Commercialization strategy of e-commerce search traffic distribution

In this chapter, we explain the commercial distribution strategy of search traffic in e-commerce search .

1. The value of commercialization of search traffic

For e-commerce platforms, the value of commercializing search traffic can be summarized as follows:

1. For e-commerce platforms

The monetization of search traffic is the main source of platform profits. Taking Alibaba’s e-commerce platform as an example, its advertising revenue (mainly from traffic monetization) in fiscal year 2019 was 174.5 billion yuan, and JD.com’s advertising revenue in fiscal year 2019 was 42.6 billion yuan.

Not only is the scale of advertising revenue large, but it also accounts for a high proportion. Let’s take the purest e-commerce platform PDD as an example. PDD basically only has a merchant C model, with very few self-operated businesses and very few other businesses. Such revenue mainly comes from merchants. In the 2019 fiscal year, advertising revenue was 26.8 billion, accounting for more than 80% of the platform’s total revenue.

2. For merchants

Advertising is an effective way for businesses to actively acquire traffic. The distribution of free traffic is more about following platform rules and competing with other businesses within the rules, while advertising acquisition can actively control the customer acquisition object by setting advertising bids, delivery time and promotion targeted population. The scale of customer acquisition and time of customer acquisition are decided independently by merchants based on their own business conditions.

3. For consumers

Advertising is one of the main sources for consumers to obtain new products and new stores, and to obtain a wealth of consumer objects and novelty. Generally, new products and new stores will be advertised on the platform. Exquisite pictures and interesting interactive designs can stimulate consumers' emotional resonance and trigger consumption trends.

2. Two strategies for monetizing search traffic

On e-commerce platforms, there has always been a game relationship between traffic distribution between the platform and merchants. The platform wants to earn as much profit as possible through traffic distribution, while merchants want to obtain as much free traffic as possible. However, there is also a balance of interests between the two, that is, the comprehensive affordability of the merchants.

If the platform excessively seizes the operating profits of merchants, the merchants will eventually be sucked thin by the fat ones and killed by the thin ones. However, if merchants take advantage of the platform to obtain free traffic, the platform will eventually be unable to maintain a closed-loop sustainable business model and will go bankrupt.

Therefore, in terms of traffic monetization, the overall goal is to achieve a dynamic balance between the platform and merchants. The laws of economics are actually at work behind this. This is why Amazon has fewer economists than the Federal Reserve. Platform-driven processes are actually driven by economic interests.

In terms of specific monetization strategies, we implement a strategy of coordinating free and paid services according to the size of the category and a strategy of decreasing the differential size of the category. The former is mainly aimed at large merchants in the same category, while the latter is mainly used by small and medium-sized merchants. We elaborate on the specific strategies in detail.

For medium-sized and larger merchants, they have certain operating strength and are the main beneficiaries of e-commerce platforms. They have a certain sales scale. The platform can easily calculate the merchants' operating costs and gross profit levels based on the merchants' business categories, and calculate the traffic costs that the merchants in each category can bear.

If the merchants make higher profits, the platform will force them to invest more in advertising to obtain paid traffic by adjusting their ability to obtain free traffic. If the merchants do not invest, then under the regulation of the platform behind the scenes, their ability to obtain free traffic will become smaller, thus creating a vicious cycle that further reduces their ability to obtain free traffic. At this time, the merchants will know that they should increase their investment.

The increase in investment has reached an ideal ratio between free and paid services, so that merchants' ability to acquire traffic remains basically stable amid competition. Of course, the operational details are achieved more through the merchant’s self-understanding, third-party training, or communication between the platform’s waiter and the merchant.

For small merchants, due to their poor business operation capabilities, unstable business conditions, and large number of merchants, it is impossible to achieve the coordination of free and paid services through the above-mentioned operation + system regulation. The payment scale is more determined by the sales scale of such merchants within a certain period of time. This rate (paid traffic amount/sales scale) is related to the merchant's business category. Different categories have different gross profit margins, and the calculated rates are also different.

In fact, this method can also achieve the goal of survival of the fittest among merchants. Merchants that cannot afford it will be eliminated by the platform, and merchants with good operations will have the opportunity to be promoted to medium-to-large-scale merchants and enter the aforementioned strategic state.

Commercial pricing is the core capability of the platform. It cannot drain the pond to catch fish, nor can it be fleeced by merchants. This tests the platform's strategy and pricing capabilities. Behind this is actually the depth of understanding of the market and business by the platform staff, which determines the richness of the platform's pricing and the diversity of its strategies.

3. Front-end performance of search ads

On the front page of the APP, e-commerce search ads mainly have the following locations and forms:

1. Search shading (also becomes the default search term)

It has a large exposure volume and is calculated based on CPM (cost per thousand impressions), which is suitable for capturing users’ minds.

