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Keywords are as important to your PPC campaigns as oxygen is to your body or gasoline is to your car. Your campaigns run on keywords. If your keywords are lacking, then your campaigns start to sputter and struggle to drive the performance you need from your PPC strategy
The importance of keywords is not lost on PPC managers. You likely spend an enormous amount of time researching, planning, analyzing and adjusting your keyword targets to stay relevant to audiences and maximize the ROI of your PPC campaigns.
A significant amount of time needs to be dedicated to properly analyzing keywords because there are so many different ways to measure them. You need to evaluate each potential target to determine the value and potential profitability of every keyword.
Not to mention, keywords are constantly changing. It is a common pain point for PPC marketers to manage the continuous shifts, trends and other changes to keyword performance. If you aren’t staying on top of these ups and downs, then you could be missing out on rising keyword stars. Even worse, you could be wasting your valuable ad budget on low performing keywords.
One of the ways to make keyword research, planning and analysis more efficient is to use charts and other aids to visually depict the data. This discussion will look at scatter plot examples and how these charts can help you analyze your keyword data and select better targets in less time.
Data is incredibly messy, especially when it is unfiltered and unstructured. That’s why we use spreadsheets to collect and organize the raw data into rows and columns. While this organization is better than having a mess of data points, it still falls short.
As your spreadsheets grow in size, a phenomenon occurs called data fatigue, or data paralysis. Essentially, this is an overload of numerical or text data. It’s that feeling when you open up a large spreadsheet and are met by a giant wall of numbers.
No matter how familiar you are with interacting with sheets and data, it takes your brain a lot to translate all of the numbers and text information into signals that it can actually process and use.
Your brain prefers to interact with visuals because they are easier to analyze. For example, imagine describing your house, or even just the room you’re sitting in, to a complete stranger. It would take quite a lot of time to communicate every detail. And, by the end of your description, they’d still have only a vague idea of what the environment actually looked like.
However, if they saw a photo, it would take micro-seconds for their brain to process the image. They know what the space looks like the moment they see it.
The same is true of your keyword research. Your spreadsheets and tables do tell you what’s going on in your campaigns, but the format is not as efficient as charts. You have to analyze the numbers for yourself, which is much slower than a chart showing you what’s happening. As soon as you see it, you get it.
Now that we’ve touched on why PPCexpo charts have a place in keyword research, we can begin investigating the specific benefits that they bring to the table.
As we just covered, charts are useful because they allow you to process keyword data at a much faster rate than spreadsheets. There is actually some science to back this up. According to research, the brain is capable of processing visual information 60,000 times faster. It also retains visual data better than text or numbers.
Speed is powerful and extremely valuable when managing your keywords. If you can realize a keyword opportunity quickly, you can capitalize before any of your competitors. This means lower costs, higher impression share and more.
Similarly, when a keyword starts to decrease in value, quickly identifying this change can allow you to swiftly allocate your budget elsewhere. This dramatically reduces your wasted ad spend, thereby improving ROI.
PPC management is rarely a one-person effort. You may have team members, stakeholders, clients or other individuals that are invested in the success of your Google Ads efforts. Thus, they may be curious about current keyword targets and what sort of improvements or changes have occurred lately.
That said, these individuals are not always familiar with PPC metrics or comfortable interacting with campaign data. Asking them to look at a spreadsheet of keyword data is like asking someone to follow directions in a foreign language. They might get to the destination, but it’s going to take them a lot of time.
You need to make the information and the insights accessible and engaging to others. Charts that visually present the numbers achieve this. Again, it’s about visual information being more familiar and easier on the brain. When people understand the information you’re communicating, it is easier to collaborate and strategize together.
Every time you select new keyword targets, adjust match types, restructure ad groups or adjust bids, there is a result. You need to be able to recognize this result because it will help you understand whether the change you made was positive or negative.
The results of the changes you make are not always immediate, nor are they so significant that it is easy to recognize in a spreadsheet. Sometimes, you need to see the change to appreciate and understand its impact.
By comparing pre-change and post-change charts, you’ll see how any edits you made have affected performance for better or worse.
There are hundreds of thousands of potential keyword targets that relate to your business, website and products or services. Even if you have a small business, there are volumes of search keywords that could relate to your company and connect you to valuable customers.
PPC charts are not just useful when analyzing the performance of your existing keywords, but also researching new potential targets. You can use charts to compare different keywords in terms of expected CPC values, search volume and other important metrics when assessing keyword value.
