If a picture says a thousand words, a chart says ten thousand.
In the digital age, data is created at an increasing rate. Thus, data visualizations and charts are no longer just tools used in business meetings.
They are practical and necessary tools for conveying complex ideas and concepts without words or raw numbers. This is why data visualizations and charts are everywhere now.
In this discussion, we’ll look at various double y-axis charts that can be used for marketing. For each chart type, we’ll answer the following questions:
We’ll also discuss how to make a graph with two Y-axis in Excel but first learn about the benefits of using a Double Y-Axis chart. Let’s begin!
Here’s an example of a double Y-axis chart:
You can also create such chart by installing add-in in your spreadsheet app by clicking below.
In the chart above, two different KPIs are being compared. Even though each data has dramatically different scales, the double Y-axis can express both at the same time.
This allows you to compare data in a completely different way. Many different charts use this double-axis design. These various visualizations can lead to new discoveries.
This part of the guide teaches you how to create charts with 2 Y-axis in Excel using ChartExpo add-on and how each double Y-axis chart works.
Specifically, we’ll cover these 4 charts:
In this section, you’ll also learn about different chart examples available in Excel thanks to the ChartExpo add-in.
This is a free as trial add-in that expands Excel’s existing charting options with around 80 new selections. Many of the visualizations included in ChartExpo are designed specifically with marketers in mind.
ChartExpo is the best tool to show your data in ways that immediately bring trends and insights into vision. Insights are the driving force behind change and growth in the business world.
This section will outline how to make a graph with two Y-axis in Excel using the ChartExpo add-in. The Dual Axis Line Chart is a prime example of why two axis are better than one!
As discussed earlier, the Dual Axis Line Chart is great for comparing two data sets with very different ranges. This frequently happens in marketing. Imagine comparing your clicks to your conversions. You may have 1,000 clicks and only a handful of conversions.
With the Dual Axis Line Chart, you can compare each trend line’s relative values, despite this imbalance in data ranges.
To reiterate, two axis allow you to compare data with two very different ranges. This enables you to illustrate the relationship between these two variables without allowing these different ranges to skew the data.
There are many metrics in PPC marketing that share relationships, yet have very different data ranges, such as:
Comparing these metrics will help you better understand your campaigns. The Dual Axis Line Chart allows you to include each data set in one chart.
To make any graph with two Y-axis in Excel, you need to start with a spreadsheet. ChartExpo will then use this sheet to fill in the blanks of the chart.
For example, Wilma wants to compare the CPC to CTR for the last 24 hours in her campaign.
To do this, she prepared the table as shown below: You must know that CPC is in dollars and CTR is in percentage.
| Hour of Day | CPC | CTR |
| 0 | 22.23 | 9.1 |
| 1 | 19.87 | 8.2 |
| 2 | 18.22 | 7.6 |
| 3 | 27.67 | 7.3 |
| 4 | 22.7 | 8.5 |
| 5 | 15.76 | 8.4 |
| 6 | 16.85 | 8.6 |
| 7 | 17.54 | 9.2 |
| 8 | 16.14 | 8.6 |
| 9 | 16.33 | 8.7 |
| 10 | 16.43 | 8.9 |
| 11 | 16.34 | 8.5 |
| 12 | 16.21 | 8.7 |
| 13 | 16.52 | 8.9 |
| 14 | 16.42 | 8.9 |
| 15 | 16.17 | 9 |
| 16 | 15.57 | 8.6 |
| 17 | 16.48 | 9 |
| 18 | 16.34 | 8.8 |
| 19 | 14.99 | 8.9 |
| 20 | 17.26 | 9.8 |
| 21 | 13.67 | 8.9 |
| 22 | 12.32 | 9.3 |
| 23 | 11.28 | 8.6 |
Creating A Dual Axis Line Chart With ChartExpo:
To get started, Wilma will click on INSERT from the top toolbar in Excel.
From the resulting toolbar, she’ll click the down arrow next to My Apps. Then, the ChartExpo™ for Excel option will appear.
It’s important to note that these steps assume you have already downloaded the ChartExpo add-in for Excel.
If you haven’t already done this, click here to download the ChartExpo add-in for Excel.
Once you click on the ChartExpo option, it will open the add-in. The first screen you’ll see gives you the opportunity to find lots of charts available.
There is also a search bar that you can use to look up any visualization you want to use directly. In this case let’s find dual axis line chart.
