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# PPC Reports: How to Highlight Meaningful Metrics Using Data Visualization

Whether you’re in-house or agency, good PPC reporting is a key factor to proving the value of PPC and of the job you’re doing managing PPC

A crucial aspect of PPC reporting is data visualization. We PPC managers deal with numbers all day long – a seemingly endless stream of data that can be sliced and diced in an infinite number of ways. It’s our job to pick out the gold nuggets from all that data, and present it to the decision makers in a way that’s easy to understand.

Every PPC manager is intimately familiar with Microsoft Excel. It’s probably the most-used tool for managing and working with PPC campaigns & data. And it has a ton of built-in features that help with reporting, like charts and graphs.

If you aren't using charts in your PPC reports, they probably look something like this:

If that’s the case, stop reading now and go figure out how to use the Chart function in Excel.

Even if you are using charts, however, they’re worthless if they aren't structured properly. They make your PPC reports suck.

Data visualization is the reason charts exist. They’re supposed to make tables of numbers (like the one above) more meaningful and easier to understand and interpret at a glance. But a bad chart doesn’t do that.

### Axes Must Make Sense

Take a look at this chart, for example:

Now look at this chart:

Which one is more meaningful to you?

A good chart has x and y axes that make sense. In the first chart above, the y (vertical) axis is too compressed. There is no reason for the y axis to start at 0 when the smallest data value is obviously close to \$1,000. By starting at \$0, it flattens out the entire line so it’s more difficult to see the highs and lows – which is precisely the information a line chart like this is supposed to illustrate! That chart should start at \$500 or maybe even a larger number.

The second chart does a better job – by beginning at a number larger than 0, the data is much easier to visualize.

### Use a Second Axis

Have you ever seen a chart like this?

How many clicks did you get in April? Zero? It sure looks like it. And how does that compare with March? Do you have any clue what’s happening with clicks here?

When a chart is comparing more than one metric with diverse values, such as huge numbers and smaller numbers, or numbers and percentages, the best option is to use the second axis. To use the second axis, right-click on the data you want to put on the second axis (in this case, Clicks) and select “Format Data Series.” From there, select “secondary axis.”

When you’re done, the chart should look this:

Better, isn’t it?

### Don’t Cram Too Much In

When you’re reporting on a lot of key metrics, it can be tempting to throw them all into one chart. Sometimes, that’s OK – it’s often meaningful and useful to see the metrics plotted over time and look at how they compare with one another.

That said, sometimes the multiple metrics end up looking like this:

Wow. Do you have any idea what’s going on here?

Neither do I. I often refer to this as the “child’s scribble” chart, because it looks like the “coloring” my kids used to do when they were babies: a totally random collection of lines, dots, and colors that is so jumbled, it doesn’t mean anything.

If your charts are starting to look like child’s scribbles, maybe it’s time to split the data points into multiple charts, or remove metrics that are old or no longer meaningful.

### Use the Right Chart Type

Even well-constructed charts can suck. I’ve seen a surprising number of reports with charts like this:

Once again, it’s tough to tell what’s going on here. It looks like content and search are approaching a more even percentage of clicks, but I’m not sure.

Better to use a different type of chart. In this case, pie charts make sense:

Wow, what a difference! It’s clear from the pie charts that the percentage of content traffic is almost doubling every month. Whether this is a good thing or a bad thing is yet another element that should be included in a good report.

Reports with poorly-crafted charts and rows of numbers suck. Take the time to use the right charts to effectively visualize your data, and combine them with solid analysis, and you’re on your way to useful, un-sucky reports!

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