Google Ads KPIs: How a Point Moving Average (PMA) Enhances Your Campaigns

Large Pay-Per-Click (PPC) campaigns can be fun and profitable. However, they can also be a pain to manage. It would help if you gathered insights from large mountains of data. That way, you can take advantage of the information collected and put it to better use.

Of course, first, you need to know which data is relevant and useful, and which is a time-waster. In other ways, you’re spending precious dollars and time on things that won’t get you a better ROI (Return on Investment).

This article will look at the right Google Ads KPIs (Key Performance Indicators) to manage and improve. That way, you can confidently move forward in improving your campaigns and increasing your conversions. Let’s get started:

The Challenges with Making Decisions on Daily Data

In today’s world, data is a valuable organizational asset that can be used to drive decision-making processes and qualify or disqualify ideas based on cold, hard facts.

Regardless of your stance on the overall comparison of data to experience, there is one thing you cannot deny: data is a valuable tool for helping modern businesses determine strategy.

Any company not using data to make decisions is at a tremendous disadvantage. Being able to accurately track performance and understand the impact each of your initiatives has in the market is incredibly important.

But if you don’t have much data available in your campaigns, it’s difficult for you to determine the meaningful insights from such a small amount of data. Points Moving Average (PMA) can help you to forecast the trends using less data.

Introduction to PMA for Google Ads KPIs

In general, a moving average is a calculation used to analyze data points by creating a series of averages of different subsets of the full data set. A moving average (MA) is an indicator that is commonly used in technical analysis.

The reason for calculating the moving average is to help smooth out how data is displayed by creating a continually updated average.

By calculating the moving average, the impacts of random, short-term fluctuations in the value over a specified time-frame are mitigated. Several moving averages can be used, with the following being the most common.

• Three-point moving average.
• Four-point moving average.
• Custom Points moving average.

The three-point moving average is the easiest and quickest moving average to calculate, but it doesn’t completely smooth the trend line, and so it makes accurate extrapolation more difficult. Three-point averages are calculated by taking a number in the series with the previous and next numbers and averaging the three of them:

For this, you take the first three figures in the series and average them:

3000 + 1500 + 2100 / 3 = 6600 / 3 = 2200

Three-point moving averages are also useful in working out the average variations across a longer period when looking at your Google Ads KPIs. This is because the average of three numbers falls on the middle of the series and can be compared directly with the actual sales for that period.

If these variations are seasonal or cyclical, they can predict actual sales by adjusting the extrapolated future sales to take account of the predictable variation.

With PPC advertising, we have historical data that can help us define and analyze the average with more points. With larger campaigns, this can get complicated.

That’s why tools like PPC Signal can help. They can automatically figure out the PMA in your campaign to have a clear visualization of the trend of your campaigns. Below is the trend chart in PPC Signal showing the PMA:

If you compare the daily CTR (Clickthrough Rate) on the pink line with the Point Moving Average CTR on the blue line, you will see a huge fluctuation in CTR on daily data, and you cannot derive any actionable decision from this pattern.

The PMA metric would aggregate the data at specific intervals. You can track the PMA over time to see that your campaign was headed in the right direction at first but fell in the middle, finally coming back up near the end. This all you can explore in PPC Signal.

In PPC signal you can find following different KPIs which has been defined based on the custom points moving average.

• Average CPC (28 points moving average)
• CTR ( 28 points moving average)
• Conversion Rate (28 points moving average)
• Cost Per Conversion ( 28 points moving average)

These custom moving points KPIs are defined under different stages of marketing funnel. But if you want to make your own changes in any funnel steps you can just pick then drag and drop the metrics to place it under your desire stage.

Advantages of using Points Moving Average

• Smooth Line – The primary advantage of using the PMA is that it offers you a smooth line. It is less prone to bouncing up and down in response to short term, temporary data swings so that you can chart the correct course of your campaigns more accurately.
• Simplicity – You can minimize all the noise from the rest of the data. You can analyze trends in a cleaner way. You can even use two PMAs to confirm your trend hunches.
• Ad Changes – You can find the right places in your campaign to make changes. You can predict with better risk and reward ratios which changes to make and precisely when to make them. This is something that many advertisers currently struggle with, regardless of the size of their campaigns or budgets.