You can click on that, you can paste the data table in the Excel sheet Once you’ve selected the Dual Axis Line Chart, you want to press Create Chart From Selection. This will use your spreadsheet to produce a chart.
Based on the example spreadsheet of Wilma’s data, here is what the visualization would first look like:
But above chart is not showing the data provide in the table reason is this visualization by default is showing percentag of data. There are few properties which you will tweak to make the chart awesome.
You can select Value Based and click on Apply button to see the actual data.
Next step is to put the lables and on each axis, put headings and provide dollar signe and pecentage as prefix and post fix on the axis. All these properties you can find by click on Edit Chart button.
You can also create the visualization on your data by installing ChartExpo library for your desire tool.
The first thing to note with this chart is how similar the two trend lines are. The Dual Axis Line Chart immediately shows Wilma the relationship these two metrics share.
From there, Wilma can begin looking hour-by-hour for interesting trends or anomalies.
The big spike in CPC around hour 3 is the most obvious change in the data. This is also the point where CTR is at its lowest. This could signal a hyper-competitive type slot where costs are high and performance is lacking.
Wilma may want to pause her campaign for this period!
For the rest of the day, the data remains pretty normal. Around hour 20, there is a notable increase in both CPC and CTR. This may be a time that Wilma wants to investigate further. Even though her clicks are costing slightly more, she sees a promising rise in CTR.
A Dual Axis Line Chart allows you to compare two values, but a Multi-Axis Line Chart gives you the opportunity to compare more than two.
This means you are comparing 2 or more values with differing scales. Thus, each data set needs its own Y-axis.
Since this is a line chart, it’s helpful to compare these differing values over a stretch of time.
In marketing, there are a lot of metrics that are relative to one another.
For example, if your ad doubles its impressions or ad views, you should see a similar spike in clicks. After all, more people seeing your ads means more potential clicks.
In turn, this also creates more conversions. If 100 people click your ad and 5 converts, then it stands to reason that 1,000 clicks will generate approximately 50 conversions.
However, each metric has a very different scale. You may have 2,000 impressions, 100 clicks, and only 5 conversions. The Multi Axis Line Chart makes it possible to graph all of this data in a single visualization.
Daphne is a marketing manager who wants to see how her ads perform in terms of impressions, clicks, and conversions.
| Date | Clicks | Impressions | Conversions |
| 5/1/2022 | 1483 | 18766 | 55 |
| 5/2/2022 | 1313 | 18788 | 57 |
| 5/3/2022 | 1345 | 18743 | 60 |
| 5/4/2022 | 1256 | 18788 | 63 |
| 5/5/2022 | 1304 | 16406 | 59 |
| 5/6/2022 | 1407 | 17765 | 60 |
| 5/7/2022 | 1498 | 20532 | 65 |
| 5/8/2022 | 1597 | 20016 | 58 |
| 5/9/2022 | 1587 | 20122 | 61 |
| 5/10/2022 | 1483 | 20125 | 64 |
| 5/11/2022 | 1565 | 23783 | 59 |
| 5/12/2022 | 1587 | 22942 | 57 |
| 5/13/2022 | 1599 | 23127 | 70 |
| 5/14/2022 | 1620 | 24548 | 78 |
| 5/15/2022 | 1788 | 23448 | 80 |
| 5/16/2022 | 1768 | 23408 | 91 |
| 5/17/2022 | 1987 | 25473 | 89 |
| 5/18/2022 | 1939 | 24959 | 81 |
| 5/19/2022 | 1987 | 23710 | 86 |
| 5/20/2022 | 1964 | 24221 | 98 |
| 5/21/2022 | 1740 | 23317 | 89 |
| 5/22/2022 | 1748 | 24431 | 85 |
| 5/23/2022 | 1876 | 23785 | 79 |
| 5/24/2022 | 1826 | 22247 | 83 |
| 5/25/2022 | 1920 | 23851 | 83 |
| 5/26/2022 | 1886 | 24875 | 90 |
| 5/27/2022 | 1769 | 24015 | 94 |
| 5/28/2022 | 1869 | 25689 | 104 |
| 5/29/2022 | 1823 | 24416 | 99 |
| 5/30/2022 | 1899 | 25874 | 114 |
| 5/31/2022 | 1924 | 26146 | 98 |
So in the same way as previously steps are shown to use ChartExpo. We will also use in the same way but this time will select Multiaxis line chart and it will appear as shown below:
Final look will be like this:
You can also create this chart with your own data by installing this library by clicking below:
With this data visualization, Daphne can see how well her ads perform (or how well they aren’t performing) at each stage of the ad process.
