飞瓜易投

Platform introduction:

飞瓜易投It is a "streaming data hub tool" created for domestic Douyin advertisers. It solves four types of advertising pain points: Data fragmentation : Huge amounts of advertising, thousands of rivers, star maps, and local push data are scattered in different backstages. Manual summary takes more than 2 hours/day, making it difficult to form an "omni-channel delivery view"; It is difficult to run materials : I don't know the core logic of "high-conversion advertising (such as script structure, emotional marketing points)", the cost of trial and error in material creation is high (For example, an advertisement has less than 100,000 exposure in three days); Opacity of competing products : Unable to monitor the "advertising rhythm of competing products (such as the streaming intensity during the new product promotion period) and hiding video advertisements" in real time, missing differentiated delivery opportunities; Blind placement optimization : The conversion data of CID advertisements and live streaming advertising is vague, making it difficult to locate the "exposure-click-transaction" loss link (such as high paid traffic clicks but low transactions).

Its core logic is to "reconstruct the advertising link with 'omni-channel data integration +AI material analysis'": there is no need to manually integrate data, and multi-platform delivery data can be opened with one click; there is no need to blindly create materials, and AI disassembles the core of high-volume advertising. Elements; no need to keep an eye on competing products, and the system tracks their delivery actions in real time; There is no need for lag optimization, real-time data + strategic suggestions help the iteration of streaming, allowing advertising to shift from "experience-driven" to "data-based precise execution", adapting to the needs of all levels from small and medium-sized streaming teams to brand groups.

Core functions:

1. Core: Four major functional modules

   (1) Multi-platform launch data integration: Omni-channel view is clear at a glance

   Solve the problem of "scattered advertising data and difficult to control overall delivery" and cover the mainstream streaming channels of Douyin:

   1. Access to huge amounts of data :
      • Omni-channel data aggregation: Integrate the core data of "huge amount of advertising (brand marketing), huge amount of thousands of rivers (e-commerce conversion), huge amount of star map (talent marketing), huge amount of local tweets (local drainage)" in real time. Example: A brand launch data shows that "huge amount of thousands of rivers accounted for 38.71%(1009.7w exposure), general advertising 32.07%(1101.5w exposure), and live streaming drainage 26.28%(487.3w exposure)", clearly understand the proportion of channels;
      • Unified presentation of key indicators: generate omni-channel delivery report according to the dimensions of "estimated exposure (such as 246.8w), interaction volume (likes/comments/shares, such as Helena Advertising Interaction 5000w), estimated sales, and number of advertisements". Support Excel export;
   2. Full coverage of launch types :
      • Adapt to "live streaming advertising (Qixi welfare advertising in Feigua Live Broadcast Room), product advertising (such as Helena Green Bottle Essence), CID advertising (precise attribution), and general advertising (brand exposure)" to meet different marketing goals (drainage/conversion/exposure).

(2) Real-time advertising monitoring and rankings: grasping industry launch trends

Solve the problem of "I don't know 'which advertisements are running and which products are selling strongly'" and provide industry reference:

1. High-launch list :
   • High-release advertising list: Update "Hot advertising materials, estimated exposure, and interaction volume" daily, marked with "launch platform (Qianchuan/Xingtu), promotion category (clothing/beauty/food)". Example: September 20, 2025 In the list, the advertising exposure of Feigua's official flagship store is estimated to be 246.8w, and the interaction volume is 246.8w;
   • High-launch product list: Display "product advertisements, estimated sales", help identify "popular products"(such as Maliardun Air Cushion Cream, Helena Green Aquarius Essence), and assist in product selection and delivery direction;
2. In-depth monitoring of single ads :
   • Minute-level data update: Track the "exposure trend, interaction fluctuations, and related group purchase conversion" of a single advertisement. Example: The estimated exposure of Helena Green Bottle Essence advertising is 6300.4w, likes 4320w, comments 1289w, and related group purchase data is simultaneously presented;
   • Dismantling of release details: Display "material size (such as 1080×1920), release time, promotion talent (such as Helena official account, 122.8w fans), content mentioned (preferential activities/product efficacy/out-of-box comparison)" to provide reference for material creation.

(3) AI disassembly of running volume material: quickly copy high conversion logic

Solve the problem of "low efficiency in material creation and difficult to capture the logic of running volume" and lower the creation threshold through AI:

1. AI core analysis capabilities :
   • Material tag extraction: Automatically identify the "core tags" of high-volume material (such as "Emotional Marketing","Product Efficacy" and "Logistics Introduction"). Example: A portable WiFi advertisement tag is "Free Shipping by SF Express, Fast Internet Speed, Free Traffic", Help locate user concerns;
   • Script and frame-by-frame extraction: Extract 4.2 million + advertising scripts and 1.68 million + video frame-by-frame images per day, and disassemble the "streaming capture logic in the first 3 seconds (e.g.,'Free shipping by SF Express!!' Strong benefits beginning), intermediate selling points presentation (product efficacy demonstration), and end conversion guidance (click to buy)";
   • Recommendation of similar materials: Enter the target material and recommend "similar advertisements of the same category with high running volume"(such as entering "essence advertisements" and recommending similar materials such as Helena Green Bottle) to stimulate creative inspiration;
2. Material running volume analysis :
   • Multi-dimensional scoring: Score materials according to "average running volume score, price fitness, and scene fitness", and screen "high-potential materials"(such as materials with running volume score of 80+ will be given priority);
   • Release effect correlation: Analyze the correlation between "material duration, label type" and "exposure/conversion"(such as "15-30 seconds of material with 'promotion activity' tags, the conversion rate is 25% higher than that of ordinary material") to guide material optimization.

