Everybody desires to be data-driven of their advertising and gross sales course of. This can be a good purpose. Understanding your knowledge and making use of that perception means that you can optimize your campaigns and drive extra site visitors, conversions, and gross sales.
Usually, these “insights” come within the type of trigger and impact: “Once we do X, it ends in Y. So let’s do extra of X.” However many entrepreneurs don’t analyze the info deep sufficient and mistake correlation for causation.
And once you don’t perceive the distinction between correlation and causation, you possibly can misread your knowledge and make misguided choices. You possibly can waste some huge cash and time on ineffective and even detrimental channels and ways.
On this article, we’ll cowl what correlation and causation are, how they differ, and clarify how they have an effect on advertising and gross sales. Lastly, we’ll share some sensible methods to constantly inform correlation from causation in a enterprise setting.
What’s correlation vs. causation?
Let’s say you elevated the variety of gross sales emails you despatched final quarter. You went from sending 1,000 emails monthly to sending 3,000 monthly. On the similar time, your gross sales income elevated. Does that imply that sending extra emails induced you to make extra gross sales?
Not precisely. We are able to see that there’s a connection, i.e., a correlation, between the two metrics. As 1 goes up, the opposite intently follows. Nonetheless, we don’t have sufficient knowledge to grasp if that’s why the income elevated.
What if the variety of emails you despatched elevated as a result of different advertising channels drove considerably extra focused leads, thus driving up the whole variety of sends? It might even be an out of doors issue, like elevated model recognition that drives each extra leads and makes them simpler to shut.
For this reason it’s essential to know how one can inform correlation from causation. With out that understanding, you possibly can find yourself investing within the flawed areas of your campaigns. The definitions under will assist you to perceive the qualities of every and how one can distinguish them.
What’s correlation?
Correlation merely means that there’s a vital relationship between 2 variables. A variable is one thing you possibly can measure—in advertising, consider issues like income, site visitors, social shares, the variety of electronic mail campaigns, or advert spend.
The two variables within the instance we launched above are the variety of emails despatched and the gross sales income.
A correlation could be both constructive or destructive. A constructive correlation is when each variables enhance or lower collectively. In different phrases, when 1 variable will increase, so does the opposite, and when 1 variable decreases, the opposite does as nicely. If you happen to chart factors on a graph of those 2 variables, the factors type an upward line.
A destructive correlation is when the connection reveals that when 1 variable will increase, the opposite decreases. If you happen to chart factors on a graph of those 2 variables, the factors type a downward line.
For instance, over the previous century, the variety of individuals incomes grasp’s levels and the whole field workplace income of the movie business have elevated steadily. Each variables elevated, so this can be a constructive correlation. Our instance of emails and gross sales income is one other instance of a constructive correlation.
For an instance of a destructive correlation, contemplate the gross sales of smartphones and the weekday circulation of newspapers. Since 2007, smartphone gross sales have elevated whereas newspaper circulation has decreased.
What’s causation?
Like correlation, causation is a relationship between 2 variables, nevertheless it’s a way more particular relationship. In a causal relationship, 1 of the variables causes what occurs within the different variable.
A causal hyperlink will also be both constructive or destructive. In a constructive causal hyperlink, the rise or lower of 1 variable causes the identical change within the affected variable. So if A will increase, B will increase. And if A decreases, B additionally decreases. For instance, extra rainfall will trigger the native river’s water ranges to rise.
In a destructive causal hyperlink, the connection is the other. If A will increase, it causes B to lower, or vice versa. For example, extra individuals driving into city and parking their vehicles will trigger there to be fewer empty parking areas.
Why does correlation not equal causation?
As we’ve lined, a correlation simply means that there’s some relationship between 2 variables. In distinction, causation implies that the change in 1 variable is inflicting the change within the different. Folks typically mistake the two, assuming that as a result of 2 variables have a relationship (whether or not constructive or destructive), 1 should have induced the opposite.
Entrepreneurs are particularly responsible of this. “Look, we did X, and our gross sales elevated!” Cue plowing time, effort, and assets into extra of the identical. Two months later, the group’s scratching their heads, questioning why their new marketing campaign isn’t driving vital outcomes.
In actuality, there are numerous different explanation why 2 variables may exhibit a sample in how they alter. Understanding these causes helps you keep away from assuming causation when it’s actually only a correlation.
Third variable (or confounding variable)
As a substitute of 1 of the two variables inflicting the change within the different, there could also be a 3rd variable that impacts each. One basic instance is that ice cream gross sales enhance as charges of sunburn enhance. As a substitute of assuming 1 causes the opposite, we should always contemplate a 3rd variable impacting each: the climate. Greater temperatures and extra sunshine have an effect on each ice cream gross sales and sunburn charges.
Directionality points
The problem of directionality refers to when it’s unclear whether or not variable A is inflicting variable B or if variable B is inflicting variable A. For instance, are you consuming extra espresso since you didn’t sleep nicely, or are you not sleeping nicely since you’ve been consuming extra espresso?
This can be a basic downside with advertising and gross sales, as every division will fortunately take the glory for a rise in income and drum up some metrics that appear to show that “we did it.”
Chain response
Just like the third variable situation, chain reactions are when 1 or extra different variables act as an middleman between A and B. Fairly than A inflicting B, maybe A is inflicting a change in variable C, and the change in C impacts B. If you happen to had been to alter one thing about variable C, the correlation between A and B may disappear.
How correlation vs. causation impacts what you are promoting
Fashionable gross sales and advertising campaigns are data-driven, so it’s essential to perceive the patterns in knowledge and what relationships they point out. Whenever you perceive the place correlation and causation present up in what you are promoting, you can be higher ready to determine every.