Because of these three metrics’ relative nature, it is normal that they follow a similar trend pattern. It would be unlikely that conversions would spike when clicks and impressions are at their lowest.
The real exciting point in this example Multi Axis Line Chart is where the impressions and clicks trend lines intersect. This reflects a period of good CTR and not-so-good CTR.
Daphne may want to investigate this period further to see what changed.
The Pareto Vertical Chart is built on the idea that the majority of results come from a small minority of your efforts. In PPC, for example, most of your clicks and conversions will come from only a handful of keywords.
This is also known as the 80-20 rule — 80% of outputs are created by 20% of inputs. (It is not always a perfect 80-20 distribution).
Here’s an example of a Pareto Vertical Chart showing how a budget is being spent across different keywords. Here is the data below:
| Keyword | Consumed | Budget |
| mobile | 510 | 540 |
| smartphone | 545 | 550 |
| phones | 99 | 115 |
| mobile phones | 533 | 572 |
| cellphones | 85 | 93 |
| unlock phone | 63 | 88 |
| mobile shop | 485 | 497 |
| free phones | 80 | 115 |
| prepaid phones | 470 | 489 |
| cheap phones | 67 | 87 |
By creating this chart with ChartExpo following look will appear.
You can create the above chart by install ChartExpo libray by clicking below for your desrire tool.
On the surface, the Pareto Vertical Chart looks like a typical bar chart. The primary difference is the cascading line across the bars. This represents the cumulative total of each item.
In this example, the line shows how much each keyword contributes to the total budget. As the most expensive keyword, “mobile” spends 27.1% of the total budget. Meanwhile, the smaller bars represent just ~5% of the budget.
With this chart, you can see how much each small piece contributes to the larger whole.
The best way to use a Pareto Vertical Chart is to identify vital versus useful opportunities in your campaigns.
Vital opportunities are the 20% of inputs that create the majority of your results.
Useful opportunities are the remaining 80% of inputs that, while not as vital, still produce some value.
When you can identify the components of your Google Ads account generating the majority of your results, you can optimize your strategies for these vital few components.
This ensures that you’re spending your time and budget on the strategies, keywords, campaigns, ad groups, etc., with the highest potential. This is a great way to maximize your productivity as a manager.
Every campaign involves multiple keywords. On the surface, it isn’t always easy to gauge each one’s performance in terms of how it contributes to the whole. This is true for budget, clicks, conversions and almost any other metric.
In short, you know that some keywords are better than others. The Vertical Pareto Chart shows how much better one keyword is to the next. This chart is also great because it lists your keywords in order of significance.
This allows you to identify your most and least impactful selections immediately. Then, you can optimize your bids accordingly.
In marketing, you have many examples of multiple metrics or data points contributing to a larger whole.
This is not unlike what we saw with the vertical Pareto Chart, where multiple keywords made up the total budget for that campaign.
This parts-and-whole relationship is prevalent in PPC. There are times where the Pareto Chart isn’t the best way to display the information. An alternative method is the Component Trend Chart.
This chart is handy when looking at how a change to one component affects the whole.
The best use for the Component Trend Chart is to analyze Quality Scores.
When managing a campaign, paying attention to Quality Scores is absolutely vital to your campaigns’ success and performance.
High Quality Scores can improve your ad ranks, lower your costs, improve your clickthrough rates (CTR) and create an overall healthier Google Ads account.
Google uses multiple factors to determine Quality Scores. Three of the most significant factors are landing page experience, ad relevance and expected CTR.
The Component Trend Chart is helpful to see how changes in these areas could positively or negatively affect your overall quality score.
In this example, Oliver is a manager that wants to improve his Quality Scores. He understands the significant impact that improving these ratings will have on his overall account performance.
Throughout two months, Oliver works hard to improve his landing page experience, ad relevance and CTR. He tracks his quality ratings for each category throughout this period and enters the data into a spreadsheet.
