If you’re just getting started with Google Data Studio, you’ve probably experienced blank-page syndrome.

You get your data source connected, open up a new file, and you have no idea what to do next.

There are no instructions. No guide rails. Just you and an empty page to fill.

And while you can start with a template (Google Data Studio Report Gallery has several), it’s still tough to know how to customize it to perfectly fit your needs.

Here are some tried-and-true elements to include in PPC dashboards and reports that will banish blank-page syndrome and give your stakeholders the insights they crave.

1. Titles, subheads and context

When you add a chart in Google Data Studio, you select the data source, dimensions, metrics and date range from the Data Panel to populate your visualization.

But your reader doesn’t see the Data Panel and won’t know what your chart is about unless you take an extra step to include it in your dashboard.

The two graphs below show identical data visualizations. Figure A includes only the chart, while Figure B includes written titles and context.

Figure A leaves questions in your reader’s mind that Figure B answers.

You can make your graphs and tables easier to understand at a glance with these tips:

• Give your data visualizations a title.
• Use subheadings and microcopy for additional context.
• Use legends.
• State the date range if it’s not included in the chart. (Note: “auto” date range defaults to last 28 days.)
• If multiple data sources are used throughout your dashboard, clarify which is used in specific charts.

How to do it:

1. Add a text box and write out your titles and descriptions.
2. This will open up a “Text Properties” panel to edit fonts, text size, and styling elements.

It’s worth the small manual effort it takes to add a text box and include context!

2. KPI scorecards

You don’t need an article to tell you that your dashboard should include your key performance indicators (KPIs).

But while you’re planning out your dashboard, pay special attention to where to include them.

Your KPIs matter most in your report and deserve top billing.

That means showcasing your KPIs with scorecards like so:

Not as afterthoughts at the end of a table:

Not only do tables make it hard to identify KPIs, for languages that are read left to right, tucking KPIs on the far right of the table tells your reader these metrics are low priority.

Keep your reader focused on your key growth metrics like lead volume, revenue, or return on ad spend (ROAS), rather than vanity and traffic metrics like impressions and clicks.

How to do it:

1. Use Chart > Scorecard.
2. In the “metric” section of the Data Panel, add your KPI. Repeat as needed.
3. Control format and size in the Style Panel.

Having KPIs appear in tables and other charts isn’t a problem, but give them added attention by using scorecards.

3. Goal pacing

Some advertisers use fixed monthly or annual marketing budgets with no room for adjustments.

Others have sales or efficiency goals they need to hit with flexible budgets.

No matter what the approach, your dashboard should answer the question:

Are we meeting our objectives, and how do we know?

Account objectives aren’t standardized, and neither is the approach for including goal pacing in your dashboard.

Fortunately, Data Studio gives you many options for adding objectives and pacing, from literally charting against a goal to adding a written description of the target.

Here are some examples of how you might anchor performance to a goal:

How to do it:

1. Option: Add a header that states the objective
2. Option: Use a pacing chart such as bullet or gauge
3. Option: Add a calculated field with progress to goal (metric/target)

Including goal pacing gives your reader confidence in how to interpret performance data.

4. Trends and historical comparisons

Trends and historical comparisons let your reader know if things are improving – or need improvement – over time.

Maybe you fell short of the goal, but you always miss it because it’s unrealistic.

Maybe you hit your goal, but you’re down compared to last year, and you need to take corrective action.

Don’t make your reader wonder whether current performance is average, down or “best month ever.”

Snapshot (single-metric) comparisons

Tables and scorecards give you an easy way to show your reader how performance for this period compares to another, using color-coded arrows to indicate the direction of the change (delta).

How to do it:

• Under “Date range,” select your comparison date range:
  • Fixed
  • Previous period
  • Previous year
  • Advanced
• In the Style Panel:
  • Control the color of positive or negative change arrows
  • For Scorecards only, you can select whether to show absolute or percentage change and whether to include a description of the previous time period (comparison label).
  • You can also format Scorecards to show both YoY and MoM comparisons.

Line charts

You can get a complete picture of performance trends using time series charts. 

Rather than just comparing this period to the last period, you’ve got an entire history revealing trends in seasonality, market impact and more.

You can use a continuous Time series chart (shown above) or designate a comparison time period.

Here’s how that same data looks as a Year over Year (YoY) Time series chart. Note that the comparison year will show as a lighter shade of this period’s line:

Another way to show historical performance is with a line chart that uses a time period as a breakdown dimension.

This Line chart is from a report comparing CPCs before and during the Covid-19 pandemic:

How to do it:

• To compare two time periods: Use a Time series chart and select a comparison date range.
• To compare three or more time periods (shown here for years):
  • Select a Line chart
  • Set the “Dimension” to Month
  • Set the “Breakdown Dimension” to Year
  • Set the “Sort” to Month
  • Set the “Secondary sort” to Year

A few important notes for trends and historical comparisons – 

• Only use these for your KPIs or metrics that directly contribute to your KPIs. Don’t add a CTR trend chart just for the sake of including a trend chart.
• There’s almost never a reason to show daily granularity in these charts. Zoomed in that closely, you’ll miss the signal for the day-to-day noise. Look for trends at a monthly level.

