“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” – John Wanamaker
Advertising is a continuous guessing game. Doing your homework (research) can help you make informed decisions and minimize risk. Perhaps you’re confident answering some of advertising’s key questions like:
When should I spend?
- If I sell ice cream cones, I should probably spend most of my advertising dollars in the summer when the temperatures are high.
Who should I advertising to?
- What are the characteristics of my primary customer?
What should I say?
- Which message is most motivating to produce my desired response? (e.g. sales)
Where should I advertise?
- Which country/province/region/state/city should I advertise in?
The question that is often a black box for companies is, “How much should I spend?”
Maybe you’ve tried to answer this question by varying your advertising spending levels. You’re on the right track, but you still haven’t answered the question.
Varying spending will simply tell you whether one amount fared better than another amount. It won’t help you answer the two most important advertising spending questions:
- Am I spending enough on advertising?
- Am I spending too much on advertising?
These are obviously important questions to answer. You could possibly be missing out on opportunity (spending too little) or throwing advertising dollars down the drain (spending too much). So how do you answer this question? The first step is understanding how the marketing response curve works.
Marketing (or for that matter, many business functions) does not operate in a linear world. The theoretical marketing response curve (“S-Curve”) is an example of a non-linear relationship. At low levels of spending, we expect to see very little increased sales response – the spending is below some effective level called a “threshold.” As spending continues to increase, we expect to start to identify a positive relationship with sales … up to a point of diminishing returns, where an incremental dollar invested doesn’t produce the same response.
Identifying the “threshold point” and “saturation point” is critical to optimizing your advertising spending. So how do you know which part of the S-Curve you’re on?
Return on Marketing Investment (ROMI) analysis
ROMI analysis is our proprietary approach to answering some of marketing’s most important questions. Our basic approach to conducting a ROMI analysis is pretty simple. We do “fancy math” (big data machine learning techniques) to identify and quantify the relationships between marketing inputs and the desired outputs. The inputs can be a long list of the various line items that marketing or sales dollars are invested in. Examples include advertising (by media – traditional AND digital), promotions, rebates, inbound and outbound phone calls, etc. There can be multiple outputs as well. Examples include $-Sales, new customers, website traffic, hand-raising activity, etc. The goal is to understand how a change in an input can impact changes in the desired outputs – pretty simple concept.
In reality, the execution of this on our side is not very simple. One reason is the number of interactions involved in your marketing activities can be very large.
The more variation your advertising spending has had over the past few years the better. By looking at different spending levels in combination with a wide range of other marketing activities, a ROMI analysis can help you identify your location on the theoretical S-Curve – and ultimately answer the question, “Am I spending enough on advertising?”
If you’re currently at the low end of the area of “high effectiveness” (see diagram above), you could be missing out on millions of dollars in untapped revenue.
If you’re currently spending below the threshold point, you have two options:
- Save your money and stop spending because the level you’re spending is not enough to make an impact.
- Increase your spending to reach the threshold point and beyond.
Every business that spends dollars on advertising needs to ask the question, “Am I spending enough on advertising?” The good news is the answer to this question is not hidden in a black box; it’s a deliverable in a ROMI analysis.