Should We Invest More in Marketing or Lower Prices to Increase Sales?

Should We Invest More in Marketing or Lower Prices to Increase Sales?

The article addresses a question we frequently receive from clients who are responsible for business decisions, conveying to us their concerns about the necessary investment in advertising and its relation to the selling price and the volume of sales: Should I spend more on digital marketing and raise the sale price to compensate? What if I instead lower the prices and the investment in Google Ads? Or should I reduce margins to increase sales?” The eternal dilemma…

 Here’s our input.

The impact of the variation of retail prices and the investment in digital marketing on sales volume and the prices of products or services depends on many factors, including the quality of the ads, the segmentation of the target audience, competition, and the supply and demand for the products or services being promoted. Generally, increasing advertising investment usually results in an increase in the reach and visibility of the ads, which in turn tends to generate more sales. However, this does not necessarily imply increased profits, as advertising expenditure can consume all the margins. Moreover, if the investment is focused on promoting products/services with high competition and high prices, this can increase price pressure and reduce profits. Therefore, it is crucial to constantly monitor and optimize the advertising campaign to maximize its impact on sales and prices.

For a digital marketing campaign, accurately determining the increase in sales due to increased advertising spend, or the decline in sales due to price increases (in selling), presents immense complexity: it would require experiments in different geographical areas, over a sufficiently long period, with no internal changes in account management, in the landing… and still, the results of such experiments would be contaminated by external factors such as competitor actions, availability of subsidies, seasonality, etc., and their validity would be very limited over time, as new actions from competitors would change the conclusions. Realistically, we can only make before/after evaluations, comparing results from different periods, and acknowledging the aforementioned limitations.

What is theoretically possible is to calculate the boundary values in the relationship between changes in advertising spend and changes in sales that maintain total profits. That is, it can be accurately determined the minimum necessary increase in sales for total profits not to decrease, when increasing advertising spending (assuming that the price is not raised). The graphs below help us explain this.

In Figure 1, the increase in advertising spend (ordinate axis, y) is related to the increase in sales (abscissa axis, x) for one of our clients.

Figure 1 - Increase in Investment per Sale vs Sales Increase
Figure 1 - Increase in Investment per Sale vs Sales Increase

The curve (orange), representing the equation y = x/(1+x), is not interpreted as “the increase in advertising investment per sale (y) associated with an increase in sales (x)”, but as a boundary representing the maximum increase in advertising per sale (y) that could be made without decreasing the total profit when sales increase by a certain amount (x) or, equivalently, the minimum sales increase (x) that is necessary to offset a certain increase (y) in advertising investment per sale.

In the case represented by Figure 1, if by investing an additional 100 $ per sale in advertising, sales are increased by 50%, the investment will have been profitable, and total profits will increase, as we are in the green zone (point A on the graph). However, if to achieve a 50% increase in sales you need to invest an additional 400 $ per sale, total profits will be reduced (we are in the red zone, point B). Finally, if by investing those additional 400$ per sale a 100% increase in sales is achieved, the total profits would not vary (break-even), and we would be precisely on the orange curve (point C). The farther from the curve in the green zone, the higher the profits; the farther from the curve in the red zone, the greater the losses.

Figure 1 is valid for a specific case, with a determined average profit. If this value changes, the scale of the graph would consequently change. However, by using a new variable y, on the y-axis, the “maximum loss of profit per sale“, understood as the total percentage of that profit, instead of the unitary advertising spend, the graph would not depend on the reference average profit, meaning, its scale would be preserved regardless of the considered average profit. This is represented in Figure 2.

Figure 2 - Profit Loss per Sale vs Sales Increase
Figure 2 - Profit Loss per Sale vs Sales Increase

The curve (orange), which again represents the equation y = x/(1+x), is not interpreted now as “the decrease in unit profit (per sale, y) associated with an increase in sales (x)”, but rather as a boundary that represents the maximum fall in profit per sale (y) that can be assumed without decreasing the total profit, when sales increase a certain amount (x) or, equivalently, the minimum increase in sales (x) that is necessary to offset a certain drop (y) in profit per sale.

If, for example, by increasing advertising investment, keeping the retail price constant, the profits per sale drop by 10%, but sales are increased by 50%, the investment will have been profitable, and the total benefits will increase, as we are in the green zone (point A). However, if that increase in advertising investment implies a fall in profit per sale of 50%, while the increase in sales is also 50%, the total benefits will be reduced (we are at point B, in the red zone). If, with that increase in advertising investment, the profits per sale were to drop by 50% while sales increase by 100%, the total profits would not vary, and we would be precisely on the orange curve (point C). The farther from the curve in the green zone, the greater the profits; the farther from the curve in the red zone, the greater the losses.

If we keep the advertising investment per unit sold constant, Figure 2 can also help us to see the relationship between a variation in the selling price and the necessary impact on sales for the change to be worthwhile.

In summary, the impact of variations in investment in digital (and analog) advertising on sales and prices depends on many factors. Generally, increasing advertising investment usually results in an increase in the reach and visibility of the ads, which in turn can generate more clicks and conversions. To maintain total costs, it is necessary for the increase in sales to be at least equal to the increase in advertising expenditure; this is what is represented, in a particular case (Figure 1) and another general (Figure 2) in the graphs of the article.

It is worth noting that, although one objective may be to maintain total costs and/or increase profits, any increase in advertising investment can present other additional benefits to the company, such as increased visibility, larger market share, and a revaluation of the company.In the end, investments in advertising have to go hand in hand with a strategic plan where the primary objective of the company is clear: to grow or to earn more money. Since both options do not always go together, and/or in the short term, priority has to be given to one of the two.

Would you like us to analyze your situation? Let’s talk, and we will design the marketing strategy that best suits your needs. Contact us with no obligation.

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