5. Categorical tables

Okay, so tables aren’t that glamorous. 

But if your Data Studio dashboard doesn’t have a table, something’s probably missing.

Why? Because there are times when your audience needs to compare multiple categories across multiple metrics. And nothing does that more efficiently than a table.

Tables are great for comparing default categories like:

• Campaigns
• Ad groups
• Keywords
• Search terms
• Final URLs

And depending on the complexity of your PPC dashboard, you can create tables for:

• Engines and platforms
• Channels and networks
• Funnels / intent / stages of awareness
• Brand vs. nonbrand
• Pivots of time segments, conversion types, and other categories

How to do it:

• Chart > Table (or Pivot table)
• Dimension(s): the category or categories you want to compare
• Metrics: your KPIs and supporting metrics
• From the Style Panel, you can format your table to include heatmaps, bars and targets

It’s easy to build tables and add metrics, and it’s easy to get carried away. Exercise some restraint and limit the number of metrics in your table, so it remains useful to your reader.

Bonus: Shiny charts

Our list constrained us to five categories, but here’s one bonus for making it to the end:

Shiny charts.

What are shiny charts?

Shiny charts are visualizations that your audience loves and gets excited about, even if they’re not super actionable.

Your readers may not learn anything new, but they’ll feel like they learned something new.

Maps are a great example. 

Many dataviz experts say not to use map charts; there are better ways to communicate location data. 

But try to find a client or stakeholder who doesn’t love to see performance data on a map. Go ahead. I’ll wait.

Sure it’s a bit counterintuitive when you’re trying to build out an actionable dashboard. Maybe even a bit controversial. And you don’t have to do it. But a chart that makes your audience feel good just for seeing it has its own merit.

Putting it all together

While your Data Studio dashboard can technically include whatever you want, it should at a minimum include:

• Title and context
• KPI scorecards
• Goal pacing
• Historical comparisons
• Categorical tables

These don’t need to (and can’t) all be discrete sections. One scorecard can include a title, KPI, pacing, and time comparison.

There are many other charts and visualizations that can take your PPC dashboard from good to great. Getting started with this list will set you up for success and give you a dashboard worth the time it took to build.

The post 5 things your Google Data Studio PPC Dashboard must have appeared first on Search Engine Land.

Want to understand your paid search results? Geography is one of the most significant factors to analyze.

DIfferent words and brands mean other things based on location. For example, are you “soda” or “pop”? The same is true for brand names.

Read on to learn about geolocation results in paid search, how they vary and what to do with the variances.

Data: How PPC results vary across regions

For years I’ve had discussions with various brands about their performance by region. Should they be geotargeting? How does it impact bidding? Does it matter at all? 

I pulled a data set to see how performance varied by geographies over the past year. Let’s start by looking at how results vary across regions. To understand the variances, I indexed each metric against the campaign totals or averages. 

How much do the metrics vary? The first thing that jumps out is how wide the variance is, especially for CTR. We saw variance for all metrics of at least 2x and in the case of CTR as high as 15x. The minimums also vary much more than the maximums, except for CTR.

There was a significant difference by geographic region (in this case, “geographic region” means “states”). Why the big swings? Among the reasons;

• Brand awareness: Brands signify different things to different people based on locations. For example, a brand may be available nationally, but they were founded on the East or West Coast. 
• Market competition: Regional players might only advertise in a given region that will influence the metrics.
• Keyword/bid strategy: The paid search managers of these accounts on a daily basis have something to say about the performance. They shift bids and keyword lists based on performance as a regular part of maintenance. This can have a natural influence on the metrics.

The next thing I looked at was what would happen if I stopped spending in the lowest-performing 20 states. What would be the impact on my metrics? 

A simple first step could be to stop spending the lowest-performing states. Using my data set, I viewed “lowest performing” by four categories:

1) Lowest conversion rates
2) Highest CPC
3) Highest Cost per Conversion
4) Lowest conversion rates

These categories all impacted the results pretty differently. Removing the lowest conversion kept the most revenue but didn’t improve the ROI.

Removing the highest cost per conversion improved the ROI the most but removed more than 30% of the total revenue. The impact on the ROI was pretty small, and the volume of results was reduced by up to 35%, based on this data. 

So what if you took the lowest-performing states and poured that spend back into the top 20 performing states? The hypothesis showed improvement with all four scenarios increasing revenue vs. the baseline results.

The best scenario was removing the 20 states with the lowest costs-per-conversion and investing more in the states with the lowest cost-per-conversion. However, even in that scenario, the ROI and revenue didn’t increase more than 4% versus the baseline index.

Many companies would be ecstatic about the opportunity to increase revenue by 4% without any incremental costs. But for others, the juice wouldn’t be worth the squeeze. 

What could alter this analysis?

