Monitoring Ad Performance in a Google Ads Dashboard

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Bold BI

9 min readJul 20, 2020

Monitoring Ad Performance in a Google Ads Dashboard

Are you looking for the best place to post your business ads? Google Ads is one of the most popular online advertising platforms for automating your business ads to help promote your business, sell products and services, expose your ads in search results, and increase traffic to your website.

In Google Ads, business marketers and advertisers can measure the performance of their ad campaigns through metrics like ads clicked, new visitors, leads generated, lead costs, and many more. Bold BI allows you to monitor all these advertisement-related performance indicators in a single dashboard to help you achieve your business targets. In this blog post, we are going to explore:

The following figure shows a complete sample dashboard for monitoring Google Ads performance that we will re-create by the end of this blog post.

Bold BI’s Google Ads Performance Dashboard

Defining key ad performance metrics

Considering paid search metrics, you can monitor important Google Ads metrics to help marketing leads and managers improve their website traffic. Some of the most important metrics are:

Let’s see how each of these KPIs can be plotted using Bold BI widgets.

Impressions

Impressions are the number of times each ad is shown on a search result page or other site on the Google network. In the sample dashboard, impressions are showcased using a KPI card. The card shows the current month’s number of impressions compared to the previous month. For a marketing team, this comparison KPI value is useful for knowing whether an ad is shown more or less frequently in the current month to their target audience.

Clicks and click-through rate (CTR)

Clicks are the number of times your Google ads are clicked. Click-through rate (CTR) is the number of clicks divided by the number of impressions. The clicks and CTR metrics are displayed in a KPI card in the sample Bold BI dashboard. The card visualizes the clicks and CTR numbers for the current and previous months, and displays the difference along with an arrow and color to provide easy comprehension of the metrics’ status at a glance. With these metrics, a marketing manager can see a particular ad’s click count and how many people have seen the ad and clicked on it. Also, the marketing manager can gauge how attractive the ad is, how closely the ad matches keywords, which ads and keywords are successful, and which need to be improved.

Conversion and conversion rate

Conversion is the number of times people interact with your ad. The conversion rate is the average number of conversions per ad interaction. The KPI card widget is used in the Bold BI dashboard to visualize conversions and conversion rate over a period of time, and to compare performance between time periods.

A marketing team needs this KPI to measure how many site visitors have purchased their product, downloaded their app, or left their website after clicking the ad. They can see the average number of conversions per ad impression.

In the following figure, comparing the current month’s conversions to the previous month’s reveals that the current month conversions are lower. The KPI is displayed with a red color using a formatting option. With this information, the marketing team can take necessary action to improve their ads and campaigns to increase conversions.

Looking at the conversion rate card in the second figure, we can see that the conversion rate has increased slightly. The card is formatted with a green color to communicate an increase.

Cost

Cost is total amount spent on ads. The cost metric is showcased in the sample dashboard as a KPI card that compares the current month’s cost to the previous month’s. A marketing manager can identify whether the amount being spent is higher or lower. With this metric, they can plan to spend less for the next month and hopefully improve their revenue. In the following card, the cost is showcased with a green color using formatting options because the cost is lower than the previous month, and a lower cost is good.

Cost per click (CPC)

Cost per click (CPC) is calculated by dividing the total cost by the total number of clicks. The average cost per click is showcased in the sample dashboard in a KPI card comparing the previous month and current month values. This KPI will provide information about whether the cost per click is increasing or decreasing compared to the previous month. The lowest cost per click and conversion is ideal, so the KPI is displayed with a green color in the following figure using formatting options.

Cost per conversion

Cost per conversion is the average amount charged for a conversion from an ad. This data is showcased in the sample dashboard in a KPI card that compares the current month and previous month values. Using this data widget, a marketing team can easily see whether the cost per conversion is increasing or decreasing compared to the previous month. A lower cost per conversion is good, so the value of the KPI in the following figure is formatted with a green color.

