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Understanding Data Metrics & The Common Mistakes to Avoid
As digital marketing professionals, a popular saying we hear a lot is “data is king!”. It is true that without data, all we can do is guess where we stand and have inaccurate insights. But we should also consider this – that while data is a great tool, it can also fool us.
With unprecedented amounts of data available to us, we can get lost in understanding what that data actually means and what we should do with it. Who among us hasn’t assembled data from Facebook Ads, Google Ads, Bing Ads, and a sprinkle of some Hotjar or SEMrush, and then had a sudden feeling of being overwhelmed while trying to make sense of it all? That’s why we’re here; let’s find out how to avoid getting the wrong conclusions from data and how to make data work for us.
Table of Contents
Metric Misconceptions
My humble proposal is this, look at each set of metrics as a passage leading to a better understanding of its meaning rather than an “end-all-be-all” answer. On that note, let’s examine some misconceptions about specific metrics and how to avoid those pitfalls.
Lower CPC = Good
It seems obvious that digital marketing is about getting clicks, and ‘the cheaper, the better’, right? Wrong! Achieving lower CPC means you get a click for cheaper, but the end goal for a business is never the clicks. What if the clicks you’re getting are irrelevant? Are these clicks done by potential customers? These questions help us put the Cost-Per-Click metric in a better perspective.
High Impression Share = Positive
The impression share metric gives us a glimpse into a user’s search results on Google. The higher it is, the higher the percentage of searches for the keywords we are targeting that show our ads. That may seem like a good thing; after all, we want our ads to show, but when and to who?
It’s important to consider that while this metric is high, it could mean the chosen keywords are irrelevant and cheap, meaning our ads won’t garner many clicks or at least relevant ones that could drive conversions.
Data will help us greatly when everything is put together in order to tell a larger story- one that is easily and intuitively understood.
We could also have a high impression share % because we are willing to spend a higher budget for specific keywords (using our campaign budget, a keyword’s max CPC, etc.) more than our competitors and even more than we actually should be spending at all. Bidding isn’t about one-upping all prices and winning bidding wars. It’s about knowing how much we are willing to spend for a keyword and at what point we would rather let someone else outbid us.
High Conversion Rate = Highest Priority
Conversion rates show the percentage of interactions (such as impressions) that lead to a click.
We all want our target audience to see our ad, forget any other ads exist and click immediately.
Let’s consider how that could also be a bad thing. When comparing current data with past data and seeing a much higher CTR % now than before, does that mean it’s doing better now? Maybe so- in a world where our ads, audiences, keywords, and any other factor stays in place forever; but in reality, things change constantly.
A higher CTR could also be achieved by bidding less on keywords, possibly making our volume more effective. With digital marketing, we must always combine efficiency with volume while understanding that, in many cases, one comes in favor of the other. Therefore, put the account/business strategy first, and be willing to enter the fray for “generic keywords”. The CTR might not be as impressive as you’re accustomed to, but you’ll watch your revenue improve greatly if done correctly.
Using Metrics for Storytelling
These three examples of metric misconceptions can be quite telling when put in different lights and contexts. So, how do we use that to our advantage? Data will help us greatly when everything is put together in order to tell a larger story- one that is easily and intuitively understood.
Looking at the difference:
“Our CPC for our Scented Candles campaign in Toronto has lowered significantly on mobile during December”
VS
“Our campaign for Scented Candles in Toronto has become increasingly more effective in targeting the right audience”
*This claim is backed by the lower CPC, higher impression share, a higher CTR, average time on site, conversion rate, and average order value*
What is the difference between these two statements? The first statement tells us about the metrics, while the second tells us what those metrics actually mean so that we can clearly see what needs to be done and then move on to how to do it. Thats how you use your data to look at meaningful trends and results to help tell you a story. From there, try to create a hypothesis and see if relevant metrics support it. Most of the time, not all relevant metrics will point in the same direction. You could see an increase in CTR and a lower conversion rate, which could be explained if you look at it realistically and try to tell a nuanced story.
Making Decisions Based on Metrics
Seeing as metrics are context-based, making decisions based on them can sometime feel like guessing. That’s exactly why the process of testing is so important. If our hypothesis, for example, is that we sacrificed ROAS for a higher volume, we could try and make our adjustments more nuanced. If you were to add keywords, could see which ones affected the ROAS the most; look for a common theme and try to see what happens without those new keywords only.
Final Thoughts
Data is pretty much unlimited, and so are the questions needed to understand it. That’s why a marketer must stay as curious and attentive as possible. Only by taking data and creatively disecting the possible meanings behind it, can we make the right conclusions, take the right actions, and achieve our results. If you struggle with you campaign data and understanding metrics, let the professional’s at Adcore help you out! Our PPC experts have years of experience and can take your campaigns to the next level- for more information, click here!
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