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Get started# How to Analyze Google Ads Data: Strategy to Simplify Data Analysis in PPC Campaigns

As a pay-per-click (PPC) advertiser, one of the significant aspects of managing a campaign is to monitor and analyze the performance of your ads. But reviewing your PPC campaign performance can be quite overwhelming.

When you’re learning how to analyze Google Ads data, you can choose key metrics and see the results against different dimensions on the Google Ads dashboard. However, that’s not the only way to do it. There may be many combinations of different dimensions and metrics that can predict something you’ve never noticed before.

Whether you’re running your PPC campaigns yourself or have hired an agency for this purpose, you still have to keep an eye on the insights you are getting based on the unseen combinations. That’s why you need a tool that can show you the available data combinations. It’s important to know these combinations before you can analyze your Google Ads data.

PPCexpo combinations calculator helps you determine the number of combinations in your campaign. Plus, it also shows you every possible combination of your campaign, up to a certain length.

In this article, we’ll share tips on how to analyze Google Ads data. Plus, we’ll explain how using the PPCexpo combinations calculator can help to determine the complexity of your PPC campaigns.

## How to Determine the Complexity of Your PPC Campaign?

Complication, you must overcome the biggest challenges of your PPC campaign. A major aspect that makes your campaign more complicated is the number of combinations generated by the dimensions and metrics. The more combinations you have, the more complex your PPC campaign becomes. That’s because you have to evaluate more combinations in the same amount of time.

It is possible to calculate the impact of dimensions and metrics combinations on the complexity of your PPC campaign. In a PPC campaign, dimensions (such as keyword, device, geography, etc.) can be combined with metrics (like click, cost, conversion, etc.) to define a user interaction.

For example, suppose a keyword “PPC analytics” has 5,000 clicks on mobile devices in the geographical location of California. Now, PPC analytics, mobile, and California are dimensions, and clicks is a metric. As the number of dimensional attributes and metrics increase in a campaign, the number of combinations increases proportionally.

And, as the number of combinations increases, it becomes difficult for you to identify any change. Complex combinations can have a negative influence on your ROI. When you have a large number of combinations, it becomes difficult to detect where significant changes are happening.

As your PPC campaign grows in scale, sometimes your ROI starts declining. This dynamic happens because when dealing with massive, intricate accounts, it’s impossible to consider every factor that can impact your campaign performance.

Using the PPCexpo combinations calculator can simplify this complexity for you, pointing out the right combinations in your account within seconds and let you know the level of complexity. The very next challenge is to monitor these combinations for the changes and take necessary actions to keep the campaign performance on the track. PPC Signal can help you with this. You can monitor the changes that are happening on these combinations and can also evaluate the combinations based on their impact and intensity.

Here is your go-to strategy for data-driven campaign optimization.

- Use Combination calculator to determine the complexity of your campaign
- Use PPC Signal to understand, simplify and fix the complexity
- Do small little changes daily using PPC Signal and get the exponential growth over time

## What is a Combination?

A combination is the number of ways in which you can select ‘r’ elements out of a set containing ‘n’ distinct objects. The order in which you choose the elements is not as crucial as the permutation.

For example, suppose a campaign has ten different dimensions, and you randomly choose five dimensions. How many distinct sets of dimension with one metric can you get? In other words, how many different combinations can you get? Determining such combinations manually can be time-consuming. That’s where a combinations calculator comes handy.

## Why Combinations are Important?

In a PPC campaign, there are many dimensions e.g. keyword, device, geography, etc. that can be combined with metrics e.g. click, cost, conversion, etc. to describe a user interaction that measures and shows the ad performance in different ways.

Suppose there is a **keyword**=‘Best PPC Reports’ which has 1,000 clicks on **device**=mobile in **geography**=Houston. In this example, **Best PPC Reports**, **mobile**, and **Houston** are attributes of dimensions, and clicks are a metric. You never know what type of combination of dimensions and metrics can bring the result in the long run. As the number of dimensional attributes i.e. number of keywords, geographies, etc. and metrics grow in a campaign, the number of combinations will grow proportionally. This growth creates complexity and makes it difficult for you to detect a change.

Let’s consider another example, to understand more, why these combinations are important in PPC:

### Pick your best device:

You have 4 devices (desktop, mobile, tablet, smart TV) in PPC to target, now to find which device is best for conversion, the choice will be 1 out of 4. Let’s assume desktop is considered best out of all devices.

### Pick your best day:

Now consider the days of the week, as there are 7 days in a week not all days can perform best. The choice is 1 out of 7. Let’s assume Friday is best amongst all.

### Pick your best hour of the day:

You cannot get your overall campaign performance all the time excellent throughout the day. There are certain hours when the campaign performs best and at certain times it can’t. So the choice is 1 out of 24. Let’s Assume 7 PM. Is taken out best of all hours of the day.

### Now let’s make a combination to find the best:

If you will be having data of your campaign this will be good to filter out the best combination. Now if you make a combination to find out the best performing set the choice will be 1 out of 672 because if you make combinations of **device** X **day of week** X **hour of the day **it will become 4 X 7 X 24 =672. So there are hundreds of results available out of which you have to find the best one. After finding the combinations and calculations, it may infer that mobile at 9 am and on Tuesday performs best. Here you are with the oddity and peculiar results.

As the data keep on growing, it becomes more complex to identify and detect were salient and dominant changes are occurring, so you can’t neglect the importance of combinations.

## How to Calculate Combinations?

Here’s the formula that you can use to calculate the number of combinations easily:

**C (n, r) = n! / (r! * (n-r)!)**

Where:

- C (n, r) is the number of combinations.
- n is the total number of elements in the set.
- r is the number of elements you select from this set.