This is what Oliver’s data looks like:
| Date | Relevancy | Status | Quality Score |
| 5/1/2022 | Ad Relevance | Above Average | 4.9 |
| 5/1/2022 | Ad Relevance | Average | 4.3 |
| 5/1/2022 | Ad Relevance | Below Average | 3.1 |
| 5/1/2022 | Exp. CTR | Above Average | 5.6 |
| 5/1/2022 | Exp. CTR | Average | 3.6 |
| 5/1/2022 | Exp. CTR | Below Average | 1.8 |
| 5/1/2022 | Landing Page Exper. | Average | 5.8 |
| 5/1/2022 | Landing Page Exper. | Below Average | 3.7 |
| 5/2/2022 | Ad Relevance | Above Average | 4.9 |
| 5/2/2022 | Ad Relevance | Average | 4.3 |
| 5/2/2022 | Ad Relevance | Below Average | 3.1 |
| 5/2/2022 | Exp. CTR | Above Average | 5.7 |
| 5/2/2022 | Exp. CTR | Average | 3.6 |
| 5/2/2022 | Exp. CTR | Below Average | 1.8 |
| 5/2/2022 | Landing Page Exper. | Average | 5.9 |
| 5/2/2022 | Landing Page Exper. | Below Average | 3.7 |
| 5/3/2022 | Ad Relevance | Above Average | 5.1 |
| 5/3/2022 | Ad Relevance | Average | 4.3 |
| 5/3/2022 | Ad Relevance | Below Average | 3.1 |
| 5/3/2022 | Exp. CTR | Above Average | 5.7 |
| 5/3/2022 | Exp. CTR | Average | 3.6 |
| 5/3/2022 | Exp. CTR | Below Average | 1.8 |
| 5/3/2022 | Landing Page Exper. | Average | 6.4 |
| 5/3/2022 | Landing Page Exper. | Below Average | 3.7 |
| 5/4/2022 | Ad Relevance | Above Average | 5.1 |
| 5/4/2022 | Ad Relevance | Average | 4.4 |
| 5/4/2022 | Ad Relevance | Below Average | 3.1 |
| 5/4/2022 | Exp. CTR | Above Average | 5.8 |
| 5/4/2022 | Exp. CTR | Average | 3.6 |
| 5/4/2022 | Exp. CTR | Below Average | 1.8 |
| 5/4/2022 | Landing Page Exper. | Average | 6.3 |
| 5/4/2022 | Landing Page Exper. | Below Average | 3.8 |
| 5/5/2022 | Ad Relevance | Above Average | 5.1 |
| 5/5/2022 | Ad Relevance | Average | 4.5 |
| 5/5/2022 | Ad Relevance | Below Average | 3.2 |
| 5/5/2022 | Exp. CTR | Above Average | 5.7 |
| 5/5/2022 | Exp. CTR | Average | 3.6 |
| 5/5/2022 | Exp. CTR | Below Average | 1.8 |
| 5/5/2022 | Landing Page Exper. | Above Average | 6 |
| 5/5/2022 | Landing Page Exper. | Average | 6.4 |
| 5/5/2022 | Landing Page Exper. | Below Average | 3.8 |
| 5/6/2022 | Ad Relevance | Above Average | 5.2 |
| 5/6/2022 | Ad Relevance | Average | 4.6 |
| 5/6/2022 | Ad Relevance | Below Average | 3.2 |
| 5/6/2022 | Exp. CTR | Above Average | 5.7 |
| 5/6/2022 | Exp. CTR | Average | 3.6 |
| 5/6/2022 | Exp. CTR | Below Average | 1.7 |
| 5/6/2022 | Landing Page Exper. | Above Average | 6 |
| 5/6/2022 | Landing Page Exper. | Average | 6.8 |
| 5/6/2022 | Landing Page Exper. | Below Average | 3.8 |
| 5/7/2022 | Ad Relevance | Above Average | 5.4 |
| 5/7/2022 | Ad Relevance | Average | 4.7 |
| 5/7/2022 | Ad Relevance | Below Average | 3.3 |
| 5/7/2022 | Exp. CTR | Above Average | 5.7 |
| 5/7/2022 | Exp. CTR | Average | 3.6 |
| 5/7/2022 | Exp. CTR | Below Average | 1.7 |
| 5/7/2022 | Landing Page Exper. | Above Average | 7 |
| 5/7/2022 | Landing Page Exper. | Average | 6.7 |
| 5/7/2022 | Landing Page Exper. | Below Average | 3.9 |
| 5/8/2022 | Ad Relevance | Above Average | 5.6 |
| 5/8/2022 | Ad Relevance | Average | 4.7 |
| 5/8/2022 | Ad Relevance | Below Average | 3.4 |
| 5/8/2022 | Exp. CTR | Above Average | 5.7 |
| 5/8/2022 | Exp. CTR | Average | 3.6 |
| 5/8/2022 | Exp. CTR | Below Average | 1.6 |
| 5/8/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/8/2022 | Landing Page Exper. | Average | 6.6 |
| 5/8/2022 | Landing Page Exper. | Below Average | 4 |
| 5/9/2022 | Ad Relevance | Above Average | 5.6 |