Revenue per click (RPC)

Revenue per click (RPC) takes the total revenue and divides it by total clicks. The RPC metric is displayed in a KPI card in the sample dashboard. This KPI identifies whether the revenue per click is increasing or decreasing by comparing the current month’s RPC to the previous month’s. This metric helps a marketing team make decisions on how to get more clicks and improve their revenue performance.

Now that we’ve covered some useful Google Ads metrics and KPIs, let’s see how to visualize them in a Bold BI dashboard.

How to create a Google Ads performance dashboard

To visualize the performance metrics we discussed using Bold BI, you have to do the following:

Check out our tutorial video to learn how to create a dashboard from scratch before connecting Google Ads data with Bold BI.

Now let’s create a data source using the dashboard designer.

Connecting Google Ads data with Bold BI

To create a Google Ads data source from the dashboard designer, follow the steps described in Choose Google Ads Data Source in the Bold BI documentation. Also, consult the steps outlined in Authentication with Google Ads to authenticate with the Google Ads web service.

After successful authentication, the New Data Source configuration panel opens in Bold BI.

Creating a Google Ads data source

Specify a unique name for the Google Ads data source and provide a description (optional).
Choose the Account, Properties, and View of your Google Ads account.
Select a Start Date and End Date to fetch data from Google Ads for a specific period.
Choose Metrics and Dimensions from the respective drop-down lists. The corresponding URL will be displayed in the URL text box. If you want to connect with other endpoints, you can enable the Custom Url check box and provide the URL in the text box manually.
Leave the default value GET for the REST API under Method.
Provide a size to Page(s) to retrieve more than one page of data. You can use the max-results parameter in your query to select up to 10,000 records in a single page.
Set a time interval for Refresh Settings so that the dashboard can refresh itself with the latest data updates.
Set the data format to be JSON since all the REST API endpoints return results in JSON format.
Google Ads will be set automatically in the Authentication Type section since OAuth is used for authenticating with the Google Ads account.

Google Ads Connection Window with Required Properties

10. Click Preview & Connect. A window will open listing the data results as shown in the following image.

11. Choose the desired columns and click Connect. Drag and drop the table and save the data source. The created data source will be added in the Data Sources

12. Click the edit icon next to the Google Ads — Data Source item in the Data Sources panel to edit the data source.

13. Now, the editing view of the data source opens. We can add more columns by creating an expression column in the data source designer. Click the expression icon in the toolbar of the table design view to open the expression designer.

14. Create an expression column in the Google Ads data source to calculate fields based on the current and previous months.

15. Finally, save the data source. Now the data source is ready to be configured with widgets in the dashboard.

Add required widgets to a blank dashboard that you created using the video reference and configure data to the widgets in the dashboard. After successful publishing, you can view the Google Ads performance dashboard. Along with the metrics discussed earlier in this blog post, you can also monitor each campaign’s performance in a grid widget, as well as data on new users, sessions, impressions over time, clicks, conversions over time, and cost per conversion over time to gain a clear view of the effectiveness of the Google Ads campaigns.

Advantages of monitoring a Google Ads performance dashboard

A Google Ads dashboard gives you a clear view and understanding of your business’s website traffic performance to help you make better marketing decisions and more creative advertisements.
All the metrics can be monitored at a glance in a single dashboard, enabling quick decision-making about your business advertisements.
Revenue per click and cost per click of your business ads can be tracked to help measure your business’s success. In addition, you can use this information to decide whether to invest more in ads or to improve your business and retain your market share.

Conclusion

We hope this article helps you understand how to monitor Google Ads performance metrics to assist your marketing team using Bold BI dashboards. If you have any questions on this blog, please feel free to post them in the following comment section. To get started with Bold BI, please request a free 30-minute demo with our experts to discuss creating dashboards and any other features you would like to learn more about. You can also contact us by submitting your questions through the Bold BI website or, if you already have an account, you can log in to submit your support question.

Originally published at https://www.boldbi.com on July 20, 2020.