Mega-Metrics: Monthly Conversion Rate

Almost all of us have analyzed the results of marketing activities via the "conversion rate". The online industry is fueled by conversions. Directionally, the metric works.

And yet, the metric is fundamentally wrong.

At Nordstrom, we analyzed our multichannel shoppers to death. We knew the following happened, on a monthly basis --- called the "3-2-1" rule.

• The multichannel shopper visited our website three times a month.
• The multichannel shopper visited at least one store two times a month.
• The multichannel shopper purchased one time a month, usually in a store.

An online conversion rate is woefully inadequate when measuring this type of behavior. So is shopping cart abandonment. All we really care about is that, over a period of time, did the customer buy from us? We don't care how the customer got to the end result --- we only care about the end result!! With that in mind, conversion rates and shopping cart abandonment rates are feckless --- they simply do not measure how customers actually behaved.

While still flawed, we evaluated a "Monthly Conversion Rate".

• Take all customers who visited your website in the past month.
• Of those visitors, what percentage purchased something, in any channel?
  
• Divide monthly purchasers by unique monthly visitors.

Now some of you will send me e-mail messages and leave anonymous comments, nitpicking the fact that I forgot to think about concepts "A", "B" and "C". And you'll keep using conversion rate as your favorite metric. Life is richer when individuals have different ideas for solving problems.

What is important is the business intelligence you gain from a monthly conversion rate. All of a sudden, you realize that your conversion rate isn't a measly 4.398541842304%. Instead, your website facilitates a monthly conversion rate of 37% across all channels. Heck, you're not the failure that the vendor community portrays you to be!!!!!!! You're actually more successful than you thought. That's not a bad thing.

So instead of beating me up over all the reasons this metric is wrong, work with your BI team, or with Coremetrics/Omniture to create this metric, and start enhancing the way you evaluate your business --- pick a different timeframe or metric --- just do something to advance your industry!

Shopping Cart Abandonment And Conversion Rate

1) Customer visits on 11/1, places item in shopping cart.

2) Customer visits on 11/5, browses, leaves item in shopping cart.

3) Customer visits on 11/7, deletes item from shopping cart, calls over the phone, and buys an item after talking to a customer service rep.

Question #1: Do you have a conversion rate or shopping cart abandonment rate problem?

Question #2: If your answer to question #1 is "No", are you accounting for this behavior in your web analytics tool, so that you can clearly see any real shopping cart abandonment rate issues?

Question #3: If the customer in (3) purchased online, do you have a conversion rate or shopping cart abandonment problem?

Discuss!

Do Online Conversion Rates Differ By Business Model?

Please click on the image to enlarge it.

Each year, Internet Retailer publishes their Top 500 websites, in terms of annual net sales.

If one is willing to take the time to have information transcribed into digital format, there are interesting tidbits to consider, including information about conversion rates and business models.

In this case, I took the top three hundred sites, and analyzed various performance metrics by the type of business model employed by the brand.

In other words, Crutchfield would be viewed as a cataloger, due to their catalog heritage, whereas Talbots would be viewed as a Retail Chain, due to their retail heritage. Blue Nile would be a web-only business. Sony would be a Consumer Brand Manufacturer. Internet Retailer made these determinations.

Of the three hundred sites, I adjusted the top ten and bottom ten outliers for each metric. For instance, if the top ten conversion rates were 20%, 18%, 17%, 16%, 15%, 15%, 15%, 14%, 14% and 14%, then I adjusted all ten outliers to 14%.

Now for today's tidbit. An analysis of conversion rates by business model indicates that Catalogers have the highest website conversion rate at 4.89%, followed by Web-Only businesses at 3.92%, Retail Chains at 3.05% and Consumer Brand Manufacturers at 2.99%.

Catalogers have natural advantages. They bring in traffic via catalog marketing and online marketing. Retail Chains have disadvantages online, in that websites are used for research that results in an online purchase. Consumer Brand Manufacturers have distinct disadvantages, in that conversion may actually happen at a Cataloger, Web-Only Business or Retail Chain.

For catalogers, the news is encouraging. With postage and paper costs impeding the catalog marketing channel, this provides hope. Undoubtedly, catalog marketing will evolve as the cost structure makes traditional catalog marketing difficult. Catalogers will evolve their online experience further away from "order taking", moving closer to the experience provided by Web-Only businesses. The economics of catalog marketing will dictate this.