| 5/9/2022 | Ad Relevance | Average | 4.9 |
| 5/9/2022 | Ad Relevance | Below Average | 3.4 |
| 5/9/2022 | Exp. CTR | Above Average | 5.7 |
| 5/9/2022 | Exp. CTR | Average | 3.6 |
| 5/9/2022 | Exp. CTR | Below Average | 1.6 |
| 5/9/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/9/2022 | Landing Page Exper. | Average | 6.4 |
| 5/9/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/10/2022 | Ad Relevance | Above Average | 5.6 |
| 5/10/2022 | Ad Relevance | Average | 4.9 |
| 5/10/2022 | Ad Relevance | Below Average | 3.5 |
| 5/10/2022 | Exp. CTR | Above Average | 5.7 |
| 5/10/2022 | Exp. CTR | Average | 3.7 |
| 5/10/2022 | Exp. CTR | Below Average | 1.6 |
| 5/10/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/10/2022 | Landing Page Exper. | Average | 6.3 |
| 5/10/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/11/2022 | Ad Relevance | Above Average | 5.6 |
| 5/11/2022 | Ad Relevance | Average | 4.9 |
| 5/11/2022 | Ad Relevance | Below Average | 3.5 |
| 5/11/2022 | Exp. CTR | Above Average | 5.7 |
| 5/11/2022 | Exp. CTR | Average | 3.7 |
| 5/11/2022 | Exp. CTR | Below Average | 1.6 |
| 5/11/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/11/2022 | Landing Page Exper. | Average | 6.3 |
| 5/11/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/12/2022 | Ad Relevance | Above Average | 5.6 |
| 5/12/2022 | Ad Relevance | Average | 5 |
| 5/12/2022 | Ad Relevance | Below Average | 3.5 |
| 5/12/2022 | Exp. CTR | Above Average | 5.7 |
| 5/12/2022 | Exp. CTR | Average | 3.7 |
| 5/12/2022 | Exp. CTR | Below Average | 1.6 |
| 5/12/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/12/2022 | Landing Page Exper. | Average | 6.5 |
| 5/12/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/13/2022 | Ad Relevance | Above Average | 5.7 |
| 5/13/2022 | Ad Relevance | Average | 5 |
| 5/13/2022 | Ad Relevance | Below Average | 3.5 |
| 5/13/2022 | Exp. CTR | Above Average | 5.7 |
| 5/13/2022 | Exp. CTR | Average | 3.7 |
| 5/13/2022 | Exp. CTR | Below Average | 1.6 |
| 5/13/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/13/2022 | Landing Page Exper. | Average | 6.3 |
| 5/13/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/14/2022 | Ad Relevance | Above Average | 5.7 |
| 5/14/2022 | Ad Relevance | Average | 5 |
| 5/14/2022 | Ad Relevance | Below Average | 3.5 |
| 5/14/2022 | Exp. CTR | Above Average | 5.8 |
| 5/14/2022 | Exp. CTR | Average | 3.7 |
| 5/14/2022 | Exp. CTR | Below Average | 1.5 |
| 5/14/2022 | Landing Page Exper. | Above Average | 7.3 |
| 5/14/2022 | Landing Page Exper. | Average | 6.4 |
| 5/14/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/15/2022 | Ad Relevance | Above Average | 5.7 |
| 5/15/2022 | Ad Relevance | Average | 5 |
| 5/15/2022 | Ad Relevance | Below Average | 3.5 |
| 5/15/2022 | Exp. CTR | Above Average | 5.7 |
| 5/15/2022 | Exp. CTR | Average | 3.6 |
| 5/15/2022 | Exp. CTR | Below Average | 1.5 |
| 5/15/2022 | Landing Page Exper. | Above Average | 7 |
| 5/15/2022 | Landing Page Exper. | Average | 6.4 |
| 5/15/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/16/2022 | Ad Relevance | Above Average | 5.7 |
| 5/16/2022 | Ad Relevance | Average | 5 |
| 5/16/2022 | Ad Relevance | Below Average | 3.5 |
| 5/16/2022 | Exp. CTR | Above Average | 5.7 |
| 5/16/2022 | Exp. CTR | Average | 3.6 |
| 5/16/2022 | Exp. CTR | Below Average | 1.5 |
| 5/16/2022 | Landing Page Exper. | Above Average | 7 |
| 5/16/2022 | Landing Page Exper. | Average | 6.4 |
