Promotional Analysis: Profit Calculation

It may well be that discounts and promotions are what are needed to stimulate business.  Unfortunately, the tools needed to analyze whether a promotion is profitable or not aren't always available to the Google Analytics Generation.  The savvy Web Analyst needs to go a step further, in order to determine if a promotion is likely to generate profit.

In our example, we're going to pretend the following:

• Our promotion is "Take 20% Off Of Your Order, Today Only".
• Average order value = $100.
• 35% of demand converts to profit.

Step 1 = Execute A Test:  Ok, I realize almost none of you are going to do this.  But if you had done this, you'd know exactly how much business would have have happened "organically", without the need of a promotion.

Step 2 = Talk To Finance:  Since you didn't execute a test, you'll need to guess how much demand would have happened.  Somebody in the Finance department has a forecast for total demand on the day of your promotion.  Let's pretend that amount is $100,000.

Step 3 = Measure Sales on Promotion Day:  Let's pretend that demand was $140,000 on the day of the promotion.

Step 4 = Calculate Incremental Profit:  Here, we measure the difference in profit between $140,000 at 20% off vs. $100,000 at full price.

• The $140,000 demand yields $140,000 * 0.35 = $49,000 profit.  However, we gave up 20% of the $140,000 revenue, or $28,000, yielding $21,000 profit.
• $100,000 demand yields $100,000 * 0.35 = $35,000 profit.

Now, honestly, the CFO folks are going to jump all over me, telling me that there are hundreds of subtleties involved in calculating profit.  Go ahead, jump all over me.  This is an example, folks, the idea here is to stimulate thought among the Google Analytics Generation.  Savvy Web Analysts will work with their CFO to do this analysis and calculate profit.

Another thing to note here.  In many cases, companies offer a promotion, and the customer chooses not to use it ... the customer fails to enter the promo code, for instance.  So the Savvy Web Analyst will apply a "utilization rate" here, saying that 88%, for instance, of customers utilized the promotion.


Step 5 = Calculate Incremental New Customers, And Incremental Existing Buyers:  This is important.  Let's pretend that our average order value was $100 in each case.  This means we had 1,400 customers purchase via discount, and we had $1,000 customers who would have purchased at full price.  Carefully measure how many customers are new vs. existing.

• Discount Example:  400 new customers, 1,000 existing customers.
• Full-Price Example:  100 new customers, 900 existing customers.

Step 6 = Know 12-Month Profit By Customer Type:  People have been arguing for lifetime value analyses for decades.  For the Google Analytics Generation, it's hard to use software to calculate lifetime value.  The savvy Web Analytics analyst exports data out of existing Web Analytics platforms and analyzes long-term value.  I like to use 12-month profit.  You use whatever you want to use.

• Discount Newbies = $10 of 12-month profit.
• Discount Existing Buyers = $15 of incremental, additional 12-month profit.  This is the profit you get by converting, say, a three-time buyer into a four-time buyer.
• Full-Price Newbies = $15 of 12-month profit.
• Full-Price Existing Buyers = $17 of incremental, additional 12-month profit.  This is the profit you get by converting, say, a three-time buyer into a four-time buyer.

Step 7 = Calculate Expected Long-Term Profit:

• Discount Newbies = 400 * $10 = $4,000.
• Discount Existing Buyers = 1,000 * $15 = $15,000.
• Full-Price Newbies = 100 * $15 = $1,500.
• Full-Price Existing Buyers = 900 * $17 = $15,300.
• Discount Long-Term Profit = $19,000.
• Full-Price Long-Term Profit = $16,800.

Step 8 = Calculate Short-Term + Long-Term Profit:

• Discount Strategy = $21,000 short-term + $19,000 long-term = $40,000.
• Full-Price Strategy = $35,000 short-term + $16,800 long-term = $51,800.

In this case, the discount/promotion strategy yielded less short-term profit, more long-term profit, but not enough total profit.


