The data that automatically comes up in your dashboard, however, doesn’t always mean what you think.
For example, you might see that you’ve earned thousands of clicks on a blog article and automatically assume that it’s your top-performing post, but would you still consider it a top-performing article if the bounce rate was incredibly high and people only spent an average of five seconds on the page?
Getting the data you need isn’t always as simple as looking at your analytics tool’s dashboard presets; in fact, sometimes that information can actually be quite misleading! Here are five marketing data myths debunked.
Data Myth 1: Cost per click determines the effectiveness of your ad campaigns
Whether you’re running ads on Facebook, Google, LinkedIn or anywhere else online, it’s essential to know the metrics that determine whether a campaign is a success or failure. Use the wrong data and you risk pouring money into ineffective ads.
Lower cost upfront isn’t always better
Let’s say you’ve been running two ad campaigns for over a month — one running at $3.50 cost per click (CPC) and the other at $1. You check in on them daily and are growing to favor the $1 CPC ad for obvious reasons; you’re spending less than a third of the money on clicks for this campaign.
A month has passed with these same consistent results, so you stop the more costly ad. The next day, you notice that something horrifying has happened: Your sales came to a screeching halt. This can’t be possible, right? Unless you were looking at the wrong data to begin with.
Dig deeper: Look at your ad ROI
Once the initial shock of halted sales wears off, you pull up all the numbers to compare the two ad sets in more depth. Here’s what you find:
The seemingly more expensive ad was actually bringing in more leads — at nearly half the cost per lead. So you decide to dig deeper. Did they turn into customers?
Come to find out, the $3.50 CPC ad not only brought in a higher number of quality leads, but it also converted those leads into much higher-paying customers than the $1 ad, resulting in more revenue coming from the ad you’d once pinned as a failure.
The number you should have been calculating all along was return on investment (ROI). Here’s how to calculate it:
It’s a date
Why is ROI the magic number? Marketing analytics expert Scott Desgrosseilliers says, “Think about dating. If you’re trying to get married, cost per click is evaluating how much it cost you to take her to dinner. But the ROI is, ‘Did you fall in love or get married?’”
The answer is in the context: If your goal is to close more sales and generate more revenue, your ROI can’t be calculated by simply counting how many people clicked on your ad.
Data Myth 2: If the open rate is good, your email campaign is a success
While a high email open rate is a good sign, it’s not a definitive answer to whether your email was a success or failure. Think about your own inbox: How many emails do you open up just to clear your notifications?
It’s not about how many people open it; it’s about what they do after
Let’s say you send a promotional email every week on the same day at the same time to 1,000 subscribers. Your average open rate is 12%, but in the first week of April, you changed your copy and noticed that 20% of your subscribers opened it. This email must be better, right? Not necessarily.
It all goes back to your goal. Ask yourself the following questions:
1) Why am I sending out emails in the first place?
2) What do I hope to gain from them?
3) If I don’t achieve that goal with these emails, are they still a success?
Chances are, your ultimate goal is to generate sales and revenue from your email marketing campaigns. If that’s the case, there’s a whole different set of numbers that determine whether your campaign is a success or failure.
It’s all about revenue per email
Open rates and sales generated from emails don’t always go hand-in-hand. In fact, it’s completely possible to get a low number of opens, but those who do read your message are compelled to buy. There’s no way to know unless you dig into the numbers for revenue per email.
In order to accurately calculate revenue per email, set up tracked links and use “last click” information to determine whether or not a reader bought after clicking on a link within the email.
Data Myth 3: First-click attribution tells you your best source of sales
When it comes to attributing sales, one of the most common misconceptions is that first-click attribution is the only factor to consider. While first-click does tell you how a lead got in the door, it’s only a piece of the puzzle. It’s like asking a married couple how they ended up together — the smooth pickup line or fancy first date might have been where it all started, but the proposal and all the stuff in between is also an important part of the story. The same goes with first- and last-click attribution.
Combine first- and last-click attribution for the win
For marketers, the full story matters. In order to understand exactly what converted leads to customers, they not only need to know how they became aware of your brand, but also what nurtured them into the sale.
First-click attribution shows you what attracted your customers to your business, while last-click shows you the last link they clicked on before converting. This is useful in telling you which of your assets are most convincing at prompting your desired result. With that information, you can adjust your campaigns to direct more traffic to that asset. This is why you should be using both first- and last-click attribution.
Data Myth 4: Number of page views determines landing page success
Views on your landing pages are a good sign, but they’re not the only sign. How many times have you clicked on a page only to realize it wasn’t what you were looking for and immediately closed it?
Page views are only on the surface
If you only look at the raw number of views your pages get, chances are you’ll be misled. Paying attention to metrics that are more meaningful is key in deciphering the numbers. Since there is no single KPI that can tell you the full story, you should be familiar with the metrics that can successfully direct your campaigns in the right direction.
Instead of just looking at page views, a combination of metrics — such as time on page, unique visitors and percentage of article completed — are a better way to measure whether a page is performing well.
Let’s say you have two versions of your sales page: One has 12,000 page views and the other has 8,000. Similar to our CPC scenario, if your business is getting lots of sales, you might attribute that mostly to the page getting so many views. Your gut reaction may be to pull budget from the 8,000 page, but after doing so you see a dramatic drop in conversions.
After pulling up the numbers for both of your sales pages, you realize that the one with all the views was actually not performing well on a deeper level — the average page viewer only stuck around for a few seconds and didn’t scroll down the page at all. They also didn’t convert. You were surprised to find that the other page, however, had almost all unique views, and the average time on page was 116 seconds — long enough to make it through the content on your page and convert.
This scenario goes for any page: Just because it’s getting lots of traffic doesn’t mean it’s the right kind. There are several things that could be off — you’re targeting the wrong audience, your headline or description could be misleading, etc. Bottom line, in order to figure out which pages are really working, you have to dig a little deeper.
Data Myth 5: Cost per acquisition tells you how well your campaigns are performing
Earning new customers can be expensive, so most marketers will jump at any chance they get to lower their cost per acquisition (CPA). The problem with this? CPA alone only tells you half the story.
What’s the other half of the story?
While a low CPA is a good sign, knowing what customers do after converting is actually key.
This is where looking at customer lifetime value (CLV) comes into play. Let’s say you have two active marketing campaigns running. Campaign one has a higher CPA than campaign two (meaning it costs more to earn each customer), but before making any decisions you decide to look further into the numbers.
After digging around, you discover that while campaign one was initially more expensive for recruiting customers, those particular customers tend to spend considerably more on your brand and are way less likely to churn than the ones who converted through the lower CPA campaign. Those customers also refer more new customers to you.
You realize that the campaign with the higher CPA pays off because it attracts customers with a higher CLV. In other words, it leads to more sales and higher revenue for your business.
Regardless of the area of your marketing you’re looking to optimize, being able to investigate past the surface level into your marketing metrics is key to working towards the results you’re really after.