(III) Search Advertising Bidding Strategy

The following mainly explains the strategies for achieving the goal of "click count". There are two main categories of strategies: "automatic bidding strategy" and "manual bidding strategy". If it is "test search ads" or ads in the adjustment period, I recommend using the "manual bidding strategy". If there is not much change in the data in the short term, you can switch to "strive for as many clicks as possible" and set the highest upper limit bid.

Note: The above is a screenshot of Google Ads settings.

1. The following explains the corresponding strategy using

1.1 Aim for as many clicks as possible

This is an automatic bidding strategy. It's the easiest way to increase clicks. You simply set an average daily budget, and Google Ads will automatically manage your bids to get as many clicks as possible within that budget.

1.2 Maximize the number of conversions

If you want to optimize to maximize conversions but only want to use your full budget instead of targeting a specific CPA, you can use the "maximize conversions" bidding strategy.

1.3 Maximize conversion value

If you want to optimize with the goal of maximizing conversion value, but only want to use the full budget instead of targeting a specific ROAS, you can use the "maximize conversion value" bidding strategy.

1.4 Target Impression Frequency Share

This bidding strategy automatically sets bids to display your ads anywhere on the absolute top, top of the page, or any location on the Google search results page.

CPC Manual Bidding: This bidding strategy allows you to manage your maximum CPC bid. You can specify different bids for individual ad groups within a campaign, or for individual keywords or placements. If you find that certain keywords or placements are generating more revenue, you can use manual bidding to allocate more ad budget to those keywords or placements.

2. Recommended strategy details

a. This method uses manual bidding based on cost-per-click , primarily for search ads. Optimizers can manage budget bids for different ads and keyword phrases based on strategies and performance. It is suitable for accounts with professional optimization specialists, and is a commonly used bidding strategy during normal campaigns and A/B testing.

The primary ad campaign type is "Search Ads or Display Ads." The maximum bid per click is controlled for each ad group, keyword, or placement. The main objective is to increase website traffic; it's not necessary to reach the target budget every month.

b. The "Aim for as many clicks as possible" bidding strategy is primarily used to increase website traffic. It allows setting a maximum cost-per-click bid for the entire campaign. Suitable for accounts that don't have time to monitor keyword adjustments, it's applicable to campaigns where overall keyword bid adjustments aren't significant. Compared to manual strategies, its ability to optimize individual keywords is weaker.

You've set an advertising budget. You don't want to spend time monitoring and updating individual CPC bids, and you'd rather have Google Ads automatically update those bids for you.

3. The Impact of Ad Quality on Bidding Strategy

Ad quality score affects ad traffic acquisition, determining ad ranking and eligibility for display . It's calculated using your bid, ad and website quality, search context, ad rating thresholds, and the projected impact of add-ons and other ad formats. Here are 4 ways to improve ad performance using your quality score.

Note: The above is a screenshot of the Google Ads data dashboard.

3.1 Review the elements of the quality score

To understand which specific areas need improvement, analyze the three elements of the score:

Expected click-through rate: The likelihood of an ad being clicked when it is displayed.

Ad relevance: The degree to which an ad matches a user's search intent.

Landing page experience: The relevance and usability of the landing page for users who click on the ads.

Note: The above is a screenshot of the Google Ads data dashboard.

These elements help you determine whether to update your ads, keywords, or landing page content. Each element has a corresponding status, which is active when...
When the performance is "below average", corresponding improvements are needed.

3.2 Improve the relevance of advertisements to keywords

If the ad relevance status is "below average", you can try the following practical approach:

Modify ads: Match ad text content more directly to user search terms.

Keyword grouping screening: For ad groups where the keywords are difficult to cover, split the ad group into multiple ad groups with varying degrees of relevance to the user's search content. (Note: For details, please refer to Account Setup, Keyword Grouping);

Note: The above is a screenshot of a Google Ads ad dashboard.

3.3 Optimize to improve click-through rate

Projected click-through rate (CTR) indicates the likelihood that a user will click on your ad. If your projected CTR is listed as "below average," try the following practical approach:

Modify ads: Ensure ad content and keywords are relevant and can attract the attention of the target audience.

(Note: For example, "Highlight the unique advantages of your product or service, such as free shipping. Use calls to action relevant to the landing page.")

Tip :

Search ads are charge-per-click, so optimizers use conditional ad copy to filter for precise traffic. The more specific the ad, the lower the click-through rate, but the higher the conversion rate for ads with strong user intent & ). The key is to find the balance that yields the best results within your target audience.

Optimizing and iterating landing pages to provide visitors with an excellent website experience is one of the key factors in generating inquiries. Here are some practical tips:

Relevance: Ensure that keywords align with user intent, and that the promotional information in the ads and landing pages is consistent. Ensure that the offers or calls to action in the webpages and ads are consistent.

