"Almost the same white lace dress, I sell it for 299 yuan and no one cares, why does the competition store sell 599 yuan and sell more than 10,000 yuan a month?" "Why do competing stores have explosive sales every month? We put a lot of effort into the original design to sell a little? ”
Is it really "metaphysics" to the explosion of the model?
Today, let's take a look at the hot style of clothing e-commerce.From demand forecasting, market verification, and other key steps, summed up a set of effective formula for creating explosive models, which is mainly divided into 4 steps:
AI big data predicts demand
according toData trends of online e-commerce (e.g., Taobao, Tmall, Douyin, Dewu, etc.) and social media (e.g., Xiaohongshu, Douyin, etc.)., summarize the consumption preferences of consumers in the mainstream market, and understand what are the best-selling clothing at the moment, as a reference for new product development.
Part 1: Analyze e-commerce sales data
Step 1: Analyze the best-selling e-commerce platform
Product analysis of Taobao, Tmall, Douyin and other e-commerce platforms sales or sales TOP100 best-selling products,From it, the commonality of style, category and price band is extractedFor example, in the TOP100 sales of Tmall women's clothing in March, T-shirts accounted for 26%, and products in the price range of 50-100 yuan accounted for 37%.
Source: Zhiyi-Leaderboard
With the help of the [Zhiyi/Douyi-Ranking] function, you can easily find the product ranking in demand by selecting the time, market, and sales volume, and support the export of EXCEL sheets as a data source for in-depth analysis, mining the corresponding data such as the price band, shelf time, first-day sales, and article number of the store.
Step 2: Analyze user feedback on best-selling products
Focus on the analysis of the target best-selling productsNegative review keywordsAs the key optimization direction of their own new product development, such as fading, poor packaging, etc.
Source: Zhiyi-Product Details
With the help of the word-of-mouth analysis of [Zhiyi/Douyin-Product Details], you can see the evaluation keywords and buyer shows of the corresponding products.
Source: Zhiyi-Consumers said
Or directly through [Industry Insight-Evaluation Analysis] and [Consumer Say-Positive and Negative Voice].Extract the evaluation keywords of a certain category/brand in the Tmall and Taobao marketsto gain a comprehensive understanding of consumer pain points.
Step 3: Analyze the data of competitors
Analyze the recent new and hot-selling products of competing stores,Focus on analyzing the silhouettes, design details, colors and other elements that appear frequently on the other side, such as check patterns, panelled fur collars, etc.
Source: Zhiyi - store details
In [Zhiyi/Douyin-Store Analysis], you can gain insight into the recent operation dynamics of the other party by monitoring the store, covering sales performance, new status, hot-selling product data, etc., and obtain the recent consumption preferences of similar customer groups.
Part 2: Mining Social Media Trend Data
In recent years, the out-of-the-circle dopamine, Maillard, mint mambo, Bath style and other outfit trends have all become popular from social media, thereforeClothing e-commerce and fast fashion practitioners need to focus on monitoring the new fashion trends on social media platforms such as Xiaohongshu, Douyin, and Weibo, such as dressing topics with soaring interactions, fashion bloggers, etc.
Generally speaking, fashion trends on social media will appear 3-5 weeks earlier than e-commerce platforms, mainly because the most fashion-savvy influencers always like to share their outfits on social platforms for the first time. By analyzing these contents, we can:You can predict upcoming fashion trends about a month in advance。
Source: Zhi Xiaohong - Trend Insights
In [Zhixiaohong-Trend Insight-Hot Words List] and [Shake Clothes-Leaderboard-Topic List], yesFilter by time for fashion topics related to the recent month-on-month spike in dataand click to view the associated video/note to identify the design elements that are trending upwards as a powerful data support for new product development.
Source: Zhiqian - Trend Report
There is also [Trend Report - Trend]Dozens of reports summarizing the latest trends are available every weekWith a large number of data and shows, domestic and foreign brand style pictures as cases, in-depth interpretation of the most cutting-edge consumer preference changes and market trends, to help brands and designers fully grasp the trend picture at home and abroad.
Quickly validate the market
In order to ensure sales and control the cost of trial and error, many clothing e-commerce companies will repeatedly verify market acceptance when developing new models, so as to avoid a misjudged popular element from entering the production process, which is likely to lead to a million-level inventory backlog and become an "out-of-season model" that cannot be sold.
Step 1: Analyze the best-selling products on the marketplace
When many clothing e-commerce companies develop new models, they usually follow the best-selling versions that have been verified in the market, and then integrate the popular elements of the season for iterative improvement. A design director once revealed that nearly ninety percent of their company's new models are so remodeled.
To summarize its specific approach, it is actually a modular design and development method.Based on the version that has been verified by its own brand, it is popular with new elements, such as the 24-year-old coat fit with a spliced collar element, which not only greatly improves the efficiency of the individual design, but also reduces the risk of reheating and subjective experience errors.