Again, there are countless experts out there who will take exception with the methodology outlined here.  That's ok, those experts should publish their take on this, letting everybody see how they would approach the topic.  I'm trying to create a framework here for the Google Analytics Generation to see how one might measure whether discounts and promotions yield profitable outcomes.  In this case, there's no denying that the promotion yielded a significant sales increase, but does not appear to generate enough profit, short-term or long-term, to pay for the promotion.

Our Promotional Future

Sometimes we do things that cause customers to change behavior. In 2009, we might wonder why our customers don't seem to want to pay full-price for merchandise.

Here's what happens. Based on considerable customer analysis, we have a customer who like to buy full-price merchandise. Here's what this customer is expected to do, next year:

Normal Scenario	Full-Price	Discounts	Grand Totals
Demand	$50.00	$10.00	$60.00
Net Sales	$40.00	$8.00	$48.00
Gross Margin	$20.00	$4.00	$24.00
Less Mkt. Exp.	$7.00	$2.50	$9.50
Less Pick/Pack/Ship	$4.60	$0.92	$5.52
Variable Profit	$8.40	$0.58	$8.98
Profit % of Net Sales	21.0%	7.3%	18.7%

Notice that this customer has a reasonable chance of taking advantage of one of our many discount schemes (lower prices, free shipping, %-off offers). If the customer takes advantage of an offer of this nature, here's what next year's activity looks like:

Transition To Discounts	Full-Price	Discounts	Grand Totals
Demand	$25.00	$45.00	$70.00
Net Sales	$20.00	$36.00	$56.00
Gross Margin	$10.00	$18.00	$28.00
Less Mkt. Exp.	$5.00	$11.25	$16.25
Less Pick/Pack/Ship	$2.30	$4.14	$6.44
Variable Profit	$2.70	$2.61	$5.31
Profit % of Net Sales	13.5%	7.3%	9.5%

The customer is fundamentally different now. She actually spends more, $70 per year instead of $60 per year, but she's going to shop when you tickle her buying bone. And it costs money to tickle the buying bone of a loyal customer.

This style of analysis is essential in 2009. We need to see whether our thirst for clearning merchandise and "maintaining market share" in Fall 2008 have a detrimental impact on customer profitability in 2009.

Six Steps To A Well Executed Free Shipping Or %-Off Campaign

Read through each step, and ask yourself if your brand follows these steps.

Step 1: Always Execute A/B Tests. It's a good idea to make sure that some of your e-mail marketing list or catalog marketing list or paid search keyword campaign does not receive the promotion, and measure the performance of customers who receive the promotion vs. those who do not receive the promotion.

Step 2: Measure A/B Tests Long-Term. I cannot stress this enough. If you execute a free shipping test in November, re-visit the results of the test next May or June. Seriously. Measure the short-term impact and long-term impact. If you see a 20% lift in weeks 1-3 (the test period), and a -20% lift in weeks 4-26, you know that the promotion did not help your brand --- at all! Few folks actually execute this level of testing discipline. Those who do know secrets that the rest of us fail to understand.

Step 3: Quantify Incremental Orders And Flunked Orders. Incremental orders are those that were generated because of the promotion. Flunked orders are those that would have happened anyway, but now you gave away profit that lowers your bonus amount. If the test/control groups suggest that the promotion gave you a 20% increase in sales, while almost all of the orders happened with the key-code, then you know that 80% of the orders would have happened anyway. Flunked orders are bad --- they are orders where the customer believed in your brand, and would have spent hard-earned dollars that generate profit. We choose to flush that profit away. See Step 2 to understand if flunked orders generate long-term profit.

Step 4: Quantify "Staying Power". At Eddie Bauer, we measured the incremental value of the promotion by day. If the promotion lasted three weeks, we measured the lift by day. Those who execute this style of analysis know secrets about the staying power of tests that the rest of us simply make guesses about. Staying power is important, because if a promotion loses impact after a few days, you're required to constantly pull promotions off the board, then put them back up a few days/weeks later. And that isn't healthy for a brand --- it is like constantly hitting the gas pedal and then hitting the brakes while driving a car on the freeway. It means you are shifting power away from merchandise and to promotions. That's not a good thing --- you're in business to sell merchandise, not to sell promotions and gimmicks.