Let’s go back to our example and apply this equation to our problem. In our case, n=10 and r=5. The total number of combinations will be:

**C (10, 5) = 10! / (5! * (10 – 5)!) = 10! / (5! * 5!) = 252.**

This means, taking only five different dimensions from a total of 10 will result in 252 combinations. As you include more dimensions, the number of combinations will increase proportionally. You’ll reach a point where it won’t be possible to manually calculate the total number of combinations. A combinations calculator will help you calculate the total combinations and figure out the combinations of specific metrics.

## Drawbacks of Manually Calculating Combinations

There are several drawbacks to manually calculating combinations, including:

### 1. It is Time-Consuming

Too many combinations become a big problem for PPC managers. It bogs down data workers and substantially increases the time-to-insights window. This has a direct negative influence on your business performance.

Instead of focusing on other critical factors of your campaign performance, PPC managers must keep on calculating the combinations. As a result, they invest less time in optimizing and improving campaign performance. As such, the more combinations your campaign has, the more time you’ll need to calculate them.

### 2. It Wastes Resources

For calculating the combinations, you need a data analyst and a PPC manager with extensive domain knowledge. However, as the combinations become more complicated, you need to onboard more data analysts and PPC managers to handle the additional workload.

### 3. It Increases Complexity

Manually calculating combinations can make your campaign quite complicated. With accurate analysis and calculations, you get clean, reliable datasets. However, when you blindly calculate combinations, pulling in all sorts of data, the quality of your data suffers, along with its reliability for decision-making.

### 4. It Makes Integration Challenging

Businesses have to deal with a large number of combinations, both internal and external, to determine the critical factors of their campaign. When integration involves vast amounts of combinations, most of which are extraneous and unnecessary, the process becomes sluggish. It creates more problems that you have to solve along the way. All of this reduces the effectiveness of a combination integration project. Plus, poorly integrated integration increases costs as well.

## What is the PPCexpo Combinations Calculator?

A combination calculator is a simple tool to solve combination problems. Before you start using a combinations calculator, it is vital to know the basic formula and functionality.

The PPCexpo combinations calculator works on **nCr** to get you the most reliable and accurate outcomes without consuming a lot of your time. You can use it to determine the number of combinations that can be made from a particular number.

Calculating ROI is one of the basic principles of PPC. But many PPC advertisers tend to overlook it. Some of them don’t understand it. We’ve seen many advertisers performing campaign optimizations based solely on conversion rate or cost per conversion (CPC). They choose the ads and keywords with the best metric and call it a day.

The PPCexpo combinations calculator presents a multi-criteria decision model that can manage diversity and possible conflict by attaining an effective balance across a wide range of creative options. It can help you determine the optimal creative combinations of your campaigns by overcoming the complexity so that you can better optimize your campaign for a higher ROI.

## How Does the PPCexpo Combinations Calculator Work?

The PPCexpo combinations calculator can help you determine the number of combinations. Plus, it can also show the possible sets you can make with every single combination.

You can use it to determine the possible number of combinations that can be achieved by campaign dimensions and metrics. It also shows you how various possible combinations can be made from your campaign dimensions and metrics such as the number of campaigns, ad groups, keywords per ad group, devices, etc.

The PPCexpo combinations calculator provides two functionalities to get an estimate of total combinations in your campaign.

### Manual

In this functionality, the PPCexpo combinations calculator allows you to alter the following as per your requirements:

- Number of Ad Groups.
- Number of Keywords.
- Average number of keywords per ad group.
- Number of devices.
- Number of geographic locations.
- Hours of the day.
- Days of the week.
- Total number of metrics.

However, varying these values can impact the total number of combinations in your campaign. For instance, you have one campaign with 10 Ad Groups, with each Ad Group having 15 keywords. Suppose you’re targeting four devices and 20 geographical locations running 24 hours a day and seven days a week and pointing to 10 metrics. This setup means you’ll have 258,000 total combinations in your campaign, as shown below.

If we start calculating all these combinations on a piece of paper, it will be time-consuming as this use-case is quite convoluted. When you’re managing a PPC campaign, it’s just not feasible to dedicate so much time and effort into calculating the combinations. Otherwise, you can end up overlooking other critical areas.

The increase in the number of combinations also makes your campaign more complicated. That’s why consider calculating the impact of dimensions and metrics combinations at the same time. The digital platform allows businesses to evaluate how using the same creative in a unique combination can yield more fruitful results.

### Automatic

This feature of the PPCexpo combinations calculator allows you to collect the campaign structure, dimensions, and metrics from your Google Ads account automatically. It also calculates the potential number of combinations of your account or campaign. As a result, you can make your campaign less complicated, managing your campaigns more effectively.

Once you get the combinations, you want to point out the factors that can yield a better ROI. But before that, it’s imperative to understand your customers and how they interact across different platforms if you want to effectively serve them with relevant ads and accomplish your ROI objectives.

How successful your campaign ultimately depends on using the right creative in the correct sequence to get the optimal results – regardless of your success metric. The PPCexpo combinations calculator allows you to calculate the impact of dimensions and metrics combinations on the intricacy of your PPC campaigns, achieving the best ROI possible.

Let’s give a try to PPCexpo Combination calculator.

## Wrap Up

Whether you’re creating your first-ever PPC campaign or are a veteran in this domain, it’s essential to know all the strategies and tips on how to analyze Google Ads data. This analysis can help you optimize your PPC ads, boost conversions, and yield more sales. By Using the PPCexpo PPC Signal, you can streamline and simplify your campaigns to improve your sales and conversions and reach the desired ROI.

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