Using PMA to Determine If Your Google Ads KPIs are Improving

To decipher trends in data series, advertisers perform various statistical manipulations. These operations are referred to as “smoothing techniques” and are designed to reduce or eliminate short-term volatility in data.

A smoothed series is preferred to a non-smoothed one because it may capture changes in the direction of the ROI better than the unadjusted series does. A points moving average is simply a way to smooth out data fluctuations to help you distinguish between typical “noise” and the actual trend direction.

There is a downside to using a point moving average to smooth a data series, however. This is because the calculation relies on historical data, and some of the variable’s timeliness is lost. There might be a particular timeslot which performed very well or might performed very bad but you won’t know it exactly.

For this reason, some advertisers use a “weighted” moving average, where the more current values of the variable are given more importance. Another way to reduce the reliance on past values is to calculate a “centered” moving average.

The current value is the middle value in a five-month average, with two lags and two leads. The lead figures are forecasted values.

With a smooth trend defined by the PMA, you can improve your strategy. As we have discussed above in the trend chart, your CTR is fluctuating at different time intervals.

CTR drops when your campaign is getting impressions but no clicks. This commonly stems from a problem with keywords, which are too broad. Additionally, your ad copy might not be appealing, bringing your Google Ads KPIs to a halt.

Think about it this way: an impression occurs when a user searches one of your keywords, causing your ad to appear. It is important to note that, at this point, the user has only seen your ad and not your site. Therefore, everything they know about your business is based solely on what your ad tells them.

The solution to this dilemma is relatively straightforward in principle but can be quite an art in practice. You need to carefully select the keywords which cause those ads to appear so that when a user searches for ‘robot cleaner’ or ‘robot polish,’ you show them an ad that clearly (and compellingly) says you have those exact products.

You have to consider the following points if your ads are not getting clicks but have impressions:

Narrow Your Keyword Selection

You might be going too broad. This is often the case if you are aiming for brand awareness. Beware that if conversions are your ultimate goal, you may need to refine keywords in order to target your market more effectively. You should do proper keyword research to use the best keywords in your campaign.

Quality Score

Your Quality Score could be low due to your landing page not matching up with the keywords in your ads. It may be because of wrong audience targeting.

Google has become more sophisticated in identifying “cheating” campaigns by using keywords in their ads without having a consistent experience on the landing page. If your audience is also not relevant then focus on right audience, at right devices at right time so that only the concern audience should see your ad and visit your landing pages.

Campaign Budget

Your campaign budget may be too small. If you are spread out among several keywords, try focusing on just a handful. Eventually, you can expand out again. This is typically a problem for smaller businesses and agencies. If you have limited budget you might not rank properly to appear on SERP.

Bidding

Make sure that you are bidding enough on each keyword. You don’t need to get first place in every category. However, you do need to be in the top few positions to drive optimal returns. Otherwise, it would help if you consolidated bidding to fewer keywords.

Ad Copy

Are you employing sound marketing principles in your ad copy? Does your headline grab attention (and preferably feature the keyword)? Have you included a call to action? Are you using all of the features available to you, such as extensions?

Be sure to analyze your ad copy from your ideal customer’s perspective, not just your business. Quite often, companies focus too much on the product and not on the problem being solved.

Wrap Up

Regardless of your PPC campaigns’ size, data is an invaluable tool when keeping your Google Ads KPIs on track. It separates marketers who shoot in the dark from those who achieve real success in their conversions.

Still, this process is not easy at first. Using the right metrics, like the PMA, can help you forecast trends and be efficient with the data you are reviewing and using in your campaigns.

If you apply the tips above, your campaigns will take less effort over time and be more profitable for your business. And that is key for every online enterprise, especially in these uncertain times.