November 30, 2006

Return on Investment Formulas In Multichannel Retailing

Let's talk about some of the equations that individuals use to measure advertising return on investment in the multichannel retailing industry.

Ad to Sales Ratio: This is one of the most frequently used equations. Assume you spent \$10,000 on an online marketing campaign, and generated \$50,000 net sales. The ad to sales ratio is calculated as (\$10,000 / \$50,000) = 20%. Obviously, the lower this percentage is, the better your advertising performed. Multichannel retailers compare advertising efforts against each other with this metric.

Sales per Ad Dollar: Some industry publications like to use this metric. In the above example, we simply calculate the inverse of the ad to sales ratio. (\$50,000 / \$10,000) = 5.00. In this case, you get five dollars of sales for every dollar of advertising spent. The higher the metric, the better your advertising performed. E-Mail pundits like to use this measure, since e-mail has virtually no cost, thereby insuring that it has a good "return on investment".

Cost per Order: Online marketers enjoy using this metric, one that is maybe the least effective metric of all. Assume that the \$10,000 spent in our previous examples generated 400 orders. Cost per Order (sometimes labeled "CPA" for cost per acquisition) is (\$10,000 / 400) = \$25.00. Each advertising strategy is compared, with lower metrics preferred. This metric is highly skewed, because the metric doesn't account for how much was spent, per order.

Profit per Order: A more effective, but less-used metric, is profit per order. Let's assume that, in the example above, twenty-five percent of the sales generated are converted to profit. In this case, (\$50,000 * 0.25 - \$10,000) = \$2,500 of profit is generated. Next, divide the \$2,500 profit by 400 orders. This yields \$6.25 profit per order. This is one of the better ROI measures, because all aspects of the profit equation, sales, margin, and marketing cost, are included. Better yet, this measure can be stacked-up against long-term value metrics. For instance, if a marketer loses \$10.00 profit per order, but expects to get \$50.00 lifetime value back, the marketer should invest in the marketing activity.

Internal Rate of Return: This metric is not frequently used, but reflects what happens if marketing dollars are continuously invested over the course of a year. In the Profit per Order equation, we netted \$2,500 profit on an investment of \$10,000. Let's assume that this marketing effort took place over a twenty-six week period of time. The internal rate of return is calculated as (\$12,500 / \$10,000) ^ (52 / 26) = (1.25 ^ 2) = 1.56. In other words, on an annual basis, this investment has a fifty-six percent interest rate. The interest rate can be compared against all other marketing activities (many of which have a different time window --- e-mail may have just seven days, for example).

Your turn! What return on investment metrics do you like to use to evaluate marketing activities at your company?

1. You wrote:

Respectfully, not necessarily so.

Consider 3 marketing campaigns. Assume COGS @ 50% of sales and other variable costs (call center, credit card discount, etc) @ 10% of sales. Here are the scenarios:

[A] \$1 mil sales, 10% A/S
[B] \$3 mil sales, 20% A/S
[C] \$5 mil sales, 40% A/S

Which scenario "performed best"? Let's do the math.

[A] generates \$300k in marketing contribution (\$1mil - \$500k cogs - \$100k advertising - \$100k other var exp).
[B] generates \$600k in marketing contrib.
[C] generates \$0k.

So again, which is best?

[B] clearly trumps [A] -- you put dollars in the bank, not percentages. But which is better, [B] or [C]?

Answer: it depends on what the retailer P&L goals. The retailer seeking profit clearly prefers \$600k to zero, and choose [B]. The retailer who values top line growth may prefer \$5 mil in sales to \$3 mil, and choose [C].

If your marketing goal is 30% A/S and your team delivers 25% A/S and their was more advertising inventory available (of sufficient quality to keep the whole A/S at 30%), then you could criticize that team for leaving sales on the table.

Just pointing out that lower A/S isn't always "better". More efficient, yes, but sometimes sales and/or margin dollars trump efficiency percentages.

Cheers --

Alan

rimmkaufman.com/rkgblog

2. Alan, you would be correct. And the majority of the folks who use ad-to-sales would not be able to follow the more complex logic that comes from evaluating several dimensions at the same time (sales, margin, advertising, variable costs).

Because of that, most folks revert back to ad-to-sales ratio or CPA. And those folks aren't as profitable or don't drive the sales volume they could drive.

3. Another metric: a handful of our clients use A/M, advertising-to-margin.

Not entirely obvious (one benefit of A/S is you can read it right off a P&L), but the idea is what fraction of a productions gross margin do you invest in selling it.

I think in general the best bet is maximize sales subject to an A/S constraint, if the margin structure is relatively homogeneous. (If not, appropriate category-level A/S targets based on category margin).

A/S used this way is a very good proxy for true marketing profitability, and is simple to calculate and employ.

Cheers!

Alan

4. Ray S5:06 PM

Interesting dialogue guys-- I spent a little time playing with P&Ls in Excel and I follow your logic. Thanks for the thoughts!

On Alan's point of driving revenue vs. driving profit, would either of you be willing to comment on this topic? As a marketing analyst I've often analyzed marketing campaigns with top line demand growth but no incremental profit. I've struggled spinning a complete 'story' with this result and I've seen conflicting opinions by directors in my organization.

Any rule of thumb? Thoughts in general? Is driving demand enough!?

5. Ray, I think the question you ask comes down to one of philosophy, and corporate objectives.

Driving incremental sales increases, without corresponding profit increases, can be beneficial in at least three instances. If the company is having a hard time increasing top-line sales, then campaigns that drive top line sales but leave profit flat can be positive. Second, if the long-term value gained by migrating customers from 1x to 2x purchase frequency, or 2x to 3x, or 10x to 11x is sufficient to off-set no change in short-term profit, the decision could be a good one. Third, if there is no gain in long-term profitability, but you obtain a stronger customer file by executing campaigns that increase sales but do not increase profit, the decision can be a good one.

Most controversial is the situation where you purposely decrease sales, in order to become more profitable. If you work for a publicly traded company, this is seldom viewed as a great way to manage the business. Data miners sometimes get into this rut. They build statistical models that suggest you can reduce expense, while maintaining sales and increasing profit. The strategy doesn't work very often, and seldom builds a strong customer file.