4 steps to product advertising conversion: analysis of search advertising conversion

The ultimate goal of search advertising is to bring profits to advertisers. For example, medical advertising is to bring in effective patients; e-commerce advertising is to bring in product orders; and application distribution advertising is to bring in more app installations. Although the ultimate goals vary greatly, for search advertising products, the key points we need to focus on can be summarized as almost the same, that is, the conversion of the entire process (as shown in the figure below).

1. The first step of conversion - from keyword search to ad display

This is the first step of search advertising and the basis for subsequent processes. How to increase the number of ad impressions is crucial to improving monetization capabilities. Baidu searches hundreds of millions of times every day. With such a huge volume, there are countless advertisers found. It is impossible to display all the ads. Therefore, we need to consider two aspects.

User experience perspective

Imagine that when you search for "Beijing cuisine", the search result is "US presidential election". Isn't it a headache? Wouldn’t it be thoughtful if the search results included not only “Beijing Food Ranking”, but also “Food Nearby” or “Food Your Friends Have Visited”? So what factors need to be considered from the perspective of user experience?

1) Relevance between search terms and ads

The search terms and ads must be matched to the maximum extent possible. The ideal situation is that users cannot tell that it is an ad but a normal search result. This can minimize the damage that advertising causes to users. Here you can focus on the degree of match between the search terms and the title , picture, and description of the ad.

2) Search term association matching

Common ads are only displayed when they have repeated words in the search terms. This makes the chance of the ads being displayed very low, which is not conducive to increasing the amount of ad impressions. For example, when a user searches for "flowers", usually only flower shops will appear. However, if machine learning knows that Valentine's Day is in a few days, and the current user has previously searched for "buy gifts for girlfriend", then "chocolate", "necklace" and other products can be recommended in the search results at the same time. This will not only avoid a bad search experience for users, but also help users make decisions in multiple dimensions.

3) Improve the quality of advertising

Because the quality of ads varies, not all ads can be displayed, and ads need to be rated for quality. Here you can combine the relevance of the advertising creative itself. For example, the title of an advertisement is "IELTS Speaking Test", but the description and picture are of an abortion hospital. The relevance itself is extremely poor and it is impossible to be displayed to users. In addition, it is necessary to evaluate the historical click CTR of the ad, the conversion rate of the landing page , and the estimated conversion rate , etc., to comprehensively evaluate the quality of the ad and ensure that its display will not affect the user experience.

Customer Perspective

In search advertising, although brand advertising and top advertisers account for a large part, there are still a lot of mid- and tail advertisers who hope to make profits through search advertising. The quality of these advertisers may not be the highest, and their bids may not be the highest, so their ads may not get a lot of exposure. However, we must not give up on these large advertisers. Therefore, from the perspective of customers, we must focus on the interests of mid- and tail advertisers:

1) Rain and dew are equally distributed

Each search term is purchased by multiple advertisers. If the ads of the top advertisers or the advertisers with the highest bids are displayed every time, then the interests of the mid- and tail advertisers will not be obtained. Over time, this will cause the loss of these advertisers. In order not to abandon or give up the interests of each advertiser, we must find the right opportunities for exposure. For example, after users search for similar keywords several times, we can appropriately change the ad display strategy to allow mid- and tail-end advertisers to make profits and avoid wasting prepaid advertising fees.

2) Personalized business display

Each advertiser has its own business characteristics, and business characteristics need to be comprehensively considered when displaying to users. For example, when searching for "vacuum cleaner", you can personalize the display according to the classification of vacuum cleaners, such as "industrial vacuum cleaner", "handheld vacuum cleaner", "household vacuum cleaner", etc.; when searching for "hot pot", you can classify it according to distance, highest sales volume, most popular, etc.; when searching for "TOEFL", you can classify it according to the course classes, such as "1 to 1", "weekend class", "3-person class", etc. In this way, advertisements for each business can be customized, rather than simply in graphic or text form. This not only enriches the display style, but also improves the user experience and shortens the user's decision path.

2. The second step of conversion - from ad display to ad click

The conversion rate from ad impression to click is mainly determined by the ad display style. For example, the traditional graphic and text advertising style includes four elements: title, picture, description, and text link. The key to improving conversions lies in how to improve the relevance between these four elements, as well as the relevance between these four elements and user intent, so as to increase click-through rate .

