Why do we need to conduct research on high clicks on live visuals? (1) Feed direct investment is not working Many merchants ’ live streaming rooms have low click-through rates and poor efficiency through direct feed delivery, so they can only rely on short videos to attract traffic. The lack of a direct feed delivery traffic entrance means that it is difficult to increase the GMV volume of live streaming. Quoting the golden formula, it is proposed that the more mature the live broadcast room, the greater the proportion of feed traffic. Therefore, the direct feed difference is an issue that cannot be ignored. Provoking thought: What are the factors that influence direct investment? (2) Visual information directly affects feed click-through rate When the anchor, products, delivery and operation team are all stable, changes in the visual information in the live broadcast room will cause changes in the feed click-through rate and live broadcast click-through rate. (3) External click-through rate - Feed ROI - Natural traffic GMV contribution Conclusion of visual optimization verification of the brand: Through visual optimization, the direct click-through rate of the feed is effectively improved, the feed input-output ratio is increased, and the flow structure of the feed and short videos is optimized; the viewing click-through rate and shopping cart click-through rate at the front end of the live broadcast room conversion funnel are broadened, and the GMV contribution brought by natural traffic is improved. "Drill down to optimize the content strategy of the live broadcast room, how to improve the click-through rate of the live broadcast room through visual optimization, reduce subjective judgment suggestions, systematically increase data indicators for testing and verification, and output a reusable live broadcast room optimization methodology to help brands effectively increase their live broadcast room indicators at a low cost." Core solution: amplify the unique competitiveness of the live broadcast room. Looking at all the high-click live visual images, we found that even if some live broadcast rooms have poor visual quality, uneven color matching, and serious lighting problems, they still have a high click-through rate. But without exception, they all displayed the competitiveness of their live broadcast rooms in a crude way. The essence of increasing the click-through rate of a picture is not to make it more artistic or beautiful, but to improve its competitiveness. Therefore, the "strategy to increase click-through rate" is actually "how to find the competitiveness of the live broadcast room and the strategy that allows users to see it quickly." The goal of this article is to provide solutions from two points: "finding the competitiveness of the live broadcast room" and "how to amplify it". Targetedly improve the click-through rate of the live broadcast room. 1. What is the competitiveness of the live broadcast room and how to find it? 1. Five core competitive advantages of feed click-through rate The total of 45 positive and negative top samples were classified based on the competitiveness of the block with the largest screen area, and the results were: (The largest and most conspicuous area means that only one competitive advantage can be highlighted. Trying to highlight multiple competitive advantages at the same time will weaken the core information.) Figure 01 Good Case: Only highlight the core competitiveness of the live broadcast room Figure 02 Good Case: Leave enough space for the scene, no need to add more sticker information Figure 03 Bad Case: Trying to pass multiple core messages at the same time 2. How to find the competitiveness of the live broadcast room? Summary of practical experience in creative design linkage content operation: 2. How to enhance the competitiveness of the live broadcast room? Let’s take a look at how the high-click live broadcast rooms are done. Split the live broadcast images into labels and find features. 1. Extraction of benchmark live broadcast rooms and summary of excellent commonalities Sample selection: Sort by feed direct click rate in descending order, with higher click rates as positive samples and lower click rates as negative samples. Summarize the visual features that positive samples have but negative samples do not have as the influencing factors of high click vision. 2. Split from the perspective of the live broadcast room screen Splitting logic: After discussing with the designers, split according to the live screen area. Avoid subjective identification factors and perform text labeling analysis. 3. Summary of the Phased Research (Time Dimension: July 2021) The core factors affecting FEED click-through rate: Detailed disassembly: The 'grey' area represents the characteristics of high CTR images. It is intuitively found that the proportion of grey area is obviously reduced in low CTR images. Core summary: (1) Real scene CTR > virtual background (2) Three top click scenarios: warehouse, shipping location, and retail store; Commonality: They are all points in the product production-distribution chain. This can be extended to other similar high-click real scenes: etc. (3) Specific clothing and accessories will increase the anchor’s sense of character and the strength of his personality Commonality: Anchors with personality and style are more attractive to users to click and watch. (4) Concise slogans that reflect the brand and product can increase users’ interest in the live broadcast