Step 5: Understand Who Utilizes Promotions. We don't do nearly enough of this, do we? Good analytics teams profile the customers who take advantage of promotions. Are they the best customers? Full price customers? Sale customers? Promotional customers? New customers? Lapsed customers? After profiling the audience, measure the long-term value of the customers utilizing promotions, comparing them to the customers who pay full price and pay for your bonus check.

Step 6: Understand Channel Dynamics. There's nothing wrong with executing promotions in e-mail campaigns and not in other advertising channels. But it is important to understand what this does to your business. Do the promotions cause e-mail subscribers to not buy from full-priced catalog marketing? If so, adjust the contact strategy accordingly, and realize that your e-mail marketing strategy lowers response in your catalog marketing channel (or vice versa). And seriously consider why your e-mail subscribers are more deserving of discounts and promotions than all other customers.

Poison Percentage

Ever wonder how you're really impacting your business with all of those free shipping and 20% off offers and bogos and whatever additional incentives you're offering the customer to buy merchandise?

One metric I've run for folks is called the "Poison Percentage" --- the percentage of volume, on a rolling twelve month basis that is generated because of a promotion.

I tend to stay away from item-level discounts, as those are influenced more by price elasticity and clearance activity --- those can be analyzed via a separate metric.

So the poison percentage focuses on free shipping, cheap shipping, percentage off an order, any promotion contrived by the marketing folks, any promotion that comes between the customer and the merchandise.

If that percentage is "high", maybe more than twenty percent of the total sales volume, then the business is being "poisoned", or so the theory goes. If you can drive enough volume and profit on discounted transactions --- and increase lifetime value in the process, then of course, you're not poisoning the business.

You'd run a profit and loss statement as follows:

Business With Discounts
	Clean Sales	Promotions	Tot.Company
Demand	$20,000,000	$10,000,000	$30,000,000
Net Sales	$16,000,000	$7,700,000	$23,700,000
Gross Margin	$8,800,000	$4,235,000	$13,035,000
Less Marketing Expense	$3,200,000	$1,309,000	$4,509,000
Less Discount Expense	$0	$1,200,000	$1,200,000
Less Pick/Pack/Ship Expense	$1,840,000	$885,500	$2,725,500
Varaible Profit	$3,760,000	$840,500	$4,600,500
Less SG&A Expense / Fixed Cost	$2,000,000	$1,000,000	$3,000,000
Earnings Before Taxes	$1,760,000	($159,500)	$1,600,500
Business Without Discounts
	Clean Sales	W/O Promos	Tot.Company
Demand	$20,000,000	$7,000,000	$27,000,000
Net Sales	$16,000,000	$5,390,000	$21,390,000
Gross Margin	$8,800,000	$2,964,500	$11,764,500
Less Marketing Expense	$3,200,000	$916,300	$4,116,300
Less Discount Expense	$0	$0	$0
Less Pick/Pack/Ship Expense	$1,840,000	$619,850	$2,459,850
Varaible Profit	$3,760,000	$1,428,350	$5,188,350
Less SG&A Expense / Fixed Cost	$2,000,000	$1,000,000	$3,000,000
Earnings Before Taxes	$1,760,000	$428,350	$2,188,350

You make assumptions about what would happen if you drop the discounts and promotions --- maybe within that audience, you lose 30% of your business, but you end up managing a smaller but more profitable business.

Are Discounts And Promotions Ruining E-Commerce?

A quick quiz: If we removed every one of the twenty boxes in the image (click on the image to enlarge it) and all of the potential permutations of the boxes in the image, what would happen to net sales, and earnings before taxes?

Discuss.