basic Web metrics and understand and use these numbers to maximize results. Are you just gathering data, or are you gleaning valuable information that impacts your bottom line?
Bryan Eisenberg is co-founder and chief marketing officer (CMO) of IdealSpot. He is co-author of the Wall Street Journal, Amazon, BusinessWeek, and New York Times best-selling books Call to Action, Waiting For Your Cat to Bark?, and Always Be Testing, and Buyer Legends. Bryan is a keynote speaker and has keynoted conferences globally such as Gultaggen, Shop.org, Direct Marketing Association, MarketingSherpa, Econsultancy, Webcom, the Canadian Marketing Association, and others for the past 10 years. Bryan was named a winner of the Marketing Edge's Rising Stars Awards, recognized by eConsultancy members as one of the top 10 User Experience Gurus, selected as one of the inaugural iMedia Top 25 Marketers, and has been recognized as most influential in PPC, Social Selling, OmniChannel Retail. Bryan serves as an advisory board member of several venture capital backed companies such as Sightly, UserTesting, Monetate, ChatID, Nomi, and BazaarVoice. He works with his co-author and brother Jeffrey Eisenberg. You can find them at BryanEisenberg.com.
2015 Holiday Email Guide
The holidays are just around the corner. Download this whitepaper to find out how to create successful holiday email campaigns that drive engagement and revenue.
Three Ways to Make Your Big Data More Valuable
Big data holds a lot of promise for marketers, but are marketers ready to make the most of it to drive better business decisions and improve ROI? This study looks at the hidden challenges modern marketers face when trying to put big data to use.
December 2, 2015
1pm ET/ 10am PT
Wednesday, December 9, 2015
5pm HKT / 5am ET