Page conversion rate: Use conversion rate as a proxy metric to measure the quality of the landing page experience. (Note: For example, check CTA clicks, visit path, visit depth, dwell time, and page inquiry conversion rate.)

Device compatibility: Page loading speed can determine whether a user leaves the page or continues inquiring. Adapt to PCs and mobile devices. (You can use the official PageSpeed ​​Insights tool to check page performance).

Summarize

4. Practical Case Application Effects

4.1 Application of Low-Traffic Cost Structure Strategy for Large Models (Level 3 Optimization)

Below is a case study of ultrasonic cleaning machine manufacturing. We will use the optimization data from this case study to break down the process and hope that our execution process can help you understand the "difference between the two strategies".

implement:

①. Increase UV volume: By analyzing the search habits of the target users of the business, without making adjustments to other dimensions, we chose to expand the data by adding keyword categories. Compared with the previous advertising campaign materials, there are 243 promotional keywords; the traffic cost is 5.83 yuan/traffic; after data calculation, a single advertising campaign needs about 800 or more keywords.

② Finding 800 phrases that satisfy the three elements of keyword research is quite difficult. Through research on industry users' search habits, competitor research, and platform background checks, it was discovered that "capacity, power, frequency, material, appearance, application, etc." are all customer concerns. Therefore, keywords related to available capacities from 710mL to 27L were analyzed, along with power ratings from 200W to 1300W...

Note: The above screenshots show some keywords related to the project. For detailed information on account setup standards, please refer to the Account Setup section.

③. Maximize effective UV within the unit budget: Reducing the cost per click is the most direct way. According to calculations, the traffic cost needs to be reduced to ≤6 yuan/click; and the daily click volume needs to be ≥120 times to meet the requirement of 2~3 daily advertising inquiries; the cost per inquiry should be in the range of 240 to 360.

Note: The above are screenshots of the Google Ads campaign backend.

④. UV Search Intent Optimization: Google Ads search term reports only show a subset of users' search terms, but it's still worthwhile to invest significant time in analysis and research. By understanding user search terms, you can further target traffic. For example:

a. Intent analysis of matched keywords, expanding keywords for users' localized names of business products; essentially, users only care about the business content or solutions they need at the moment.

b. For product analysis that matches keywords, if the search engine algorithm misunderstands the product-keyword-use intent matching, these words should be blocked.

Note: Intent analysis of search keywords has more applications in ad campaign management; this section only discusses traffic and phrases.

⑤. Performance Comparison: During the A/B test, "the large model strategy was compared with the low-price precision strategy; the average cost per click decreased by 3.56 yuan, and the cost per inquiry decreased by 240.1 yuan; and the strategy achieved traffic growth and an increase in the proportion of effective UV traffic; Note: The following data does not include page conversion rate optimization, and the increase in the proportion of effective UV is "mainly judged by conversion rate improvement and search terms";

Testing phase (standard low-price precision strategy):

Testing (Large Model Strategy):

Note: The above data is presented as supporting evidence for project optimization and is for reference only.

4.2 Multi-dimensional Precision Conversion Rate Structure Strategy

A multi-dimensional, precise conversion rate strategy, focusing on localized conversion rate optimization for key ads, and the segmentation and expansion of traffic dimensions. In the era of stagnant growth and intensified competition, traffic management has entered a phase of intensive cultivation; the days of achieving results with minimal effort are long gone. Below is a case study of an optimization strategy applied to a specific raw materials industry.

Execution:

①. Increase UV traffic: The project's business is "flocking powder materials, flocking equipment, flocking adhesive," a small category that is a highly specialized industry, and the monthly average traffic for the broader industry keywords is less than 1,000, totaling less than 3,000 per month. The first step is to create a traffic model for each category. Below is an example where the global average monthly clicks for flocking powder materials are less than 100.

 Note: The screenshot is from the Google Ads backend.

After calculation, the initial focus of expanding business keywords was on categorization to cover as much of the user's commercial search intent as possible. This was to ensure the acquisition of the lowest-priced, high-quality traffic within that category, according to the strategy. Below is a sample of the expanded keyword phrases. Later, during the campaign, the estimated search volume for the keywords was low, and a reverse lookup revealed no ad slots, so they were removed.

Note: The above screenshots show some keywords. For details on account setup standards, please refer to the account setup section.

②. Page conversion rate optimization is crucial. It's essential to segment advertising pages for different product categories and improve landing page experience and conversion rates. Creating corresponding pages for different categories can significantly improve visitor CTA behavior data. Note: This project does not analyze page conversion rate optimization; please refer to the Ads section and the Landing Page Planning section for details.

Note: The screenshot is from the clarity.microsoft backend;

③. Results Presentation: Below are screenshots of project data, illustrating the application of multi-dimensional strategies in niche industries, where expanding traffic is difficult, and category conversion rate optimization models. If your industry also meets the characteristics of "few traffic, high industry competition, and high traffic costs," you can try taking action.

Note: The screenshot is from the Google Ads backend.