E-Commerce And Catalog Management Case Study: Optimal Profitability

So far, we've studied numerous aspects of a failing e-commerce/catalog business:

• Profit And Loss Statement of the Failing Business.
• Operational Management
• Managing P&L Details
• Comparable Segment Performance

In the final installment of this series, let's extend the analysis, and review the ways in which customer investment influences the profit and loss statement.

When a business is struggling, it is common for the executive team to reduce marketing investment. When a business is thriving, it is common for the executive team to increase marketing investment.

Changes in marketing investment (which, in reality, is a change in investing in customers) cause short-term and long-term ramifications.

Let's assume that the business we've been analyzing can return to good operational profit performance --- in other words, the business does a reasonably good job of fulfilling merchandise, minimizing returns, increasing gross margin, and reducing pick/pack/ship expenses.

We can simulate the short-term and long-term impact of different investment strategies (this is the essence of a Multichannel Forensics project).

In the table below, I outline this year's Earnings Before Taxes (EBT) as a function of how much we invest in each twelve-month buyer, and as a function of how much we invest in acquiring new customers and reactivating older customers.

Maximize Profit This Year
12 Month
Investment		Customer Acquisition Investment
per Buyer	$600,000	$1,050,000	$1,500,000	$1,950,000
$6.00	$1,091,000	$1,011,000	$857,000	$661,000
$9.00	$1,115,000	$1,035,000	$882,000	$686,000
$12.00	$1,098,000	$1,018,000	$864,000	$668,000
$15.00	$1,051,000	$971,000	$818,000	$622,000

Which combination yields the most profit? If our brand invests $9.00 of marketing in twelve-month buyers, and invests $1,050,000 in new/reactivated customers, EBT is maximized.

This is where those of us in e-commerce/catalog typically stop our analysis. We simply look to "optimize" current year profitability, smile, create an investment plan, and move on.

Let's take the analysis a step further. Why don't we look at the EBT of this business in five years, given each of the sixteen strategies we just reviewed?

Maximize Profit Five Years From Now
12 Month
Investment		Customer Acquisition Investment
per Buyer	$600,000	$1,050,000	$1,500,000	$1,950,000
$6.00	$261,000	$388,000	$400,000	$346,000
$9.00	$339,000	$479,000	$501,000	$457,000
$12.00	$382,000	$529,000	$556,000	$515,000
$15.00	$399,000	$546,000	$574,000	$534,000

Which strategy is best in five years? It appears that investing $15.00 in twelve-month buyers, coupled with an investment of $1,500,000 in new/reactivated customers yields the best EBT/profit.

I can count on one hand the number of catalog/e-commerce businesses that I've seen simulate the long-term impact of short-term investment decisions. Sure, some businesses calculate "Lifetime Value". Even among those businesses, the calculations are rarely plugged into a simulation that measures short-term and long-term EBT.

The CEO should be given a series of simulated results, results that help the CEO determine the best short-term and long-term profit paths based on existing and new/reactivated customer investment strategies. Owners and Boards should always have ample access to simulated business outcomes, and should actively shepherd growth of the brand on the basis of simulated results.

Here is what happens to the long-term trajectory of this brand, when maximizing short-term results.

• Year 5: Demand = $20,400,000, EBT = ($259,000).
• Year 6: Demand = $17,300,000, EBT = $1,073,000.
• Year 7: Demand = $16,100,000, EBT = $813,000.
• Year 8: Demand = $15,600,000, EBT = $659,000.
• Year 9: Demand = $15,400,000, EBT = $548,000.
• Year 10: Demand = $15,300,000, EBT = $450,000.

Conversely, here is what happens to the long-term trajectory of this brand, when maximizing long-term results.

• Year 5: Demand = $20,400,000, EBT = ($259,000).
• Year 6: Demand = $21,400,000, EBT = $818,000.
• Year 7: Demand = $21,600,000, EBT = $774,000.
• Year 8: Demand = $21,800,000, EBT = $718,000.
• Year 9: Demand = $21,900,000, EBT = $651,000.
• Year 10: Demand = $22,000,000, EBT = $574,000.

The CEO has interesting challenges ahead.

The most profitable route is to shrink the business by about fifteen percent. However, this strategy constrains long-term profitability.

Conversely, the CEO can operate under tepid to flat growth, resulting in a healthier business in the long-term.

Regardless, marketing is not going to drive sales increases. Merchandise productivity will have to significantly increase, in order to drive improvements in sales and profit.

Let's try an example. Say the leadership team is able to increase customer demand for merchandise by fifteen percent. Now look at what happens when we try to maximize long-term profit:

• Year 5: Demand = $20,400,000, EBT = ($259,000).
• Year 6: Demand = $24,700,000, EBT = $1,692,000.
• Year 7: Demand = $25,900,000, EBT = $1,801,000.
• Year 8: Demand = $26,700,000, EBT = $1,829,000.
• Year 9: Demand = $27,100,000, EBT = $1,810,000.
• Year 10: Demand = $27,400,000, EBT = $1,758,000.

Wow!

In other words, the leadership team can play with investment in customers/marketing, significantly improving the profitability of this brand. But if the merchandising folks can find product that customers like fifteen percent more than prior products, the profit and loss statement sings a beautiful tune!

Armed with this information, the new CEO is likely to require the following of this e-commerce/catalog brand.

• Objective: Improve final merchandise fulfillment to at least 93.0%.
• Objective: Reduce the return rate to 25.0%, or lower.
• Objective: Target a gross margin of at least 50.0% or better.
• Objective: Reduce the pick/pack/ship expense to 11.5% or less of net sales.
• Objective: Improve merchandise productivity by at least 15%.
• Objective: Invest $15.00 marketing expense per twelve-month buyer.
• Objective: Invest $1,500,000 marketing expense in new/reactivated buyers at the most efficient cost per new customer possible.
  
• Objective: Grow net sales to at least $24.5 million on an annual basis.
• Objective: Increase EBT to at least $1.7 million, about 10% of net sales.

Realistically, it will take two years for the brand to implement the steps necessary to achieve lofty objectives like these.

In theory, every executive, director, manager and analyst should be accountable for at least one of these objectives. The new CEO gives the entire team a two-year timeframe for making this happen, demanding significant progress during year one.

And that, ladies and gentlemen, concludes our case study! Your thoughts?