| 5/16/2022 | Landing Page Exper. | Below Average | 4.1 |
| 5/17/2022 | Ad Relevance | Above Average | 5.7 |
| 5/17/2022 | Ad Relevance | Average | 5 |
| 5/17/2022 | Ad Relevance | Below Average | 3.5 |
| 5/17/2022 | Exp. CTR | Above Average | 5.7 |
| 5/17/2022 | Exp. CTR | Average | 3.6 |
| 5/17/2022 | Exp. CTR | Below Average | 1.5 |
| 5/17/2022 | Landing Page Exper. | Above Average | 7 |
| 5/17/2022 | Landing Page Exper. | Average | 6.4 |
| 5/17/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/18/2022 | Ad Relevance | Above Average | 5.8 |
| 5/18/2022 | Ad Relevance | Average | 5 |
| 5/18/2022 | Ad Relevance | Below Average | 3.6 |
| 5/18/2022 | Exp. CTR | Above Average | 5.7 |
| 5/18/2022 | Exp. CTR | Average | 3.6 |
| 5/18/2022 | Exp. CTR | Below Average | 1.5 |
| 5/18/2022 | Landing Page Exper. | Above Average | 7 |
| 5/18/2022 | Landing Page Exper. | Average | 6.4 |
| 5/18/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/19/2022 | Ad Relevance | Above Average | 5.8 |
| 5/19/2022 | Ad Relevance | Average | 5 |
| 5/19/2022 | Ad Relevance | Below Average | 3.6 |
| 5/19/2022 | Exp. CTR | Above Average | 5.7 |
| 5/19/2022 | Exp. CTR | Average | 3.6 |
| 5/19/2022 | Exp. CTR | Below Average | 1.5 |
| 5/19/2022 | Landing Page Exper. | Above Average | 7 |
| 5/19/2022 | Landing Page Exper. | Average | 6.4 |
| 5/19/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/20/2022 | Ad Relevance | Above Average | 5.8 |
| 5/20/2022 | Ad Relevance | Average | 5 |
| 5/20/2022 | Ad Relevance | Below Average | 3.6 |
| 5/20/2022 | Exp. CTR | Above Average | 5.7 |
| 5/20/2022 | Exp. CTR | Average | 3.6 |
| 5/20/2022 | Exp. CTR | Below Average | 1.5 |
| 5/20/2022 | Landing Page Exper. | Above Average | 7 |
| 5/20/2022 | Landing Page Exper. | Average | 6.4 |
| 5/20/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/21/2022 | Ad Relevance | Above Average | 5.8 |
| 5/21/2022 | Ad Relevance | Average | 5 |
| 5/21/2022 | Ad Relevance | Below Average | 3.6 |
| 5/21/2022 | Exp. CTR | Above Average | 5.7 |
| 5/21/2022 | Exp. CTR | Average | 3.6 |
| 5/21/2022 | Exp. CTR | Below Average | 1.5 |
| 5/21/2022 | Landing Page Exper. | Above Average | 7 |
| 5/21/2022 | Landing Page Exper. | Average | 6.3 |
| 5/21/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/22/2022 | Ad Relevance | Above Average | 5.8 |
| 5/22/2022 | Ad Relevance | Average | 5.1 |
| 5/22/2022 | Ad Relevance | Below Average | 3.7 |
| 5/22/2022 | Exp. CTR | Above Average | 5.7 |
| 5/22/2022 | Exp. CTR | Average | 3.6 |
| 5/22/2022 | Exp. CTR | Below Average | 1.5 |
| 5/22/2022 | Landing Page Exper. | Above Average | 7 |
| 5/22/2022 | Landing Page Exper. | Average | 6.3 |
| 5/22/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/23/2022 | Ad Relevance | Above Average | 5.8 |
| 5/23/2022 | Ad Relevance | Average | 5.1 |
| 5/23/2022 | Ad Relevance | Below Average | 3.7 |
| 5/23/2022 | Exp. CTR | Above Average | 5.7 |
| 5/23/2022 | Exp. CTR | Average | 3.6 |
| 5/23/2022 | Exp. CTR | Below Average | 1.5 |
| 5/23/2022 | Landing Page Exper. | Above Average | 7 |
| 5/23/2022 | Landing Page Exper. | Average | 6.3 |
| 5/23/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/24/2022 | Ad Relevance | Above Average | 5.8 |
| 5/24/2022 | Ad Relevance | Average | 5.1 |
| 5/24/2022 | Ad Relevance | Below Average | 3.7 |
| 5/24/2022 | Exp. CTR | Above Average | 5.7 |
| 5/24/2022 | Exp. CTR | Average | 3.6 |
| 5/24/2022 | Exp. CTR | Below Average | 1.5 |
