August 20, 2012

Conversion Rates: Judy, Jennifer, Jasmine

You remember our lovely ladies:

The first lady is Judy.  She's around 59 years old, and her behaviors tend to be "old-school" ... she buys via catalogs, and while she embraces new technology, she primarily shops via habits derived in the 1980s and 1990s.

The second lady is Jennifer.  She's around 43 years old, and her behaviors are hard to "attribute".  She hunts online for the best products at the best prices, touching many marketing channels.

The third lady is Jasmine.  She's around 27 years old.  Her behaviors are not consistent with Judy and Jennifer.  Social and Mobile are part of her entire adult experience.

We can analyze online customer behavior via each persona.  Here's a query I recently ran ... segmenting customers as of June 30, 2012, measuring online visit behavior from July 1, 2012 to July 31, 2012.  Each persona represents weighted life-to-date transactions for twelve month buyers.


  • 38,498 customers.
  • 18.9% Re-Visit Rate.
  • 3.568 monthly visits per visitor.
  • 0.674 purchases per visitor.
  • 7.3% conversion rate.
  • 0.049 purchases per customer.
  • 143,984 customers.
  • 24.3% Re-Visit Rate.
  • 4.387 monthly visits per visitor.
  • 1.066 purchases per visitor.
  • 5.9% conversion rate.
  • 0.063 purchases per customer.

  • 88,430 customers.
  • 28.8% Re-Visit Rate.
  • 5.220 monthly visits per visitor.
  • 1.503 purchases per visitor.
  • 5.2% conversion rate.
  • 0.078 purchases per customer.

Notice that Jasmine is far more "engaged" than Judy or Jennifer.  Judy is much less likely to visit the website, and if she visits, she only visited 3.6 times in July.  Jasmine, meanwhile, is 50% more likely to visit than Judy, and will visit every 5-6 days.  Judy is more "purpose driven" than Jasmine, converting at a much higher rate.  Jasmine, however, because of her high likelihood of visit regularity, buys much more often online.

This is something the conversion optimization gurus sometimes miss ... we want Jasmine's behavior, but we optimize for Judy's behavior.  This is exactly opposite of what we should do.  We want more visits at a lower conversion rate, if the net result is a significant increase in total purchases, as it is in this example with Jasmine.

The Math Behind Bifurcated Customers Who Have "Moved On" From Catalogs

Yesterday we talked about a classic, outstanding catalog customer ... and how that customer needed MORE mailings on an annual basis. ...