Correlation vs. causation in advertising
In any efficient digital advertising marketing campaign, you’re always making adjustments and changes on the fly. And with so many variables, it may be difficult to find out that 1 trigger is having a specific impact. That doesn’t imply there isn’t one thing to be taught, simply that you need to watch out.
Electronic mail advertising is a large element of digital advertising, and entrepreneurs typically take a look at a number of other ways to probably enhance outcomes. You might change the topic line and see a higher open fee. However what if that open fee is affected by the point of day, the day of the week, and even which sort of subscribers noticed the e-mail that day?
That’s why it’s essential to manage different variables and take a look at 1 factor at a time (and with sufficient quantity to get a statistically vital consequence).
Within the quest for enchancment, it typically appears like entrepreneurs don’t have time to be this exacting. Within the subsequent part, we’ll cowl how one can navigate this downside.
Correlation vs. causation in gross sales
Gross sales groups are additionally more and more looking for to optimize their processes and practices with “massive knowledge.” In search of outdoors components that have an effect on gross sales will also be key to planning and technique.
Think about when a pricing change appears associated to a change in gross sales for a easy instance of how correlation and causation can get fuzzy. Let’s say your organization sells snow boots. Rising prices power you to boost your costs. And gross sales enhance month over month! It’d look like rising costs induced gross sales to extend, however you need to contemplate different components, like seasonality and whether or not your advertising and product availability have remained constant.
Possibly across the time you needed to increase costs, you additionally had been capable of get your snow boots in a brand new retailer. Or possibly, it’s late fall, and the approaching winter means demand for snow boots has skyrocketed.
As in advertising, your gross sales outcomes could also be affected by numerous components. When you ought to all the time be on the lookout for methods to optimize the gross sales course of, you must also keep in mind that causation is tough to show, and assuming a cause-and-effect relationship might result in false assumptions and dangerous choices.
How you can decide correlation or causation
Your corporation doesn’t happen in a superbly managed laboratory atmosphere. Some infinite variables and situations might be affecting your advertising and gross sales outcomes. However that doesn’t imply you possibly can’t examine your knowledge to learn to optimize your processes.
One of the simplest ways to determine a cause-and-effect relationship is to alter simply 1 factor and see what occurs. You possibly can consider this as testing your speculation. A speculation simply means what you assume will occur when you make some change to a variable or situation.
For instance, you may hypothesize that sending your month-to-month electronic mail publication earlier within the day will result in the next open fee. The variable you might be altering is the time the e-mail publication is distributed. To get significant proof that your speculation is right, you need to hold all the opposite variables fixed: the topic line, the sender identify, and so on. If every other particulars are modified, you received’t be capable to say that the ship time affected the open fee conclusively. That is the place A/B testing is available in.
A/B testing means that you can change and take a look at simply 1 variable in your advertising or buyer expertise at a time. Some of the frequent makes use of of A/B testing is figuring out higher electronic mail topic traces. You ship the identical electronic mail on the similar time to 2 teams of individuals, with every group getting a special topic line. If there’s a distinction within the open fee or conversion fee, you possibly can fairly assume that the topic line was the trigger (if there’s a statistically vital distinction).
In conditions the place you don’t have as a lot management, you possibly can nonetheless be looking out for correlation and causation. If you happen to or a colleague consider you see a relationship between 2 issues, ask yourselves:
- What proof is there for a causal relationship?
- What different variables is perhaps affecting the result?
- Might this be a part of a series response?
In a enterprise setting, it’s possible you’ll not all the time be capable to distinguish correlation and causation precisely. Nonetheless, you possibly can examine your proof, carry out extra experiments, and make knowledgeable choices.
Regularly requested questions
Solutions to among the commonest questions on correlation vs. causation.
How will you know if a relationship is causal or correlational?
Correlation is when there may be an observable relationship between 2 variables. Causation is a selected relationship during which 1 variable causes a change within the different.
A fastidiously managed experiment is good for figuring out causation. Protecting all the pieces else the identical, you’d change the variable you assume is the trigger and observe to see if it creates a change within the variable you consider is affected.
If you happen to can’t do such a managed experiment, it’s a good suggestion to search for exterior components which may be inflicting a correlation.
What’s an instance of causation?
Causation refers to 1 variable inflicting a change in one other—for instance, because the variety of merchandise in a transport container will increase, the load of the container will increase. The addition of merchandise provides further weight and subsequently causes the load of the container to extend.
What’s an instance of correlation however not causation?
The variety of individuals shopping for calendars and the variety of individuals becoming a member of gyms each enhance across the starting of the yr. Persons are not becoming a member of a health club as a result of they purchased a calendar, nor are they shopping for a calendar as a result of they joined a health club. Each variables are affected by the point of yr and cultural norms.
Correlation doesn’t indicate causation
Everybody desires to work smarter. Everybody desires to make progress rapidly. These needs make it tempting to see relationships the place you need them and assume trigger and impact. In advertising and gross sales, this might lead you to waste time and assets on adjustments that don’t truly trigger enchancment.
The excellent news is that when you’re conscious of the variations between correlation and causation, you possibly can take a look at and analyze your knowledge to deduce when adjustments are price implementing. And with the ever-growing variety of digital buyer interactions, you possibly can acquire and be taught from knowledge greater than ever earlier than.
To get entry to finish buyer (and prospect) knowledge and begin leveraging A/B testing in your campaigns to fact-check your data-based hunches, entry your free trial of ActiveCampaign.
