## February 20, 2007

### E-Commerce "Power" And Web Analytics

How 'powerful' is your e-commerce website?

In other words, does your website have enough recent visitors and purchasers to fuel the growth of your business?

'Power' is an area that web analytics tools and web analysts usually fail to consider when performing their valuable job function.

'Power' is simply an expectation of how productive your e-commerce website will be this year, based on last year's performance and this year's visitor counts.

Let's review a very simple example of E-Commerce 'Power'.

Step 1: Segment your January 2006 website visitors as follows:
*** Segment 1 = Any customer who purchased online in January 2006.
*** Segment 2 = Any visitor who did not purchase, but visited 3+ times in January 2006.
*** Segment 3 = Any visitor who did not purchase, but visited 2 times in January 2006.
*** Segment 4 = Any visitor who did not purchase, but visited 1 time in January 2006.
*** Segment 5 = Any visitor who did not visit in 1/2006, did visit 1+ time from 2/2005 - 12/2005.

Step 2: Once you have segmented your file, take the mean of online spend in February 2006 for each visitor/cookie in Segments 1-5.

Your analysis should look something like this:

Segment 1 = 15,000 January 2006 Buyers, Spending An Average Of \$25.00 in February 2006.
Segment 2 = 50,000 January 2006 3+ Visits / No Purchase, Spending \$9.00 in February 2006.
Segment 3 = 125,000 Jan-06 2 Visits / No Purchase, Spending \$5.00 in February 2006.
Segment 4 = 1,000,000 Jan-06 1 Visit / No Purchase, Spending \$2.00 in February 2006.
Segment 5 = 10,000,000 Feb-05 to Dec-05 1+ Visit, No Purchase, Spending \$0.50 in Feb 2006.

Multiplying customers by average spend, then summing across five segments, yields \$8,450,000 of demand generated on the website, during February 2006.

You are now ready to calculate your E-Commerce website's 'Power'. You need just one more step to complete the analysis.

Step 3 = Replicate Step 1, but instead of using January 2006 as your timeframe for segmentation purposes, advance your timeframe by one year for each segment. This reflects your website customer file, as it exists today.

Step 4 = Multiply this year's customer counts by last year's average spend. This gives you an expectation for how much existing customers and visitors will spend this year, if all other conditions are the same. Here is an example of the resulting analysis:

Segment 1 = 22,000 January 2007 Buyers, Spending An Average Of \$25.00.
Segment 2 = 55,000 January 2007 3+ Visits / No Purchase, Spending \$9.00.
Segment 3 = 135,000 Jan-07 2 Visits / No Purchase, Spending \$5.00.
Segment 4 = 1,100,000 Jan-07 1 Visit / No Purchase, Spending \$2.00.
Segment 5 = 14,000,000 Feb-06 to Dec-06 1+ Visit, No Purchase, Spending \$0.50.

Multiplying customers by average spend, then summing across five segments, yields \$10,920,000 of expected online demand during February 2007.

We've finally made it to the 'Power' calculation.

Power = This Year's Expected Demand / Last Year's Actual Demand.

Power = \$10,920,000 / \$8,450,000 = 1.292.

We did it!! Your portfolio of online purchasers and visitors are 29.2% stronger than last year. You should expect existing buyers and visitors to spend 29.2% more this year than last year, all things being equal.

In an ideal online environment, the web analytics folks will run this analysis for you at the start of the month, and communicate E-Commerce 'Power' to the executive team in the early stages of each month.

Multichannel CEO/CMO Takeaway: It is time to expect much more out of your web analytics team. Standard web analytics tools do a great job of telling you what happened during an individual session. Standard web analytics tools do a poor job of predicting the future. Leaders need to know what will happen in the future. Partner with your web analytics team on this simple segmentation exercise. You and your analytics folks will be able to forecast business problems before they happen.

During the next few years, we will hit a point where the online channel stops growing rapidly. Leaders need to be the first people to know that a demand shortfall is coming. Beat your competition to the punch by reacting to your E-Commerce 'Power' Analysis.