room. (5) The core information should be enlarged to the most prominent position; large areas without content will not attract users to click. (6) Low-saturation and low-brightness colors will make the vision softer and more comfortable; on the contrary, colors that are too bright and too vivid will easily cause users to avoid them. (7) The way products are displayed has little impact on CTR. Detailed disassembly (1) (2) Real scene CTR>virtual background; Three top click scenarios: warehouse, shipping location, and retail store; commonality: they are all points in the product production-distribution chain. This can be extended to other similar high-click real scenes: etc. a. Content dimension: scene/real scene type b. High CTR case (28 samples) (Among the real scenes: 64% are real scenes; 36% are green screen simulated scenes) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: The background, anchor, and text information are the points that can create a gap with other live broadcast rooms through visual changes, and they are the dominant factors. Detailed disassembly (3) Specific clothing and accessories will increase the host's sense of role and the strength of their personality. Commonalities: hosts with personality and style are more attractive to users to click and watch. a. Content dimension: anchor b. High CTR case (28 samples) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: Background, anchor, and text information are the points that can create a gap with other live broadcast rooms through visual changes, and are the dominant factors. Detailed disassembly (4) Concise slogans that reflect the brand and product can increase user interest in the live broadcast room. a. Content dimension: text information b. High CTR case (28 samples) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: The background, anchor, and text information are the points that can create a gap with other live broadcast rooms through visual changes, and they are the dominant factors. Detailed disassembly (5) The core information is enlarged to the most conspicuous position; large areas of space without content cannot attract users to click. a. Content dimension: Area share of each sector (Understand: the type of section that users see at first glance. Comments are excluded) b. High CTR case (28 samples) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: Area division and color are points for improving the efficiency of visual optimization and are common auxiliary factors. Detailed disassembly (6) Low-saturation and low-brightness colors will make the vision softer and more comfortable; on the contrary, colors that are too bright and too vivid can easily cause users to avoid them. a. Content dimension: color b. High CTR case (28 samples) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: Area division and color are points for improving the efficiency of visual optimization and are common auxiliary factors. Detailed disassembly (7) The way the products are displayed has little impact on CTR. a. Content dimension: Products b. High CTR case (28 samples) c. High click case d. Low CTR case (16 samples) e. Low click case f. Insight: Area division and color are points for improving the efficiency of visual optimization and are common auxiliary factors. 3. How to improve click-through rate through visuals? 1. Solution Let’s go back to the core idea at the beginning of this article: amplify the competitiveness of the live broadcast room. Now we know how to scale up, and how to find competitiveness. The solution is obtained based on practical experience: 2. Practical examples Ideas (1) Amplify brand advantages and add brand logo and slogan. There is no scene advantage, but scene elements can be added to expand the blank area. Adjust the overall color to low brightness. Verification result example: Industry: Food and beverage industry Ideas (2) Use real outdoor scenes without adding any other sticker information elements, so that the scene content occupies most of the screen. Verification result example: Industry: Food and beverage industry Ideas (3) Amplify the welfare advantages and effectively increase the click-through rate. Verification result example: Industry: Food and beverage industry Ideas (4) Amplify price advantages and fill in blank areas to increase click-through rates. Verification result example: Industry: Food and beverage industry Ideas (5) Use real scenes to attract viewers. Verification result example: Industry: 3c industry 4. Summary Review of the factory live broadcast cases in May. In the early days it was new and competitive. This later triggered a rush of businesses to imitate it, making factory-style live streaming a phenomenal way of playing. If there are 10 broadcasts and 10 of them are factory live broadcasts, will the real factory scenes still have a high click-through rate? Not necessarily, because there is no difference, and a single live broadcast room has lost its competitiveness. Among all the cases of factory live broadcasts, we also found cases with low clicks. Is the factory scene available for all products? In the food and beverage industry, snacks/primary agricultural products/grain, oil, rice and flour may be applicable, but for functional products, is factory live broadcast the best choice? Not necessarily. The real scene of the factory shows the source/price advantage of the food, it cannot explain the efficacy. Author: Juliangxue Source: Quantitative Science |
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