"How many will we sell tomorrow?" This question is a daily concern for every e-commerce business owner every night. If inventory is insufficient, sales opportunities are missed, and if too much is prepared, warehouse costs and disposal losses occur. After COVID-19, as market volatility has increased dramatically, the limitations of traditional prediction methods relying on 'intuition' have become clear.
Deepflow presents an innovative solution of AI-based sales volume prediction in this complex market environment. Going beyond simple statistical analysis, it supports companies in making accurate demand forecasting and strategic decisions through customized prediction models that deeply understand the characteristics of the Korean e-commerce market.
Today's online shoppers demand accurate delivery date guidance and promise fulfillment as basic requirements. Particularly, MZ generation customers prefer transparent disclosure of all information, and providing this level of service requires sophisticated sales volume prediction.
Since COVID-19, situations like unexpected demand surges for home training equipment, camping goods, and home cafe-related products have been repeating. As consumption patterns have diversified, it has become difficult to identify these complex factors with existing simple prediction methods.
AI can identify subtle patterns that humans easily miss. It can discover that the associated purchases of ramen and ready-to-eat rice are connected to social changes like the increase in single-person households and overtime work culture, and analyze the impact of weather changes on specific product categories considering not only temperature but also humidity and fine dust concentration.
Deepflow has developed proprietary models that intensively learned sales data and other information. It's a model that has learned all Korean characteristics including Korea's unique gift culture (Teacher's Day, Parents' Day, White Day, etc.), surge in health food sales before Chuseok, purchase patterns after payday, and rapid changes in K-beauty and K-food trends.
Through this, it achieves high prediction accuracy of over 95%, which is Deepflow's differentiated competitiveness that overseas general-purpose solutions find difficult to provide.
Deepflow's AI model is a dynamic system that continuously updates prediction models by analyzing new sales data, market changes, and external environment variables in real-time every day. It can respond quickly to sudden trend changes or unexpected market situations, differentiating it from static systems that depend only on past data.
Deepflow simultaneously analyzes dozens of variables that affect sales volume. It maximizes prediction accuracy by comprehensively considering weather, events, competitor promotions, social trends, and macroeconomic indicators. For example, it's possible to analyze in real-time and reflect in predictions the sales surge patterns of products that became hot topics on SNS.
It operates optimized prediction models for each category including fashion, beauty, electronics, and food. It provides customized predictions reflecting characteristics where the beauty category is greatly influenced by seasonal trends and influencers, while the electronics category has economic indicators and seasonality as more important variables.
Global e-commerce companies are already utilizing AI-based prediction systems as core competitiveness. Amazon's predictive shipping and Alibaba's smart logistics system are representative examples.
In Korea, Naver's delivery guarantee service achieving 95% accuracy based on AI prediction and a 4.5-fold increase in participants in 6 months shows that the effectiveness of AI sales volume prediction has been verified in the market. Coupang is also continuously investing in AI prediction systems for stable operation of Rocket Delivery.
Looking at these market trends, AI sales volume prediction is no longer an 'innovative attempt' but has become an 'essential element for survival.'
Deepflow customers are experiencing an average 20-30% reduction in inventory holding costs. Through accurate sales volume prediction, problems like warehouse costs from excess inventory, disposal losses, and decreased capital turnover rates can be solved.
Particularly for seasonal products or trend-sensitive fashion and beauty products, the cost of inventory disposal after season end can be significantly reduced, leading to substantial profitability improvement. One fashion e-commerce customer achieved a 60% reduction in end-of-season inventory disposal costs.
Accurate sales volume prediction directly leads to stockout rate reduction. Companies that implemented Deepflow solutions are achieving results of reducing average stockout rates by 15-25%. Preventing sales opportunity losses due to stockouts brings direct sales increase effects.
One household goods specialized mall accurately predicted the surge in hygiene product demand after COVID-19, maintaining stable supply even when competitors faced stockout situations, achieving a 30% increase in market share for that category.
Inventory optimization and stockout rate reduction ultimately lead to customer satisfaction improvement. Customer companies using Deepflow solutions report an average 20-30% improvement in customer repurchase rates and a 15-20 point increase in Net Promoter Score (NPS).
With AI sales volume prediction system implementation, over 80% of ordering tasks previously performed manually by purchasing managers are automated. Managers can focus on exception management and strategic tasks, significantly improving work efficiency and satisfaction.
The reason many companies fail in AI implementation is data quality problems. Deepflow enables AI to automatically cleanse and supplement even incomplete data through automatic data cleansing, data standardization engines, and real-time quality monitoring.
To solve the 'cold start' problem of new products or products with short sales histories, Deepflow developed similar product learning methods through product attribute-based similarity analysis and market trend reflection. Usually, prediction accuracy similar to existing products is reached within 2-3 weeks.
To prevent 'model drift' where prediction accuracy decreases over time, real-time performance monitoring and automatic retraining systems are built. When prediction accuracy falls below set thresholds, retraining automatically begins, allowing customer companies to always use the latest performance AI models without separate technical management.
E-commerce sales volume is affected by numerous variables including promotions, seasonality, competitor trends, and consumer psychology. Deepflow comprehensively analyzes these complex variables through real-time integration with various external data sources including the Korea Meteorological Administration, Bank of Korea, Naver Trends, and Google Trends.
Deepflow analyzes each company's industry, scale, and current system environment to establish optimized implementation plans. Through a 4-stage methodology of preliminary analysis → pilot project → gradual expansion → enterprise-wide deployment, resistance within organizations is minimized while quick results can be confirmed.
Standard APIs for major ERP systems like SAP, Oracle, Douzone, and Youngrim, as well as e-commerce platforms like Naver Smart Store and Coupang Partners are provided, enabling real-time data synchronization and automatic reflection of prediction results.
Customized education is conducted for each role including management, IT personnel, and purchasing personnel, and dedicated consultants are assigned to each customer company to continuously present quarterly performance reviews and improvement plans.
Dashboards that can monitor key indicators like prediction accuracy, inventory turnover, stockout rates, and ROI in real-time are provided, and model performance is checked and optimization work is performed quarterly.
AI-based sales volume prediction has become essential, not optional, in the e-commerce market. Deepflow supports customer companies in securing competitive advantages through AI solutions specialized for the Korean market.
20-30% inventory cost reduction through accurate sales volume prediction, 15-25% stockout rate reduction, and customer satisfaction improvement and sales increase through these. All of this is possible through Deepflow's differentiated technology and systematic support services.
We can no longer yield opportunities to competitors. Lead the future of AI-based e-commerce sales volume prediction with Deepflow. Please consult with Deepflow's professional consultants right now to check your company's customized sales volume prediction solution.
.svg)