A scatter plot, also referred to as a scatter diagram or x-y graph, is a type of chart that is designed to express the relationship between two variables. Data points are placed along x and y axes. Typically, the x-axis reflects your independent variables, while the y-axis is responsible for dependent variables. The independent variable is the control parameters that influence the behaviors of the dependent variables. However, in some scatter plots, you’ll find that both axes are expressing independent variables.
This chart gets its name because when data is plotted along these two axes, it looks scattered. Where along each axis the data point lies will demonstrate its performance for the two variables and may express a correlation between the two variables.
For instance, if you plotted highway accidents and speed of drivers in a scatter plot, you’d quickly see that as speeds increase, so do accidents.
Here’s a PPC keyword example: if you plotted keywords in a scatter plot chart by search volume and CPC, you’d see that as search volumes increase, so do CPC values. This is because more search volume often attracts attention from more advertisers. Thus, there are more accounts bidding on the keywords, hence the higher CPC.
When you plot keyword data in this fashion, you can discover interesting patterns, clusters and other correlations that can help inform your strategies and allow you to make smarter decisions regarding which search words you target.
In this section, we’ll look at all of the types of correlations that occur in scatter plot charts and what they mean. This will help you really appreciate the discoveries and insights that you can obtain when working with this type of PPC chart.
A correlation occurs between two variables when the value of one of them is somehow associated with the value of the other, such as car driver speed increasing the number of highway crashes. When you see a pattern in how the data is scattered, it is typically a sign of a correlation.
When reading a scatter plot chart, it’s important to read from left to right, same as the words on this page. If the pattern trends up, the correlation is positive. A downward pattern is a negative correlation. It’s worth mentioning that not every scatter plot will express a correlation or pattern.
Furthermore, the strength of the relationship between the two variables can be described as weak, moderate or strong. This creates a number of correlation types, such as:
Here is what each of these six correlations look like:
Let’s break down what each correlation in these scatter plot examples is showing with the y-axis variable being keyword search volume and the X-axis expressing average CPC.
This is what we expect to see from a scatter plot chart correlating search volume and average CPC. As the popularity of a keyword goes up, so does the competition for the term. More competition equals higher CPC.
If you have a sizable budget, then you can tackle the highest search volume keywords in the upper right, even though they have a high cost. Conversely, if you have less budget, you would try to target keywords in the middle of the chart. These keywords are decently popular and don’t cost too much.
Despite the “negative” label, with the two variables of cost and search volume in these scatter plot examples, the chart would actually mean that you have a solid cluster of profitable keywords. Any data point in the upper left represents a keyword with high search volume and low costs.
However, the data points in the bottom right are keywords that you definitely want to avoid. These keywords have very low volume but are high in CPC. This is a recipe for wasted ad spend!
When there is no correlation in the chart, the scatter will be spread out with seemingly no pattern or trend occurring. There will be data points high, low, left and right. This is usually a sign that there is no direct connection between the two variables.
That said, this does not mean that the chart has no value. No-correlation scatter plots are great for identifying outliers and recognizing useful clusters. Again, with the variables of cost and search volume, any data points in the upper right are extremely valuable keyword opportunities.
A non-linear correlation means that there is a relationship between the two variables, but it is not linear. In other words, the data relationship doesn’t occur in a straight line, but rather a curved one.
If you were looking at keyword search volume by time, instead of cost, this scatter plot could help you identify keywords that shift in popularity over time, whether in a positive or negative direction. For example, a summer seasonal keyword would have a curve up in the beginning months of summer, followed by a downward curve once the fall season hits.
There are many PPC charts available to marketers, especially if you’re using a tool like ChartExpo with its library of over 80 charts to choose from. The wide range of options can sometimes make it difficult to know which chart is best to showcase the given data that you’re working with.
You can access the ChartExpo for Excel from here
Here are the times when using a scatter plot chart is your best strategy:
There are also cases where using a scatter plot chart is not recommended.
Along with when to use a scatter plot, it’s also vital that you understand the pros and cons of this type of chart.
Pros:
Cons:
*You can track more than one dependent variable in a scatter plot. However, when you plot the points of each dependent variable, you need to change the color or shape of the points. Otherwise, you won’t be able to tell one variable data from the other.
There are three primary factors that affect the value of a keyword. These are critical variables that will be part of most, if not all, of your keyword scatter plots.
