Everybody needs to be data-driven of their advertising and gross sales course of. It is a good aim. Understanding your knowledge and making use of that perception lets you optimize your campaigns and drive extra site visitors, conversions, and gross sales.
Typically, these “insights” come within the type of trigger and impact: “after 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’ll be able to misread your knowledge and make misguided choices. You may waste some huge cash and time on ineffective and even detrimental channels and techniques.
On this article, we’ll cowl what correlation and causation are, how they differ, and clarify how that impacts advertising and gross sales. Lastly, we’ll share some sensible methods to persistently 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 per thirty days to sending 3,000 per thirty days. On the similar time, your gross sales income elevated. Does that imply that sending extra emails precipitated you to make extra gross sales?
Not precisely. We will 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 overall variety of sends? It may even be an outdoor issue, like elevated model recognition that drives each extra leads and makes them simpler to shut.
This is the reason that you must know tips on how to inform correlation from causation. With out that understanding, you’ll be able to find yourself investing within the improper areas of your campaigns. The definitions under will make it easier to perceive the qualities of every and tips on how to distinguish them.
What’s correlation?
Correlation merely means that there’s a vital relationship between 2 variables. A variable is one thing you’ll be able to measure—in advertising, consider issues like income, site visitors, social shares, the variety of e 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 might be both optimistic or destructive. A optimistic 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 effectively. If you happen to chart factors on a graph of those 2 variables, the factors kind 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 kind a downward line.
For instance, over the previous century, the variety of folks incomes grasp’s levels and the overall field workplace income of the movie trade have elevated steadily. Each variables elevated, so this can be a optimistic correlation. Our instance of emails and gross sales income is one other instance of a optimistic 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 can be both optimistic or destructive. In a optimistic 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 alternative. If A will increase, it causes B to lower, or vice versa. As an example, extra folks 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 signifies 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 optimistic or destructive), 1 should have precipitated 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 staff’s scratching their heads, questioning why their new marketing campaign isn’t driving vital outcomes.
In actuality, there are various 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 an alternative 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 an alternative of assuming 1 causes the opposite, we should always contemplate a 3rd variable impacting each: the climate. Increased 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 ingesting extra espresso since you didn’t sleep effectively, or are you not sleeping effectively since you’ve been ingesting extra espresso?
It is 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 problem, chain reactions are when 1 or extra different variables act as an middleman between A and B. Reasonably than A inflicting B, maybe A is inflicting a change in variable C, and the change in C impacts B. If you happen to have been to vary one thing about variable C, the correlation between A and B may disappear.
How correlation vs. causation impacts your small business
Trendy gross sales and advertising campaigns are data-driven, so that you must perceive the patterns in knowledge and what relationships they point out. While you perceive the place correlation and causation present up in your small business, you may be higher ready to establish every.
Correlation vs. causation in advertising
In any efficient digital advertising marketing campaign, you’re continuously making modifications 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 study, simply that you need to watch out.
Electronic mail advertising is a big part of digital advertising, and entrepreneurs typically check plenty of alternative ways to doubtlessly enhance outcomes. You might change the topic line and see a higher open price. However what if that open price is affected by the point of day, the day of the week, and even which kind of subscribers occurred to see the e-mail that day?
That’s why it’s essential to manage different variables and check 1 factor at a time (and with sufficient quantity to get a statistically vital consequence).
Within the quest for enchancment, it typically seems like entrepreneurs don’t have time to be this exacting. Within the subsequent part, we’ll cowl tips on how to navigate this downside.
Correlation vs. causation in gross sales
Gross sales groups are additionally more and more in search of to optimize their processes and practices with “large knowledge.” In search of outdoors components that have an effect on gross sales can be key to planning and technique.
For a easy instance of how correlation and causation can get fuzzy, contemplate when a pricing change appears associated to a change in gross sales. Let’s say your organization sells snow boots. Growing prices drive you to boost your costs. And gross sales enhance month over month! It would appear to be rising costs precipitated gross sales to extend, however you need to contemplate different components, like seasonality and whether or not your advertising and product availability has remained constant.
Possibly across the time you needed to elevate costs, you additionally have been capable of get your snow boots in a brand new retailer. Or perhaps, 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 varied components. When you ought to all the time be in search of methods to optimize the gross sales course of, you must also do not forget that causation is troublesome to show, and assuming a cause-and-effect relationship may result in false assumptions and unhealthy choices.
decide correlation or causation
Your small business doesn’t happen in a wonderfully managed laboratory setting. Some countless variables and circumstances could possibly be affecting your advertising and gross sales outcomes. However that doesn’t imply you’ll be able to’t examine your knowledge to learn to optimize your processes.
The easiest way to determine a cause-and-effect relationship is to vary simply 1 factor and see what occurs. You may consider this as testing your speculation. A speculation simply means what you suppose will occur should you make some change to a variable or situation.
For instance, you may hypothesize that sending your month-to-month e mail publication earlier within the day will result in a better open price. The variable you might be altering is the time the e-mail publication is distributed. To get significant proof that your speculation is appropriate, you should hold all the opposite variables fixed: the topic line, the sender identify, and many others. If every other particulars are modified, you received’t be capable to say that the ship time affected the open price conclusively. That is the place A/B testing is available in.
A/B testing lets you change and check simply 1 variable in your advertising or buyer expertise at a time. Probably the most frequent makes use of of A/B testing is figuring out higher e mail topic traces. You ship the very same e mail on the similar time to 2 teams of individuals, with every group getting a unique topic line. If there’s a distinction within the open price or conversion price, you’ll be able to moderately 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’ll be able to nonetheless be looking out for correlation and causation. If you happen to or a colleague imagine you see a relationship between 2 issues, ask yourselves:
- What proof is there for a causal relationship?
- What different variables could be affecting the end result?
- May this be a part of a sequence response?
In a enterprise setting, you could not all the time be capable to distinguish correlation and causation precisely. Nonetheless, you’ll be able to examine your proof, carry out extra experiments, and make knowledgeable choices.
Often requested questions
Solutions to a few of the most typical questions on correlation vs. causation.
How will you know if a relationship is causal or correlational?
Correlation is when there’s an observable relationship between 2 variables. Causation is a particular relationship wherein 1 variable causes a change within the different.
A fastidiously managed experiment is right for figuring out causation. Retaining every thing else the identical, you’d change the variable you suppose is the trigger and observe to see if it creates a change within the variable you imagine is affected.
If you happen to can’t do such a managed experiment, it’s a good suggestion to search for exterior components that could 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 extra weight and due to this fact causes the load of the container to extend.
What’s an instance of correlation however not causation?
The variety of folks shopping for calendars and the variety of folks becoming a member of gyms each enhance across the starting of the yr. Individuals are not becoming a member of a fitness center as a result of they purchased a calendar, nor are they shopping for a calendar as a result of they joined a fitness center. Each variables are affected by the point of yr and cultural norms.
Correlation doesn’t suggest causation
Everybody needs to work smarter. Everybody needs 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 modifications that don’t really trigger enchancment.
The excellent news is that should you’re conscious of the variations between correlation and causation, you’ll be able to check and analyze your knowledge to deduce when modifications are value implementing. And with the ever-growing variety of digital buyer interactions, you’ll be able to accumulate and study 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.