For retailers, the news is encouraging. The data may indicate that the retail channel gobbles up between thirty and sixty percent of possible orders. Online marketers within retail businesses have an opportunity to analyze "incremental" profit and loss statements, those that account for the sales that are truly driven by the website. Ultimately, appropriate cross-channel analysis should result in a bigger marketing budget for online marketers in retail organizations.

Conversion Rate Is No Longer An Appropriate Measure Of Website Effectiveness

It might be a good time for our friends, the web analytics folks, to help us evolve the concept of conversion rate.

I recently saw a report where a business categorized good customers as of February 1, and measured website visitation activity during the month of February. Here's what this business saw (numbers are altered, the point is still easily made).

• There are 125,993 good customers as of February 1, 2007.
• Of the 125,993 good customers, 87,327 visited the site during February (69.3%).
• On average, the visitors had an average of 3.41 visits during February.
• Of the 87,327 visitors, 15,719 purchased merchandise on the website in February, purchasing an average of 1.10 times, yielding 17,291 orders.

We typically report an overall conversion rate --- something paltry like 3.29%. Then industry pundits and vendors jump all over us, telling us how ignorant we are regarding website design, failure to convert shopping carts, you name it.


If we look at actual customer behavior, we see a different story.

• The website converted 15,719 of 87,327 visitors during the month of February.
• 15,719 / 87,327 = 18.0% of the customers who visited at least one time purchased something during February. This is what matters!! Track this metric, year-over-year, and see if this metric is improving.
  
• In terms of visits, 17,291 / 297,785 = 5.8% actual conversion rate for this segment of good customers.

Conversion rate is rapidly becoming an unimportant metric, when viewed within the context of actual customer behavior. Conversion rate is dictated by software. We want to let our customers dictate how they want to use our websites.

If a customer wants to visit your site eight times before making a purchase, then let the customer visit eight times. Don't agonize over conversion rate because the customer wants to visit your site often. Measure monthly conversion rate instead!

Multichannel Retailers and Conversion Rates

Pundits spent a lot of time telling us that multichannel customers are the most valuable customers. This finding has become largely unusable.

The concept of multichannel customers becomes very interesting, when explored via conversion rates online.

When you get to work on Monday, try this exercise.

Step 1: Segment your online visitors, from February 1, 2006 to January 31, 2007. Segment them into the following classifications:

• Those who purchased online, in catalog, and in stores during that time period.
  
• Those who purchased online, and in catalogs during that time period.
  
• Those who purchased online, and in stores during that time period.
  
• Those who purchased in catalog, and in stores, during that time period.
  
• Those who only purchased online during that time period.
• Those who only purchased via catalog during that time period.
  
• Those who only purchased via stores during that time period.
  
• Those who had not purchased, but had visited the website multiple times during that time period.
• Those who had not purchased, but had visited the website just one time during that time period.

Step 2: For each of the nine segments listed above, calculate the following metrics:

• Number of Households.
• Number of Households who visited the website during February 2007.
• Average Number of Visits per Household Visiting, during February 2007.
• Total Number of Visits, during February 2007.
• Percentage of Households Purchasing Online During February 2007.
• Percentage of Households Purchasing In Catalog During February 2007.
• Percentage of Households Purchasing In Stores During February 2007.
• Percentage of Households Purchasing, Any Channel, During February 2007.
  
• Online Conversion Rate (Total Online Purchases / Total Online Visits), February 2007.

The magic of this type of analysis is that the multichannel executive gains an understanding of who is visiting her website, how her customers use the website, and how much more effective the multichannel retailer's website is at converting online customers.

Even better, the multichannel executive will learn that the website is frequently used as the research tool for offline purchases. We hear that customers use our websites in this way all the time --- this reporting is a first step in understanding how different customer segments utilize the site to purchase merchandise.

Multichannel CEOs and CMOs: We spent a lot of time integrating purchase data across channels during the past decade. Integrating clickstream data with multichannel purchase data is another logical, important, and necessary step in the evolution of mulitchannel marketing.

Web Analytics Experts: This is a really good time to expand your skillset beyond clickstream and funnel analysis. Your future depends upon being able to segment customers at one point in time, and then measure customer performance over a future period of time.