Email Frequency/Revenues explained by The Laffer Curve
And why are the Email Potentates still fighting over something so blatantly obvious?

 

I’m getting slightly nauseated by the opinionated grandstanding going on in this supposed “dialogue” concerning frequency vs. segmentation, as methods to maximize revenue and profit in email. I therefore propose we use commonly accepted economics models to explain it, and furthermore, perhaps start to figure out what we are really disagreeing on.

The Laffer Curve serves that purpose perfectly. If you don’t know it by it’s name, I’m sure you have seen the concept in action. It was originally introduced by economist Arthur Laffer in 1972 to illustrate that increasing the tax percentage after a certain point does not increase revenues for the Government (something I wish New York State was a bit more knowledgeable about, but that’s a whole other rant).

Now, how does that relate to email? In exactly the same way, increasing email volume/frequency/cadence will increase revenue up to a certain point, but above that point the actual total revenue from email will start to decrease as you increase the frequency. Keep in mind that I said TOTAL, meaning monthly/quarterly/yearly etc. not just revenue per email although that will also be on of the consequences. This of course is due to over saturation, heightened annoyance levels and general disinterest causing emails to be ignored or unsubscribed.

To illustrate, I borrowed an illustration from Forbes.com showing the original Laffer Curve, the “Email Frequency Additions” are mine.

the laffer curve image

Now what’s the point, you might ask? The point is that most revenue maximizing strategies follow fairly predictable patterns, most of which deal with diminishing returns, meaning that increased effort after a while creates lesser and lesser profit increase, until it’s actually costing you more money than you make to increase it any further.

Think for an example about how adding one more person into your department would probably make things go smoother and allow you to increase revenue margin more than the cost of that one person, but adding 100 people would probably just create utter chaos and reduce your output overall. Even if you could miraculously manage the hiring process, it wouldn’t be a cost effective strategy.

Thus, whatever you do now to increase revenue can probably not be repeated endlessly to increase revenue, however successful it is at this stage. Email frequency is no different. As long as you see increase in revenue by adding another email into your monthly mix, you are in the increasing revenue part of the curve, just make sure that your margin is good enough to pay for the additional cost. You can continue to increase deployments as long as overall revenue, or rather profit margin continues to grow faster than the cost and you are not seeing too much increase in spam complaints or unsubscribe activity (at least from those that are likely to buy something from you).

Now one important part to add to this is that you can extend the curve by adding better more relevant content and segmentation. The two approaches are not opposites, as many have been arguing, they are complimentary strategies. You can increase segmentation and increase the number of emails to each subscriber at the same time or different times. These two strategies are never mutually exclusive, but work wonders together. We see this across all categories of B2C emails. The most successful email marketers send frequent emails to all/most subscribers and effectively segment them as well. That way they get increased revenue due to increased interest from consumers as the emails are more relevant, and they get more revenue because the frequency of the emails is higher than it otherwise could effectively be. Amazon for example sends over a thousand campaigns every day in a very segmented approach with great results.

I really and truly wish this helps, however, I don’t want to attend one more email conference where there is actually a discussion about frequency vs. segmentation. It’s like debating whether if you should eat salad or salad dressing! I think most would agree they’d go best together.

 

Written by G.B. Heidarsson, CEO at eDataSource

 

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