| 5/24/2022 | Landing Page Exper. | Above Average | 7 |
| 5/24/2022 | Landing Page Exper. | Average | 6.3 |
| 5/24/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/25/2022 | Ad Relevance | Above Average | 5.8 |
| 5/25/2022 | Ad Relevance | Average | 5.2 |
| 5/25/2022 | Ad Relevance | Below Average | 3.7 |
| 5/25/2022 | Exp. CTR | Above Average | 5.7 |
| 5/25/2022 | Exp. CTR | Average | 3.6 |
| 5/25/2022 | Exp. CTR | Below Average | 1.5 |
| 5/25/2022 | Landing Page Exper. | Above Average | 7 |
| 5/25/2022 | Landing Page Exper. | Average | 6.3 |
| 5/25/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/26/2022 | Ad Relevance | Above Average | 5.8 |
| 5/26/2022 | Ad Relevance | Average | 5.2 |
| 5/26/2022 | Ad Relevance | Below Average | 3.6 |
| 5/26/2022 | Exp. CTR | Above Average | 5.7 |
| 5/26/2022 | Exp. CTR | Average | 3.6 |
| 5/26/2022 | Exp. CTR | Below Average | 1.5 |
| 5/26/2022 | Landing Page Exper. | Above Average | 7 |
| 5/26/2022 | Landing Page Exper. | Average | 6.3 |
| 5/26/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/27/2022 | Ad Relevance | Above Average | 5.8 |
| 5/27/2022 | Ad Relevance | Average | 5.1 |
| 5/27/2022 | Ad Relevance | Below Average | 3.7 |
| 5/27/2022 | Exp. CTR | Above Average | 5.7 |
| 5/27/2022 | Exp. CTR | Average | 3.6 |
| 5/27/2022 | Exp. CTR | Below Average | 1.5 |
| 5/27/2022 | Landing Page Exper. | Above Average | 7 |
| 5/27/2022 | Landing Page Exper. | Average | 6.3 |
| 5/27/2022 | Landing Page Exper. | Below Average | 4.2 |
| 5/28/2022 | Ad Relevance | Above Average | 5.9 |
| 5/28/2022 | Ad Relevance | Average | 5.1 |
| 5/28/2022 | Ad Relevance | Below Average | 3.7 |
| 5/28/2022 | Exp. CTR | Above Average | 5.7 |
| 5/28/2022 | Exp. CTR | Average | 3.6 |
| 5/28/2022 | Exp. CTR | Below Average | 1.5 |
| 5/28/2022 | Landing Page Exper. | Above Average | 7 |
| 5/28/2022 | Landing Page Exper. | Average | 6.3 |
| 5/28/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/29/2022 | Ad Relevance | Above Average | 5.8 |
| 5/29/2022 | Ad Relevance | Average | 5.1 |
| 5/29/2022 | Ad Relevance | Below Average | 3.7 |
| 5/29/2022 | Exp. CTR | Above Average | 5.7 |
| 5/29/2022 | Exp. CTR | Average | 3.6 |
| 5/29/2022 | Exp. CTR | Below Average | 1.5 |
| 5/29/2022 | Landing Page Exper. | Above Average | 7 |
| 5/29/2022 | Landing Page Exper. | Average | 6.3 |
| 5/29/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/30/2022 | Ad Relevance | Above Average | 5.8 |
| 5/30/2022 | Ad Relevance | Average | 5.1 |
| 5/30/2022 | Ad Relevance | Below Average | 3.7 |
| 5/30/2022 | Exp. CTR | Above Average | 5.7 |
| 5/30/2022 | Exp. CTR | Average | 3.6 |
| 5/30/2022 | Exp. CTR | Below Average | 1.5 |
| 5/30/2022 | Landing Page Exper. | Above Average | 7 |
| 5/30/2022 | Landing Page Exper. | Average | 6.3 |
| 5/30/2022 | Landing Page Exper. | Below Average | 4.3 |
| 5/31/2022 | Ad Relevance | Above Average | 5.8 |
| 5/31/2022 | Ad Relevance | Average | 5.1 |
| 5/31/2022 | Ad Relevance | Below Average | 3.7 |
| 5/31/2022 | Exp. CTR | Above Average | 5.7 |
| 5/31/2022 | Exp. CTR | Average | 3.6 |
| 5/31/2022 | Exp. CTR | Below Average | 1.5 |
| 5/31/2022 | Landing Page Exper. | Above Average | 7 |
| 5/31/2022 | Landing Page Exper. | Average | 6.3 |
| 5/31/2022 | Landing Page Exper. | Below Average | 4.3 |
This type of chart looks at data over a specified period. In column A, Oliver will put “Date” information for each data point.