Essentially, these three metrics are the biggest factors in determining whether a keyword is good or not. Tracking these variables in a spreadsheet can be tedious and clunky. That’s where the scatter plot comes in handy.
Consider the following data table for a clothing store selling blue jeans:
It’s not immediately apparent which keywords are most valuable. You really have to work row by row analyzing each keyword’s volume and CPC and then comparing it to the others on the list. When you have just 12 keywords, as per the example, this isn’t the biggest inconvenience, but imagine having hundreds or even thousands of potential keyword targets?
Now, let’s look at the same information on a scatter plot. This scatter plot example was created with ChartExpo for Google Sheets and Excel.
With this chart, you can identify potential keyword opportunities much faster. You can quickly see keywords that share both a high search volume and a moderate-to-low cost. That said, you still need to consider relevancy.
For instance, the keyword “navy blue” seems like the perfect target because it has extremely high search volume and very minimal costs. However, it may be too generic for someone selling blue jeans.
You can access PPCexpo Keyword Planner from here
PPCexpo Keyword Planner was created for the professional search marketer that wants unmatched value, productivity and intelligence from their keyword planning tool. The PPCexpo tool offers several unique features that competing software solutions don’t provide their users.
Not only does it show you tabular keyword data and related terms for anything you enter into Google, but it also gives you scatter plot examples of the same data. You can also use PPCexpo Keyword Planner to measure similarities between keywords and how they are distributed on the XY-axes.
Here is what PPCexpo Keyword Planner returns when you search “skin care clinic” in Google.
Every search will display a tabular data view for the related keywords. From there, you can click the chart tab, which will visualize the data as a scatter diagram. This is an example of what this chart looks like with the PPCexpo Keyword Planner tool.
You’ll notice that the upper left quadrant is highlighted green. That’s because these are the keywords with high search volume and low costs. Any keyword that falls in this green highlighted area is a great opportunity for your campaigns.
Here is a quick recap of the features that PPCexpo Keyword Planner offers:
Any time you begin to consider using a new PPC marketing tool, you have to consider the costs. How big of an investment does the tool require and will the value provided by the software offset these costs?
The good news is that PPCexpo Keyword Planner has a free version that allows you to research keywords at no cost. With this version, you’ll receive 500 credits each day. One credit is equivalent to one keyword. Thus, you can receive data on 500 keywords every day for free.
For large accounts that require more than 500 daily keywords, you can purchase additional credits directly in the PPCexpo Keyword Planner tool. The pricing breakdown for credits are as follows:
If you have unique keyword needs or want more than 250,000 credits, you can contact PPCexpo directly.
Still have questions about how to use scatter plots? This section should clear up any remaining confusion or uncertainty about these charts and how they can improve your keyword research.
When we discussed the different types of correlations, there were three primary types of scatter plots.
You can also have a non-linear correlation, where the data points follow a curve, instead of a straight line. However, this is a special case correlation that will only be seen in very specific types of data.
It’s worth noting again that just because the correlation is positive, does not necessarily mean that it is a good thing. Similarly, a negative correlation isn’t always a bad thing. These positive and negative distinctions are just used to describe the direction that the data trend-line is traveling.
It all has to do with the variables you’re measuring and the data that you’re working with.
Scatter plots are used any time that someone wants to observe and test a relationship between two variables like we saw in above analysis of keyword research.
Every point in a scatter diagram shows the X-Y values of that particular item. The collective of all of the dots and their distance and relation to one another shows the patterns, outliers and other useful details that help you understand how the two variables connect to one another.
Reading a scatter plot is very easy. It’s arguably the easiest type of chart to read because it is no different from the XY graphs that you studied in math class. That said, it’s probably been awhile since you had to plot points along x and y axes.
To refresh your memory, here are a few tips to keep in mind when reading a scatter plot chart.
*In the case of PPCexpo Keyword Planner, this may not be true because search volume and CPC are both independent variables.
Throughout this article, we’ve looked at a lot of scatter plot examples. One thing remains true throughout all of them: they are extremely effective! This is especially true when analyzing keyword data.
Don’t waste your time analyzing every row of your keyword data spreadsheet manually, working line by line. PPCexpo Keyword Planner not only provides you with important keyword data right from Google, but it also charts each term on a scatter plot.
You’ll immediately see which keyword opportunities have the most and least potential. Considering how often you perform keyword research activities, this simple yet effective approach could save you hours every week.
Use scatter plots in your keyword research to optimize your time and accomplish more.
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