Ecommerce Analytics – The Right Measurements for All the Wrong Reasons

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With the mountain of metrics and measures available to e-commerce marketers, it's all-too-easy to get stuck in the trap of measuring for the wrong reasons. In fact, in my consulting practice I often find e-commerce companies missing the real point of measurement altogether … and missing significant opportunities for profit growth as a result.

For example, I worked with one company that was using a very sophisticated Web analytics package to measure hundreds of different aspects of their e-commerce site. This company also held weekly meetings where senior managers from across the company would discuss the various metrics. Sounds ideal so far, does not it? But after sitting in one of these discussions, it became very clear to me that the company was missing the point.

Rather than using their meters as a jumping off point to unforgettable significant opportunities for profit improvement, it seemed that the numbers were being presented for informational purposes only, as if they were just "nice to know." Significant week-over-week changes in critical measures like carting ratios were presented matter-of-factly, with no root-cause diagnosis or impact analysis taking place whatever.

This company was measuring many of the right things, but for all the wrong reasons.

Do not fall into this trap. Using your metrics to understand how you're doing is nice, but it's missing the point. The real power in measurement comes from using the numbers and ratios to significantly improve your performance . To do that, you need to get beyond the "nice-to-know" factor and ask some powerful diagnostic questions:

Is this level of performance good or bad?

Simply knowing that you have a cart-to-visit ratio of 6% is only meaningful if you also realize that typical ratios in the industry are much, much higher and you have a significant room for improvement. Similarly, knowing that you have a checkout-abandonment ratio of 70% is only useful for improving your performance if you also realize that typical ratios are much lower. After all, a number is just a number until it's put into some relative, contextual framework.

Why is this metric at this level of performance?

Whether your metrics are high or low, relatively speaking, your next question should be "why?" An overall orders-to-visits conversion rate that is really low might be a symptom of a really uncompetitive offer, a shotgun approach to lead-generation, a poorly-constructed web site, or a combination of these factors. Along the same lines, a really high checkout-abandonment ratio could have a symptom of high shipping rates, lack of shipping options, slow secure-server response times, lack of payment options, etc. Like a good doctor, you must get to the underlying causes before you can prescribe effective solutions.

What is causing this metric to change over time?

When you see a metric changing significantly over time, it's almost always profitable to try and understand why. In certain markets, a significant increase in your orders-to-visits conversion ratio could be caused by a change in competitive pricing conditions and may indicate that you're leaving big money on the table with pricing that is too low. Similarly, a big decline in cart-to-visit ratios may be caused by an influx of unqualified traffic – which may or may not be a problem, depending on whether the source is a paid source.

How can I profitably impact this metric in a sustainable way?

Once you understand the root-causes behind the metrics and the various elements that can have an effect on the numbers themselves, you have the keys to identifying profitable, systemic improvements. Let's say, for example, that you've identified six possible root-causes behind your reliably high checkout-abandonment rates. You can now tackle each one, starting with the easiest and least costly.

Extreme measure-ability is one of the many virtues of e-commerce business. But if you are not prepared to really use the metrics and measures to diagnoseose problems and identify opportunities for profit improvement, you might be measuring the right things but for all the wrong reasons.

Source by Rafe Vandenberg

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