Source: Zhiqian - Data Analysis
Regarding the skills of mining the current popular elements of the market, with the help of the [Knowledge-Data Analysis] function, you canVertically focus on the high-heat market performance of a certain style categoryFor example, the recent data of "Korean casual" style coats in Xiaohongshu, click [View Style] to directly browse the details of relevant wearing notes, which can be used as an important reference to improve the best-selling models in your store.
Step 2: AI intelligently generates an improved model
From the upper body effect to the specific upper body effect of the modified style, you can use AI digital tools.
Source: FD
For example, the [clothing remodeling] function of Zhiyi FD products can directly generate the effect of virtual sample clothes on the upper body through local remodeling, style innovation, style fusion, fabric upper body, clothing color change, etc., greatly reducing the time of physical proofing.
Part 2: Market performance of similar models
If you need to do further market research on the improved style, the next step is okayThrough [Smart Image Search], one-click mining of similar models on e-commerce platforms such as Taobao, Douyin, and DewuThrough its product links and market data, it evaluates whether the improved similar models really have market space, and finally buys or communicates with the supply chain.
Source: Zhiyi-Smart Search
Part 3: Small single quick reflex test
First develop and produce 100-300 pieces in small batches,Launched Tmall/Douyin and other e-commerce channels to test market feedback in small batches, focusing on click-through rate and conversion rate, as well as color and SKU performance, so as to quickly determine the main color and main promotion according to the add-on data.
Source: Zhiyi-Product Details
With the help of [Zhiyi - Product Detail Page - SKU Analysis], you can also monitor and gain insight into the SKU trends of similar models in the market in advance, and then combine with your own data feedback to comprehensively make replenishment needs.
Part 4: Intelligent production
Zhiyi will automatically recommend associated fabrics based on the prediction data of popular models, andSeamless docking with reliable fabric suppliers to achieve a closed loop from demand forecasting→ raw material optimization → flexible productionshorten the raw material procurement cycle by 30% to ensure the flexible reserve of explosive production capacity.
Source: Zhiyi-Fabric Center
For example, the AI system captures the surge in demand for floral dresses, and will automatically screen 5 reserve floral fabric suppliers to compare the quotation inventory/delivery date, so as to realize the real-time linkage of "demand-production-supply".
Social media promotion and marketing
Part 1: Dig up popular works/notes
There are two main purposes for mining popular works on social media.The first is to serve as a reference for the promotion and marketing content of their own clothing, and the second is to select the talent with a high degree of fit as the reserve of cooperative talents, as a waiting list for follow-up cooperation。
Source: Zhi Xiaohong-Note Library
In [Shake Yi-Works Library] or [Zhi Xiaohong-Note Library], you can filter popular works/notes that meet your needs by various dimensions such as grass category, interactive data, and delivery effect, so as to disassemble the content logical framework and obtain some optimization strategies for social media marketing content, so as to make the promotion efficiency twice as effective with half the effort.
Part 2: Analysis & Placement of Influencer Bloggers
In terms of regular delivery of talents, most clothing e-commerce companies will basically cooperate with a group of talents before every new or official event, mainly amateur talents, combined with some middle and waist, if the budget is sufficient, you can also find a few head talents with high tonality. For example, the scene-based dressing effect of cooperation with mid-waist experts, such as the OOTD dressing challenge of amateur KOC cooperation, etc.
Source: Zhi Xiaohong-Talent Library
In [Douyin/Zhi Xiaohong-Talent Library] canSearch for the target audience on demand and export the invitation cooperation in batches。 At the same time, check the promotion conversion effect based on their recent grass planting works/notes, or monitor the performance of competitors' influencers.
The formula for creating explosive styles in clothing e-commerce
Part 1: Learn the hits
To create a hit, you must first know what elements can attract customers, soIt is necessary to analyze the dimensional analysis of the target popular clothing, and learn the price band distribution and category distribution of new products of competitors: Learn the design elements, silhouettes, etc. of the top 100 in the market/sales.
Part 2: Create a hit
Fast fashion and fast reverse mode, requiring a fast pace of design, and the emphasis is on the continuation of the explosive version, we can divide the "best-selling extension" into internal extension and external extension.
Step 1: Improve and iterate your best-selling models
The main idea is:Fine-tune according to the popular models that have been verified by the market：
Step 2: Optimize your competitors' bestsellers
The main idea is:Based on the best-selling models of competing products in the market or target competitors, the core design points are refined, the key to consumer negative reviews is optimized, and then extended development is carried out。 If a big brand puff sleeve is on fire, it can be made into a new design such as a short/off-the-shoulder model.
To summarize the 4 major steps discussed above, in fact, the key to the explosion of clothing e-commerce isThe "fast" to grasp the trend 7 days earlier than the opponent, the "accuracy" to verify the product with real data, and the "ruthlessness" of mass production as soon as the order is explodedIn order to screen out 1% of popular models through weekly/monthly high-frequency new tests, and then reduce costs and maximize profits through large-scale production.
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