(4) Tracking competitive advertising: benchmarking strategies and finding differentiated opportunities

Solve the problem of "competing product launch actions are opaque and difficult to differentiate competition" and grasp the dynamics of opponents in real time:

1. Full-dimensional monitoring of competing products :
   • Dismantling of delivery strategy: Enter competing brands/accounts and check their "distribution channel proportion (e.g., huge local push accounts for 20.57%), advertising update frequency (e.g., 12 ads per day), and core streaming products (e.g., a brand's main products are shoes, boots and bags, with 154 ads)";
   • Hidden video capture: Monitor the "hidden advertising videos on the homepage" of competing products (undisclosed streaming materials) and discover their "undisclosed running volume logic"(for example, a competing product's hidden video relies on "out-of-box comparison" running volume);
2. Launch trend benchmarking :
   • Comparison of exposure and conversion: Compare "estimated exposure (such as competing product 1809.7w vs competing product 1000w), interaction volume, and estimated sales", and position gaps (such as competing product Qianchuan has a high proportion of investment, you can adjust your own Qianchuan budget);
   • New product launch tracking: When competing products promote new products (such as "Maliardun Cordyceps Air Cushion"), they monitor their "streaming intensity, material direction, and preferential strategies" in real time, and quickly formulate response plans (such as increasing the streaming of similar products in advance).

typical application scenarios

• Brand advertising optimization : A beauty brand found through "material AI disassembly" that "high-running essence advertisements all contain the label of 'product efficacy demonstration + free delivery through SF Express'", and adjusted its own materials to add "Green Treasure Bottle Essence Repair Effect Demonstration + Next Day Delivery Logistics", the estimated exposure increased from 3000w to 6300w after launch, and the interaction volume increased by 70%;
• E-commerce investment flow adjustment : A food merchant found through "competitive product tracking" that "opponents relied on huge local promotions (accounting for 20.57%) to drive the conversion of local group purchases", so it increased the local promotion budget from 10% to 25%, the in-store write-off rate increased by 35%;
• Talent marketing selection : Through "Star Map Data Integration", a certain MCN selected "high-conversion talents (122.8w fans) collaborated with brands such as Helena" and recommended them to its beauty talents to cooperate with them. Talent advertising share increased by 40%;
• CID advertising optimization : Through "delivery data integration", a 3C merchant found that "CID advertisements have high clicks but low transactions". After AI analysis, it was "the material mentioned 'fast network speed' but the details page was not prominent." Optimization details The ROI after the page increased from 1:2.5 to 1:4.2.

applicable population

Unique advantages (compared to similar advertising tools)

1. High data integration on multiple platforms : The only tool that can simultaneously open up "huge advertising + thousand rivers + star maps + local push" to avoid "switching 4 backends to view data", and the efficiency of streaming data integration is increased by 60%;
2. Lead in depth in material analysis : AI not only extracts scripts, but also decomposes the "frame-by-frame map + emotion tags + running scoring", which can capture the "3-second streaming logic" better than tools that only look at the material, and material creation efficiency increased by 50%;
3. Competitive product tracking is highly comprehensive : Support "hidden video monitoring + distribution channel dismantling", master 30% more competitive product strategies than tools that only watch public advertising, and increase differentiated distribution opportunities by 40%;
4. Full coverage of streaming scenarios : Adapt from all scenarios of "brand exposure (massive advertising), e-commerce conversion (Qianchuan), talent marketing (star map), local drainage (local push)", without needing to switch multiple tools;
5. Novice-friendly design : Built-in "running volume material template"(such as "Benefit Start + Efficiency Demonstration") and "Streaming Strategy Guide"(such as "Small Budget Priority Local Push"). Novices can get started within 1 week, reducing trial and error costs by 70%.

precautions

1. Data reference description : The platform's "estimated exposure and estimated sales" are based on industry data models, and unofficial accurate data must be adjusted based on actual data released in the background;
2. Select paid packages on demand : Small and medium-sized merchants can choose the "Small and Medium-sized Streaming Team Edition", and brands/advertising companies need to unlock "Full Tracking of Competitive Products + Exclusive Consultant" to avoid redundant functions;
3. Control material compliance : When referring to running materials, you need to avoid "copying scripts/pictures", and you need to combine your own brand characteristics to create secondary creations to avoid infringement risks;
4. Real-time data delay : There is a 1-3 minute delay in advertising data updates (such as interaction volume and exposure volume). During peak hours (such as big promotion), the delay may reach 5 minutes, and an adjustment buffer period needs to be reserved;
5. Account rights management : When working with multiple teams, it is recommended to turn on "sub-account rights grading"(for example, streaming specialists view data and managers change budgets) to ensure data security.