This is part 2 of a 6 part series. You can check out part 1 here, or you can be a rebel and continue on.
During the offseason, the Philadelphia 76ers data analyst noticed that the team with the most offensive rebounds usually wins the game. So this season, they’ve decided to do whatever it takes to ensure they get more offensive rebounds than their opponents. After a 0-22 start to the season, they still can’t figure out why their strategy – starting five poor-shooting centers and intentionally missing shots to give them the opportunity to get more offensive rebounds – isn’t working.
How miserable was that to read? And this is just part 2… imagine how bad it’ll be by part 6.
Here’s some sketchy definitions (relating solely to this article in the vacuum of advertising) for you:
Related Variable – Something that, when changed, will impact the performance of advertising relating to the advertiser’s goal.
For instance—For every 5 “10% off” (“T”) coupons James gives out, someone buys 1 pizza, and for every 3 “free cheesy bread with a pizza” (“C”) coupons James gives out, someone buys 1 pizza. To simplify:
5T = P or T = P/5
3C = P or C = P/3
If the goal is to sell pizzas, then the cheesy bread coupons are a more highly related variable because each one is essentially worth 33% of a pizza sale, while the 10% off coupons are worth 20% of a pizza sale.
Opportunity Cost – When a marketing strategy or advertising decision is made, the loss of the potential gain all of the other options that weren’t chosen in the decision.
In our pizza example above, the opportunity cost of James deciding to hand out 30 10% off coupons instead of 30 cheesy bread coupons is the sale of 4 pizzas. Using the values of T & C given above:
30T = 6
30C = 10
Part 2, Identifying Related Variables and Their Relationship with Your Goal(s)
I know, you get it. There are certain variables that affect performance.
Scoring more points than the other team is probably going to work out in your favor. Striking every batter out will probably help your team win the game. Not ever letting your king get put in check… (#TopicalDiversity #NotJustSports)
You get it.
Good. Because what I want to discuss is the identification of opportunity costs of related variables.
A restaurant with the goal of increasing profits will pretty easily come to the conclusion that getting more people to walk into the building is a variable that is highly-related to their goal. Therefore, they positively associate advertisements that get people in the door with increasing profits.
Consider this poorly conceived hypothetical with made-up statistics—A restaurant (with the goal of increasing profits… I feel like that should probably be implied from here on out unless I say otherwise) is directly off a major interstate exit, which is several miles away in either direction from the next exit.
Speaking of… here are our 30 eligible passers-by.
The restaurant boasts a large, well-lit billboard that ownership has decided to finally utilize. They want more people getting off the interstate and walk into their restaurant—an undeniably good strategy for increasing profits. In fact, the restaurant’s consulting firm has determined, based on available data, that only 3% of people who walk into their doors don’t eat there. (diners shaded green)
Ownership understands there are those that will be coming in whether they use the billboard or not. They’re the loyal road trippers. But it’s the untapped market that they want to get in the doors because, as you know according to their information, only 3% of the restaurant’s visitors don’t dine.
So, in the spirit of luring people in, they put on their massive billboard, in bright, flashing lights “Clean Bathrooms” where it’s clearly visible to the travelers on the interstate—where after several miles from both directions without an exit, 66% of them have to use the bathroom:
So what happens? The “Clean Bathroom” idea works. Foot traffic is increased. People end up just deciding to eat there although that was not their original intention out of convenience. It turns out to be a truly profitable decision by doubling their food revenue. (diners shaded green)
… but was it the most profitable?
What was the opportunity cost of their billboard messaging?
Consider for a second if they had decided to put, “$1 Carne Asada Tacos—All Day, Every Day” on the billboard, and it ended up generating a lower percentage of interstate travelers to stop by. In fact, in this alternate universe, only half of the number of people that were stopping in for “Clean Bathrooms” stop in for “$1 Carne Asada Tacos.” Scary.
Ownership in this alternate universe has cut their advertisements target demographic in half, compared to the alternative billboard option, in one of the most highly-related variables to their goal of increased profits.
… but does that make it the wrong decision? (diners shaded green)
As you already figured out paragraphs ago, maximizing a highly rated variable doesn’t necessarily generate the best results—although more often than not, it will—but sometimes, there is a better option.
In the hypothetical above, the opportunity cost of choosing the bathroom billboard was the revenue from 2 diners. (12 ate with the bathroom billboard up and 14 ate with the tacos billboard up)
Just because something works, doesn’t mean it works the best. Many businesses in every industry are incredibly apprehensive to try something new because they don’t want to risk doing something that doesn’t work. Yet with that mindset, these businesses will never realize the ever-growing opportunity cost of not changing their strategies.
Unlike my crude hypothetical, advertising today isn’t a decision between two options based on a few variables. It’s a complex, deep, interwoven matrix of information and misinformation. And instead of determining whether a restaurant should advertise food or a toilet, single individuals are being asked to evaluate the entirety of the internet and its advertising opportunities and compare them to the traditional methods, which are evolving at an exponential pace.
So what can you do to get a handle on all of the opportunity costs in an effort to make better advertising decisions? See: Part 3, Valuation of Goal(s) and Related Variables
Other Articles in this Series:
Part 1, Goal Identification
Part 3, Valuation of Goal(s) and Related Variables
Part 4, Measuring Ad Performance
Part 5, Considerations in Advertising Strategy Adjustment
Part 6, Practical Application