Waking up late, spilling your morning coffee, forgetting to take your seasonal allergy pill…those are all mistakes that can throw off your day. But there’s one mistake that beats them all—spending countless hours on analytics only to realize over halfway through that you didn’t do it correctly.
The anguish of realizing you’ll have to redo all of your hard work is something that can ruin even the best day, and unfortunately, it happens too often when it comes to B2B marketing analytics.
Combining and manipulating data to find an answer isn’t easy, which is why mistakes are common. It takes only the slightest misstep or misunderstanding to approach your marketing analysis incorrectly, not because you don’t know what you’re doing, but because you’re human and it’s not an easy job.
The good news is that you’re not alone in your struggle and there are things you can do to make sure that you make fewer mistakes in the future—learn from other marketers. In this blog, we’re talking about the 12 most common B2B marketing analytics mistakes: what they are and how you can avoid them.
You never want to see a low number in your marketing analytics, unless we’re talking about unsubscribes from your email list. In almost every other situation, your gut reaction is probably something like, “Oh no! We failed.” But that’s not the case.
Low numbers aren’t always something to lament—like, as we explained above, when it comes to email unsubscribe rates. Sometimes, a low number is exactly what you want depending on the metric and it actually means you’re successful. Other times, low numbers are fantastic learning tools.
When you see a low number, it’s the ideal opportunity to figure out what isn’t working in your marketing and to guide your future efforts. Based on the low number, you can see where you need to invest more time.
For example, if your Facebook conversions rates are low, you can dig into how to improve. Or you might come to discover that certain channels don’t work well for you compared to others and so you should reinvest your efforts elsewhere.
When reporting leads, it’s easy to mix up marketing qualified leads (MQLs) and leads, but their importance is not the same.
A lead is anyone who’s filled out a form or submitted their information on your website. A marketing qualified lead (MQL) is a lead that is more likely to become a customer, based on what you believe makes a lead “qualified,” which varies company to company. Typically, an MQL is a lead from someone who has requested something like a demo, sales consultation, or price quote.
The key to avoiding this mistake is to outline exactly what constitutes an MQL—based on information from your sales team and lead scoring. From there, you can focus on nurturing and gaining more MQLs not just leads.
Similar to mixing up your leads and MQLs, you don’t want to lump all your traffic into one pot. It matters where your website traffic comes from—organic, social, referrals, search—and you need to pay attention to the source.
For example, if you have a large amount of organic search traffic, that means your SEO strategy is paying off. On the other hand, low email traffic might mean that you need to improve your email CTAs.
Pay attention to how these traffic numbers change month-over-month to determine how best to invest your marketing efforts and resources. If social media sends you the most website traffic and results in conversion rates, that’s where you want to spend time and vice versa.
Just because two metrics happen to increase or decrease similarly, doesn’t mean they’re connected. It’s entirely possible for two unrelated metrics to follow the same path for no other reason than coincidence—correlation doesn’t mean causation.
Before you assume that your increase in conversion rates is caused by your increase in blog visits, take a look at the whole picture. Did you increase CTAs in your blogs and are those links being clicked? According to Google Analytics, are blog visitors staying on your page for more than a few seconds and checking out the rest of your website? You need to find the cause before blindly assuming it exists.
As we said above, correlation is not causation, so you want to be careful about when and how you compare data. You need to compare apples to apples and oranges to oranges. Just because one webpage has more traffic, or a particular CTA has higher conversion rates than another, doesn’t mean you can make a comparison.
For example, let’s say your latest landing page has 200 visits from mobile and 150 visits from email. Does that mean mobile is better and you should invest more effort there? Not necessarily. The two channels are different—email is used as the medium to deliver a message while mobile is the device used to deliver a message. They work hand-in-hand and thus cannot be compared.
But just because you have a tool like HubSpot, doesn’t mean you’re safe. If you haven’t set up your analytics tools properly to get accurate data, none of your efforts will be worth it.
There’s nothing worse than using a high-quality analytics tool such as Google Analytics or HubSpot, only to discover that you never set up the portals correctly, so the data you’re getting is incorrect. Then, you’ll just end up making poor decisions based on erroneous information.
KeyScouts is a Certified Hubspot agency and can help with setting up all of your tools— HubSpot, Google Analytics, etc. — correctly so that the marketing analytics you perform will give you the insight you need.
A visit is when a user visits your website from an external URL. In Google Analytics, a visit ends after 30 minutes of inactivity and no matter how many web pages the visitor views, they are only ever counted as a single visit.
A page view, on the other hand, is anytime a page is loaded or reloaded. This means that a single visit can have countless page views depending on how much they explore your website.
Neither metric is better than the other, they each share different and important information. A visit can tell you how many individuals are coming to your site, while page views tell you which topics are most interesting to your audience.
Just as views and visits are different, so are internal website visits. Every day, people in your company will visit your website for their job, you should not count their visits and views in your marketing metrics. Adding their traffic to your numbers can skew your data. You need to use IP filtering to make sure your employees’ visits are not included in your data.
Just because a customer spends a lot on time on your web page doesn’t mean they’re engaged with your company. It’s all about the user experience. The visitor could be spending a lot of time on your page because it loads slowly, they can’t find what they’re looking for, or they simply left the page open and went for lunch.
Before you can claim page engagement, you need to take a good look at UX. Did the visitor scroll through the page, but not click on any links? Did they return to the home page or another page more than once? You can use heatmap software like Clicktale or Hotjar to see how your users are interacting with your website, and then start coming to conclusions.
The key to successful B2B marketing analytics is being able to report the data properly, which means you need the right visuals. There’s nothing worse than choosing the wrong type of graph or chart to represent your data.
A few tips for getting it right:
The key is to think about the end goal of your graph—what you want to communicate—then choose a graph that matches.
When you’re trying to save money, it can be tempting to pull your marketing analytics from each source directly and try to put it all together on your own. But by not using a platform like HubSpot, which connects all your efforts in one place, you’ll miss the key insights you need.
If you don’t have an easy way to see all the data, and instead you keep your data siloed in different platforms, it will be so much harder to truly comprehend where you stand.
Last, but certainly not least, you need to be able to create reports based on your B2B marketing analytics that mean something. You need actionable takeaways. If you can’t answer the questions, “What next?”, “What did we learn?”, or “What can we do better?” Then all of your analysis is for naught. Again, a marketing platform like HubSpot or Google Analytics can give you this capability.
Make sure that with every marketing analysis you perform adds value to your efforts. By avoiding these 12 common mistakes, you can ensure that your work is paying off in both the long and short term.