In this post, I want to show you how to analyze a merged data report (Baidu’s advertising system + Google Analytics) in Looker Studio (previously called Google Data Studio), and how this report can improve your advertising results.
Suppose you’re a global company accustomed to using Google Analytics to gather and understand data, and you’re doing advertising and marketing in China. In that case, you will want all your data together in one place.
Having both data sets in one place will allow you to understand what’s happening in China and globally. Furthermore, you’ll be able to make intelligent decisions—not only about how to drive people to your website, but specifically drive those who are more likely to convert.
I’ll walk you through a sample report page, how to adjust the date range and the metrics, perform an amended keyword search and identify underperforming keywords. In the end, if you take these points away, you’ll have better access to, and understanding of your Baidu ad results.
Check the video version here or read on.
Why Should You Listen to Me?
I started doing Baidu advertising back in 2008. Since then, I’ve run successful campaigns for hundreds of different-sized companies, including industry leaders and giants. Here are just a few of the highlights:
- Microsoft – We ran a huge-scale search advertising campaign to help improve their results in China.
- Papa John’s – We increased the company’s pizza sales in Beijing and using Google Analytics,
- we helped the company track specific information, such as the types of pizza sold.
- Grammarly – Way back when it was just a small start-up, we helped the company improve its profitability in China.
All in all, I’ve been doing this long enough now to have become quite good at it.
These days, you could say I’m in more of a strategic role where I focus on the “bigger picture” data and what that means for businesses. However, I often get nostalgic for the advertising and management side of things: reports, funnels, microdata, and the meaning all the smaller numbers carry.
The Report Page
In this sample report, we’ve merged the data from Baidu advertising and Google Analytics in Looker Studio, and the report page looks like this.
As you can see, all the useful information from the overall funnel (impressions, CTR, clicks, conversion rate, goal completions, etc.) is right there in the middle of the report.
If you adjust the date range in the filter options, you’ll get a new data set for that period.
In this report, we have other filter options: keyword, keyword translation (which is not always accurate as it goes through Google’s own translator), and our ad groups set up in Chinese. However, you can change the language preferences and filter options based on your needs.
At the bottom of the report page, there’s a table for the Baidu advertising account that displays the data for each specific keyword and its Chinese translation.
We can also see other metrics: spend (CNY), impressions, clicks, cost-per-lead (CPL), etc. Everything here is from Baidu advertising, except for the goal completions, which are from Google Analytics.
The CPL is calculated by counting the number of goal completions and the overall spend.
If you want to change the order of the columns, add new data sets and metrics, or take existing ones away, you can do this by clicking on the edit button (providing you have access to edit).
Don’t like tables? Don’t worry. In addition to changing the data metrics, you can also change the overall format and presentation.
The data in the table is particularly important as it can reveal areas that require attention, improvement, or alteration. However, that’s only if you know what you are looking at, or what you are looking for.
Problems Often Missed By Marketing Teams
More often than not, different teams and departments will handle a company’s website and marketing efforts, and these teams don’t always have access to each other’s data. For example, the people responsible for driving clicks-through advertising to the website may not have access to the website.
This means important information can be overlooked or go unnoticed.
We can find an example of this in the table. (This is real data from a company, so we’ve blurred out any sensitive information).
In the example below, we have isolated one keyword and its corresponding metrics. Do you notice anything a bit off?
This keyword has a very high spend and only one goal completion, so the CPL is high.
Now, what does this mean?
This is a big business with different business units, and some keywords direct people towards the main business instead of the specific unit.
For example, let’s say we’re running a campaign for a subsidiary, and the Baidu ad contains the parent company’s name. People interested in the company (but not necessarily searching for the entity we’re working on) click on the ad causing a high click rate, which pushes up the CPL.
If a keyword has a very high CPL, it means that something didn’t work out, and we should probably stop advertising that keyword.
Filtering Keywords
Rather than just scrapping the keyword outright, we can test things a bit further by removing part of the keyword in the filter options so it shows us all the data for anything that contains the amended keyword.
Again, the filtered information shows us that the cost per conversion is very high, and we are wasting around 3,000 (CNY) every six weeks or so on this keyword.
Now that we’ve identified an underperforming keyword, we can shut down the keyword or discuss the issue with the whole team to figure out where the problem lies, and whether it’s worth salvaging or discarding.
Information Available to Everyone
These Looker Studio Reports have worked well for us: It’s relatively easy to set up, and this type of merged data that displays the whole conversion funnel is invaluable when accessible and visible to everyone in your company.
Once this data is available to everyone, informed decisions can be made across departments and teams:
- Search engine marketers
- Landing page creators
- Website developers
- Account managers
- Clients and customers
- Salespeople
- Customer support
So there you have it, having all the data in one convenient place means everyone is on the same page, and any potential issues or areas for improvement can be identified, removed, or fixed efficiently.
I hope you found this post useful. If you have any feedback or questions, or you’d like to share your experience using Looker Studio to organize and analyze merged data sets, please feel free to send us a message or comment below.