2. Search for recommended words

It has a large exposure and is based on CPC (pay per click), making it suitable for targeted audiences.

3. Search Hengtong

Accurate, pay by CPM.

4. Search CPC advertising space

Accurate, pay according to CPC.

5. Search for stores

Accurate, based on CPM or CPD (pay per day).

6. Brand dominance

Be precise, hit the user's mind, and pay according to CPM/CPD.

4. Commercialization Incentive Leverage

As the current user scale has peaked and it is becoming increasingly difficult to expand incremental business in the industry, major platforms have stepped up their traffic harvesting. In order to encourage suppliers to invest in platform resources, the weight of supplier investment assessment is increased in the search traffic allocation model. The more they invest, the more free traffic they will be allocated.

Whether more traffic can be allocated depends on the following factors:

1. The amount of advertising spending by the merchant;
2. Advertising rate (the proportion of advertising expenses to sales);
3. The continuity of merchants’ advertising;
4. The proportion of the merchant's advertising products to the store's products;
5. Popularity of advertised products among users: measured by the exposure click-through rate of advertised products and the order conversion rate of advertised products.

5. CPC advertising bidding and placement logic

CPC ranking: Comprehensive ranking = bid x quality score

CPC per click deduction = (next bid x next quality score) / own quality score + 0.01 yuan

The main factors affecting quality score:

• Product factors: sales volume, reviews, DSR, customer service response, and sell-out rate;
• Relevance: relationship between search terms and titles, category relevance, attribute relevance, and degree of complete attribute matching;
• The volume of attention paid to a product: the number of collections and clicks, the greater the market demand for the product;
• Promotion and operation capabilities: The higher the ROI, the more efficient the through train is and the more sustainable the promotion is. Any promotion that is not for profit is a hooligan and will not last long.
• The integration degree of the promotion plan, that is, the promotion qualifications, includes the length of time the promotion plan has been in operation and the amount of investment. This is an accumulation process, so do not delete the promotion plan easily;
• The degree of attention paid to the product, i.e. the click-through rate. The higher the click-through rate, the more the audience likes the product.
• The probability of a product being purchased is called the conversion rate. The higher the conversion rate, the greater the market competitiveness of the product.

The most important thing is click-through rate, and the second most important thing is conversion rate.

VI. Conclusion

In the second half of the platform when the user scale peaked, Internet platforms increased their harvest of existing traffic, among which commercial traffic monetization was the main way of harvesting. The underlying logic behind the current advertising monetization of mature platforms is how to balance the distribution of interests between merchants and platforms. The platform’s goal is to prevent merchants from taking advantage of the platform and obtaining too much free traffic, but also to prevent them from taking too much profit from merchants, causing them to continue to operate at a loss. This is actually economic knowledge.

Based on the business capabilities and category characteristics of the merchants, for medium and large merchants, set a reasonable paid traffic ratio, and use the synergy of free and paid traffic to make dynamic adjustments.

For small sellers, a certain proportion of consumption is required mainly based on sales scale and category characteristics. If they cannot afford it, they will naturally be eliminated by the platform. This is also the reason why some merchants generally reflect that it is almost impossible to obtain free traffic without promotion, because these merchants have basically no management and operation capabilities on the platform. Even if they are given free traffic, the final conversion effect is very poor. The only outcome is that they will be eliminated by the platform.

7. Final Thoughts

The current society has entered the second half of the demographic dividend. Every company is improving its digital capabilities and working to tap into the value realization and value enhancement of existing users (Kuaishou, Douyin, Baidu, and Sina are all engaged in e-commerce, and offline companies are busy transforming). Matching supply and demand transactions between goods/services and consumers is the main way to commercialize and realize profits, and search recommendations are the main mechanism for achieving supply and demand matching.

At present, only a few leading Internet companies in China have a mature and complete talent team. Other companies either have scattered professional talents and insufficient knowledge structure, or have no such talents at all. The contradiction between the huge talent demand in society and the serious shortage of high-quality talent in society has restricted the improvement of many companies' business in this area, and also restricted the improvement of young people's professional income and career space.

Given the professional characteristics of search recommendation, there is relatively little public systematic information, and the difficulty of the information varies, making it difficult to meet the urgent needs of enterprises and professionals. I have focused on e-commerce for the past 10 years, and have been deeply involved in and led the construction of the search recommendation traffic distribution and product management systems of the two major e-commerce platforms. I am familiar with the strategies, products, operations, data, and R&D of e-commerce platforms, and have summarized and refined them into building a practical e-commerce search system, a practical e-commerce recommendation system, a practical e-commerce product management system, and a series of articles on observations on new e-commerce retail.

Author: Product Expert Mao Xin

Source: Product expert Mao Xin