Columns B and C are called ‘SubTopic 1’ and ‘Subtopic 2.’ The first SubTopic includes Ad Relevance, Expected CTR and Landing Page Experience, while the second deals with the rating scores (below average, average or above average.)
Finally, Column D shows the actual rating scores.
Creating A Component Trend Chart With ChartExpo
Again, you’ll start by accessing the ChartExpo tool in the top bar of Excel. This time you will select Components Trend Chart from the list. You will select the data and click on Create Chart from Selection to see the results as shown below.
You can try this chart by ChartExpo for your data as well. Just click on below link to install for your desire tool.
With this Component Trend Chart, Oliver can accurately see how each change he made to ad relevance, expected CTR and landing page experience influenced his higher Quality Scores.
Ad relevance was a weak point for Oliver’s campaign. It started with a Below Average rating. Then, around Week03, Oliver improved this component, which resulted in a slight increase in Quality Score.
With ad relevance improved, Oliver worked on landing page experience in Week05. This created another uptick in Quality Score. Shortly after, he increased his expected CTR rating.
At the close of the 9 weeks, Oliver has a high, 9/10 Quality Score for his campaign. Looking at the Component Trend Chart, it’s evident that increasing ad relevance again is the next step. This will give Oliver’s campaign the extra push to get that perfect score!
The Internet has brought to view many informative, artistic, and entertaining visualizations.
As a result, audiences are more engaged and familiar with visual depictions of data than ever before. They are effective communication tools to be used internally and externally.
The challenge facing marketers is choosing the correct visualization to express data in the best way possible.
There are many different types of charts available to marketers. If you don’t choose the right one for the job, it may not effectively communicate the information.
Charts can provide a lot of value. Not only do they display the data, but they also help you see relationships between different numbers. This invites further interest or questions into the topic and deeper exploration.
Before making your chart, start by asking a question. What are you trying to prove or discover through visualization? Answering these questions will help you select the right chart to display your data.
When making your chart, simplicity is best. It’s not about impressing the viewer with your charting skills. It’s about telling the story of your data through a chart.
Remember, the goal of your visualization is to simplify the complex nature of the raw data. If you use an overly complicated chart to do this, you’ll defeat the purpose. How can you tell the story of your data using the least amount of chart objects?
You do not want to bombard your audience with too many unnecessary charting elements. These extra details distract from the intended purpose of your chart.
When you use a chart effectively, your data is brought to life. You and your audiences will see the insights right away.
ChartExpo allows you to preview how your data looks in different charts. This is an excellent feature for determining the best visualization for your data.
Data can be difficult to analyze without the assistance of visualization. There are several different metrics that each impact your performance in various ways.
To make it even more challenging, these metrics are constantly changing.
When you put the data into a chart, it is much easier to track and interpret changes. It’s not just about making the data look good; it’s about making it easier to analyze and understand.
Once you can see all of your data points in a chart, you can make better management decisions. You’ll see valuable correlations in your data and identify potentially risky outliers.
As a marketer, you have to make many decisions and you don’t have a lot of time to make them. If you wait too long, you could be missing out on valuable ways to improve performance.
Learning how to make a graph with two Y-axis in Excel is the first step in becoming a more productive marketer. With two axis, you’re able to compare and contrast multiple values in the same chart.
ChartExpo charts are already powerful tools that can help you make quick sense of your data. By adding an extra axis, you can pack even more value into every visualization you create.
ChartExpo transforms your raw data into stunning visualizations. With some of the best charts added to Excel, you’ll be able to see deeper insights in your data.
Deeper insights mean a superior competitive advantage!
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