• Assumptions on assumptions: A big assumption is that spending at higher levels and assuming the same throughput rates. The CPCs, conversion rates, or any of the metrics would be altered, impacting the results.
• Keywords within states: Viewing any of this data through the lens of only the geography doesn’t take into account all the other factors that weigh into performance. For example, even in a great performing state, there are specific keywords that are not performing well just as there are keywords in poor-performing states that are crushing it.
• Landing page and ad copy experiences.
• Brand type: Our data set has a mix of DTC online pure-plays and online/offline. I think local store mix and conversion types can all alter this analysis.

PPC actions to take?

Ultimately, the beauty of paid search is nothing operates in a vacuum. You have to consider the implications between the keyword, ad copy, bid, and landing page.

The correct answer isn’t just altering geotargeting. It takes the combination of these with audiences, time of day, device type and so many factors to truly drive results.

What I’m suggesting is that geotargeting can be yet another knob that can be dialed up and down and should be considered a critical optimization tactic. For example, if you want the ad copy and landing page to match the geography, geotargeting becomes more important from a user experience standpoint.

In some cases, it will complicate things to a level that doesn’t make the difference for your organization, and maybe a simple bid-modifier will do. In other cases, it could be the key to unlocking your results.

You can start simply with bid multipliers. My recommendation: dig into the data at this level, create a few tests and see if you can impact results in a meaningful way. Then you can determine if the test should be scaled up or back. 

The post Geotargeting optimization: How region impacts your PPC results appeared first on Search Engine Land.

Google and Bing have expanded ad sales suspensions imposed on Russia due to its invasion of Ukraine. Google has temporarily halted ads from serving to Russia-based users, the company announced Thursday. Similarly, Microsoft announced that it will suspend all new sales of its products and services in Russia.

Why we care. The two leading search engines now prohibit ads targeting users located in Russia, cutting off the main channels western search marketers use to reach audiences there. This will affect brands advertising to Russian users, but Yandex (Russia’s second-biggest search engine by market share) remains an option.

These ad suspensions serve to protest Russia’s actions in Ukraine, but they also help search engines avoid brand safety debacles like misinformation campaigns making it through their automated systems and showing to users.

Escalating restrictions on Russian state-funded media. Last week, both search engines stopped running ads from Russian state-funded media outlets. In addition, Microsoft is “further de-ranking these sites’ search results on Bing so that it will only return RT and Sputnik links when a user clearly intends to navigate to those pages,” Brad Smith, president and vice chair of Microsoft, said in an announcement on February 28.

Perhaps this is what Russia wanted. Roskomnadzor, Russia’s communications regulator, has accused YouTube of running “advertising campaigns to misinform the Russian audience,” according to the Wall Street Journal. The Russian agency demanded that Google change its ad moderation policies and discontinue such ads.

The new ad suspensions are likely to primarily affect Russia-based businesses, but they may also put a temporary end to the ads Russia is complaining about.

Social media platforms halted ad sales in Russia, too. Snap Inc. and Twitter have both paused ads in Ukraine and Russia, with the former halting them in Belarus as well. Facebook has stopped serving ads from Russian state media, but (at the time of publication) is still showing ads to Russian users.

The post Google and Bing halt all ad sales in Russia appeared first on Search Engine Land.

On January 5, Google removed all App campaign placement data from several reports within the Google Ads API and the AdWords API. “We made this change because the data provided didn’t fully represent the complete view of the placements that help developers monitor brand safety for their advertisers,” the company said in its announcement on February 28.

Why we care. Keeping an eye on where your ads show up can help you steer clear of unwanted placements and associations. If you’re looking for App campaign placement information in the reports (mentioned below), it won’t be there. Instead, Google advises that you reference the App Campaigns Brand Safety Placement report, which can be accessed via the Google Ads UI.

Where the data was removed from. Google removed App campaign placement data from the Google Ads API’s Group Placement View and Detail Placement View reports.

App campaign data was also removed from the AdWords API’s Automatic Placements Performance and Placement Performance reports.

AdWords API is on the way out. The legacy AdWords API is scheduled for deprecation on April 27. Developers must migrate over to the Google Ads API before then.

The post Google removed App campaign placement data from Ads and AdWords API reports appeared first on Search Engine Land.

Google AdSense will separate YouTube earnings into its own AdSense for YouTube homepage and payments account, the company announced Wednesday. The change will begin in March and roll out over the following months.

YouTube publishers were first made aware of this change in an email sent by Google in January.

Why we care. Soon, YouTube earnings will no longer appear alongside AdSense earnings. Making note of this change and alerting colleagues and/or stakeholders will help eliminate confusion when the change rolls out.

AdSense publishers aren’t actually earning less, those earnings are simply being reorganized. Unfortunately for some, it may take longer to reach the payment thresholds since AdSense and YouTube now each have their own threshold.

Separate payment thresholds. YouTube earnings will be bucketed into its own payments account, meaning that YouTube and AdSense payments accounts will have separate payment thresholds. This could affect payment timing for some as it may take more time to reach the payment threshold.

The post Google AdSense separates YouTube earnings into its own payments account appeared first on Search Engine Land.