Baidu bidding sem data case analysis, how to conduct bidding data analysis?

Friends who do bidding promotion and information flow know that to become a bidding expert, the most important thing is to understand data analysis, analyze the data every day, see a lot of information from the data, and thus improve your account. Then what about the case analysis of Baidu bidding SEM data? How to conduct data analysis in bidding? Let’s follow Dongguan editor Feng Chao to find out more!

Baidu bidding sem data case analysis, how to conduct bidding data analysis?

Identify account problems <br /> The first task of data analysis is to find problems based on the data in the account and determine optimization solutions.

So how do you find the type of disease? Here, it is recommended that you record daily account data in the marketing process table, which is especially useful for future data analysis.

For example, the figure below shows the account data for March and April organized using the marketing process chart.

SEM training-March marketing data summary SEM-March marketing data summary 2

Let's think about it first. What problems do you think exist in your account?

In fact, from the perspective of the editor, I think that although the marketing process chart organizes the data more clearly and at a glance, the data from day to day is almost the same, which makes it difficult for many novices to analyze and where to start. You can't determine the problems of the account based on the data changes of just a few days, right?

At this point, we can use the pivot function in Excel to compare the data for March and April.

As shown below. Can we clearly see the changes between the data?

SEM Training-Data Change Analysis

From the figure we can see:

1. Declining consumption

2. Decline in effective conversations

3. Decline in the number of leads

4. The cost of leads decreased by 97.24 yuan per lead

Segmentation Dimensions
After identifying the account problem, we need to analyze the problem and determine the optimization direction.

But how to analyze? What to base the analysis on? Most people will first determine the direction of account optimization based on keywords.

However, the number of keywords may reach thousands or even tens of thousands, which is not only troublesome but also has little effect. For example, my consumption words have not changed, but the consumption time period has changed. This cannot be analyzed through keywords.

Therefore, it is recommended that you analyze based on dimensions when analyzing data and determining optimization directions, such as time period dimension, regional dimension, plan dimension, device dimension, and planned keyword dimension, rather than simply focusing on keywords.

1 Time period dimension
Time period is a necessary factor in product conversion.

The following figure shows the conversion data of this account for the time period:

SEM-PC period conversion data PC period conversion data

SEM training-YD period conversion data

YD period conversion data

From the above figure we can see:

1. The conversion rate is good and the conversion cost is low during the PC time period of 10:00-11:00 and 14:00-17:00, while the conversion cost is high at 13:00 and 19:00

2. The cost of YD period is high at 13:00 and 17:00, while the conversion cost is low at 19:00-21:00

In view of the above, the optimization scheme can be operated as follows:

PC

1. Use time premium tools to control time consumption. Reduce consumption during the 13:00 and 19:00 hours periods, and increase premiums during the 10:00-11:00 hours and 14:00-17:00 hours periods.

2. Increase traffic in other time periods by adding synonyms of conversion keywords, increasing the price of conversion keywords, and exporting search term reports to add search terms that are not in the account.

YD terminal

1. Reduce the bid price of 13 points and 17 points on mobile by 10%

2. Increase traffic from 19:00 to 21:00 and raise bids for this period by 15%

Specific operations are adjusted according to the real-time ranking of the account

2 Platform Dimension
The following is a screenshot of the account’s platform conversion data:

SEM Training-Platform Dimension Platform Dimension

From the above figure we can see:

1. The conversion cost of PC is lower than that of YD

2. The click-through rate on PC is lower than that on mobile

In view of the above, the optimization scheme can be operated as follows:

PC

1. Added new display style for PC

2. Increase the price of conversion words on the PC side. For example: Region + business terms, price increase by 10%

Mobile

1. Reduce the average price of mobile terminals

2. Add new display styles for mobile terminals

3. Reduce the bid for competitor keywords by 25%

4. Reduce bids for common keywords by 5%

3 Unit Dimension
The following is a screenshot of the Account Unit:

SEM training-data screenshot

For privacy reasons, information related to the brand word has been erased. Please understand if this affects your browsing experience.

From the above figure we can see:

1. The conversion cost of common words and cost words is too high

2. The conversion cost of regional + center words and brand words is low

3. Competitive keyword plan: Brand-Other no conversion

In view of the above, the optimization scheme can be operated as follows:

1. Pause competitor words: brand-other-

2. Expand the regional + central keywords and increase the traffic of regional keywords. At the same time, increase the bid of regional + central keywords by 5%

4 Keyword dimension Keywords are also a major dimensional indicator in data analysis. By analyzing keywords, we can determine which words in the plan have good conversions and which words have poor conversions, so as to make targeted adjustments.

Here, I won’t mention it. It’s too heavy to lift.

The above is a complete set of data analysis processes.

1. First compare the marketing process chart to find out the disease type

2. Determine the optimization direction from four dimensions: time period, region, plan, and plan keywords

3. Implement optimization operations

In fact, data analysis is not as difficult as everyone thinks, but the prerequisite is that you have to have the right direction~ Well~ the editor has given you the direction here, and the rest depends on you. However, it is recommended to practice more data analysis, so-called truth is learned in practice!