Explore user intent and increase click-through rate

Search is a magical thing. When users search for "Dior", they may want to know about the brand, related products, or the latest news within the company, etc. So if we deeply explore user intentions and display the content that users are most concerned about, we can effectively increase the click-through rate.

For example, through training the model, we know that this user also searched for " Lancôme perfume" and "perfume price" yesterday, so we can guess that this user has the intention to buy Dior perfume. Therefore, when displaying advertisements, we can appropriately expose the e-commerce perfume pictures and prices, and even expose the purchase button to shorten the purchase path. This kind of advertising display will promote user decision-making and win user praise.

Diversify content rewriting to attract users to click

When uploading advertising materials, advertisers often do not compile many sets of templates. If the same set of advertising copy is always used when it is displayed to users on the front end, it will cause reading fatigue and lack of novelty. Therefore, intelligent title rewriting and description rewriting become extremely important.

For example, when searching for "difference between TOEFL and IELTS", we can guess that the user's intention is that he doesn't know which one to take and what are the advantages and disadvantages of each. Therefore, we can rewrite it as "What is the difference between TOEFL and IELTS? What are the advantages and disadvantages of each? Which one is easier to take?" This can hit user needs in multiple dimensions and increase clicks.

For example, if you search for "coffee shop", combined with the current user portrait (post-90s, college students) and the weather (rainy day), the title can be rewritten as "Top 10 coffee shops best for post-90s college students on rainy days", etc. With such a title, would you be able to resist clicking on it to take a look?

Intelligent matching of pictures to increase click desire

In the search results, display ads with pictures always have a higher click-through rate than pure text ads without pictures, which shows the importance of pictures. However, there are many problems with the images in the search results now, such as uneven image sizes, deformation, low quality, etc., which have a negative impact on users and affect clicks. Therefore, improving the quality of pictures is as important as rewriting the content mentioned above. We can label all images, such as labeling industry images, labeling product image categories, and so on. When we need to adapt advertising images, we can obtain them from the image library for display. Each refresh can display different images, which not only improves the image quality but also brings a sense of freshness to browsing.

3. The third step of conversion – ad click to landing page click

For the CPA settlement method, advertisers are charged based on the results, so the click CTR of the landing page is crucial.

Direct link to third-party landing page

Ordinary ad spaces (such as graphic and text ads) will directly link to a third-party landing page after being clicked. It is difficult for us to monitor the click effect. We can only allow advertising when we strictly control the qualifications of advertisers and conduct effective audits of third-party landing pages.

Marketing promotion landing page

In addition to the direct link situation above, we can also configure the landing page ourselves when doing marketing promotion .

For example, when searching for Chongqing food, the results will show Chongqing food rankings, the best Chongqing hot pot rankings, etc. These advertising positions need to be configured by search ads; for example, during the Double Eleven promotion and the Spring Festival promotion, we can configure the event promotion landing page ourselves and cooperate with advertisers. The landing page here needs to be provided by the search ad party.

To this end, it is necessary to make a reasonable product structure division, combine the user portrait to display the most important fields, provide users with the content that they are most interested in, and improve click-through conversions.

For example, food rankings can be divided according to categories, such as hot pot, buffet, Western food, etc. The promotion landing page can be divided according to discount intensity, distance, sales volume, etc. The landing page information can be displayed to each user based on the current user's category preferences, price preferences, search preferences, etc., to improve click-through conversion.

4. The fourth step of conversion - landing page click to subsequent conversion

Most of the subsequent conversions here are completed on the advertiser's page, so search advertising cannot interfere too much. What can be done is to monitor the advertiser's order conversion and make the estimated conversion model more accurate by continuously improving the training model, so as to improve the overall conversion rate of the delivered advertisements.

The conversion of each process of search advertising is crucial to revenue. Therefore, when making advertising products, we must pay attention to the conversion loss at each step. At the same time, advertising products should not only face the user end, but also pay attention to advertisers. Only by effectively combining both parties and conducting comprehensive analysis can the advertising products be just right.

Mobile application product promotion service: APP promotion service Qinggua Media advertising

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