Advertising guru John Wanamaker once said, "I know that half of the money spent on advertising is wasted, but the problem is I don't know which half." This wise saying can be called the " Goldbach Conjecture " in the advertising and marketing industry. Customer acquisition, which is mainly based on delivery, promotion , fission and other means, as the first level of the AARRR funnel model , has always been a headache for many people. On the one hand, market competition has intensified, advertising effectiveness is difficult to guarantee, and the cost of acquiring customers is getting higher and higher. This is one of the reasons why growth methods such as distribution fission have gradually become new means of acquiring customers in the industry. On the other hand, promotion technologies and methods are constantly being updated, but those who are involved in the delivery, operation , and marketing of these jobs find it difficult to find a reliable methodology to guide themselves on how to operate accurately. The longer many people work in these positions, the greater their need to optimize their work content and processes through feedback from data analysis . In this article, I will try to use the example of SEM advertising , analyze the two dimensional indicators of conversion rate and click-through rate through modeling ideas and channel advertising, and share with you how to find possible problems from existing data results and then optimize promotion conversion methods. This method can also be reused in product and operation data analysis feedback. For channel operations, reliable SEM marketing has three core elements: product positioning, business familiarity, and market changes.
As shown in the figure above, we use two common data indicators in channel operations - click-through rate and conversion rate as latitudes, with click-through rate as the horizontal axis and conversion rate as the vertical axis to build a channel conversion model. From this, we get 4 quadrants, each corresponding to a different channel effect, namely:
Each quadrant represents a different result, and the corresponding reasons for the result are also different, and the actions that ultimately require iterative adjustments are also different. By modeling and breaking down the existing business situation, we can more clearly see the current explicit problems, analyze the hidden problems behind them, and ultimately seek leverage solutions to achieve twice the result with half the effort. Next, we analyze the reasons behind each quadrant one by one. Quadrant 1: Precise audience (high click-through rate, high conversion rate)This type of advertising has a high click-through rate and a high conversion rate. It can be simply understood as many people clicking on ads and at the same time making inquiries or purchases. This shows that users are more willing to click on this ad, and many people successfully convert. This further shows that this type of ad delivers "the right information to the right people", and this channel is very valuable and needs to be explored further. Therefore, its optimization direction should focus on how to expand high-quality traffic and increase advertising click-through rate by expanding exposure and clicks to targeted groups of people.
Quadrant 2: Bad ads (low CTR, high conversion rate)This type of advertising has a low click-through rate but a high conversion rate. It can be simply understood that only a small number of users clicked on the ads, but among those who clicked on the ads, many people made inquiries. This shows that the ad landing page and product value information are delivered accurately, and there will not be many problems at the website level. The main problem should be at the advertising level, such as poor ranking or unattractive creativity. Therefore, the optimization direction should focus on how to optimize the creativity of advertisements and ranking exposure to increase click-through rate.
The third quadrant: inaccurate crowd (low click-through rate, low conversion rate)This type of advertising has a very low click-through rate and conversion rate. It can be simply understood as few people click on the ads, and even if they do, few people inquire about them, and there is no conversion. This means that the advertisement is not well presented to the target audience, or the creative idea of the advertisement is not attractive enough. There may also be issues at the site level. Therefore, the optimization direction should focus on how to optimize the creativity of advertisements and their ranking exposure to increase click-through rate. We should also pay attention to the matching of traffic and optimize the accuracy.
Under the premise of low traffic, we should focus on optimizing the above five directions first. Quadrant 4: Lost people (high click-through rate, low conversion rate)This type of advertising has a high click-through rate but a low conversion rate. It can be simply understood that many people click on the ads, but none of them generate inquiries. This may indicate that the advertising creativity is exaggerated to induce netizens to click; in addition, the low conversion rate may also be caused by the website and product (service) itself, such as slow website opening speed, poor landing page construction, and no advantages of the product itself. Therefore, its optimization direction should focus on how to optimize the product's value output, core selling points, and the path and experience optimization after users enter the landing page. Channel level:
Website level:
Whether the various elements of the product occupy a dominant position in the market, and whether the operational actions, marketing activities , promotional methods, etc. occupy an advantageous position among peers, this can greatly affect conversion. Analyze competitors at any time to know yourself and your opponents. Source: Mr. Ant |
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