How Heavy is Heavy-up?

We often find ourselves in the situation in which our recommendations require changes that are large in magnitude or challenge the sacred cows of an organization.  In many of these cases there is tolerance for a test- either as a way to double check results before committing to a large change, or to “put your money where your math is” to dispel the organizational mythology.

But then a critical question is “how much should we spend?”  It’s a legitimate question; spend too little and you won’t be able to read it in the results, and spend too much and you’ve blown the budget before the test even starts.

Here’s a quick-and-dirty starting point for spend levels:

A.Start with total sales for the heavy up period (in this case, we’ll assume one month):$40,000,000
B.Insert Assumed Sales Lift (see below for guidelines):1.5%
C.Multiply A x B to get topline impact of test:$600,000
D.Find appropriate margin rate (gross margin, operating margin, profit margin):45%
E.Multiply C x D to get margin impact of test:$270,000
F.Plug in assumed Payback of test tactic:$0.35
G.Divide E/F to get required test spend for that tactic:$771,000

A. Use the total sales for the product, channel, and geography that you’re going to measure here.  For instance, to test local radio in Chicago for a laptops available at a single retailer, use just Chicago laptop sales through that retailer.
B. Different approaches have differing levels of precision, based on data availability and analytics, but we generally advise that using anything less than 0.5% is too little, 0.5-1.0% has moderate risk of not being readable, but greater than 1.0% is safe.
C. This is the expected “sales lift.”
D. Use the same margin rate that you will use to calculate ROI- finance can help.
F. If you have prior assumptions for the payback of the tactic you’re testing, use it here.  Otherwise, using lower paybacks is safer.  If you’re not sure, we recommend using $0.35.

As always, don’t hesitate to contact us with questions.  We’d love to hear from you.