Noogata的动态

With holiday e-commerce sales set to hit $221.8 billion, the stakes have never been higher. Supply chain disruptions, inventory challenges, and rising expectations are testing businesses of all sizes—and AI is proving to be a game-changer. From real-time inventory management to scenario planning and supplier optimization, AI doesn’t just help navigate disruptions—it levels the playing field for SMBs, empowering them to compete with the giants. Dive in: https://lnkd.in/eDEpAvSq #Ecommerce #AI #SupplyChain #HolidaySeason #SMBs #Innovation #DigitalTransformation #CustomerExperience

?????????????????? ??-???????????????? ?????????????? ???????? ??????? In e-commerce, smart pricing can be the game-changer. Brands like Amazon use dynamic pricing to stay competitive, adjusting prices in real-time based on demand, competition, and trends. Uber’s surge pricing boosts availability when it’s needed most, setting an example of flexibility. ? At Prescience, we helped a major e-commerce client increase revenue by 8% and profit by 1.5% in just six months using AI-driven pricing optimization. With insights powered by advanced analytics, their pricing became smarter, faster, and more competitive. Ready to see how data can transform your strategy, explore our blog here - https://lnkd.in/dZ-ZtaRb ? #ecommerce #AI #PricingStrategy #Prescience #EcommerceGrowth #DynamicPricing #ArtificialIntelligence #DataDriven #TechInnovation #Analytics #RetailTech #DigitalTransformation #RevenueGrowth #SmartPricing #BusinessIntelligence #EcommerceStrategy

Small retailers vs. e-commerce giants—who wins? The answer: those who adapt. Canadian retailers have a unique edge to compete in the space! From omni-channel strategies to leveraging AI and niche markets, discover how small businesses can thrive in the competitive e-commerce landscape. ?? Ready to stand out? Read the full article to learn more. #SmallBusinessCanada #EcommerceStrategy #RetailSuccess #CanadianEntrepreneurs

Retailers and DTC brands are sitting on the biggest opportunity to leverage AI for competitor insights and recommendations to achieve better pricing, assortments, and planning. Here's a summary of the key reasons to invest in this tech movement now: https://lnkd.in/eTJnC7B5 #AIforRetail #CompetitiveIntelligence #PricingIntelligence #GainMarketShare #RetailTech

Solving the E-commerce Long-tail Inventory Puzzle Recently, I've encountered a very interesting problem. This fascinating problem is about creating a model that meets the following conditions: 1. Predict sales of long-tail products in e-commerce (products that sell sporadically, a few at a time) 2. Minimize stock-outs (when demand exceeds inventory and products can no longer be sold) based on these predictions 3. The operations team should be able to tune the model What makes this truly interesting is that the sales of most long-tail products are literally '0'. If the goal was simply to 'predict sales accurately', we could just set all future sales to 0. However, if we create a model like this, while the difference between predicted and actual sales would be minimized, all products would end up in a 'stock-out' state when deciding how much to store in the warehouse. In other words, the accuracy of the prediction model becomes practically meaningless. How interesting is this problem! (Can you hear the sound of my head exploding?) To make matters more complex, most of the time series prediction models we know (e.g., ARIMA) assume that products sell at least a little every day and have sales records for at least a few months (ideally more than 3 years). Therefore, when using these models, the predictions aren't very accurate. Then some people might say: 'AI is hot these days, can't we predict using AI or machine learning?' Of course we can, but to utilize machine learning and AI, we need to satisfy the following additional requirements: 1. There's a lot~~~~ of clean and diverse data. 2. The machine learning algorithm and AI don't need to explain 'why they predicted sales that way'. However, in reality, clean and diverse data often doesn't exist, or even if it does, it really requires more than a quarter of data cleaning and design. Moreover, for operational goals and efficiency, we often need to explain and tune the logic, making it difficult to utilize machine learning. So, coming back to our three constraints (1) Improving prediction accuracy. (2) Minimizing stock-outs. (3) Allowing fine-tuning for operational purposes. How should we create a prediction model to achieve these? Let's go through the following 5 steps! Step 1: ...... https://lnkd.in/gkcnarrr

Amazon's AI Revolution: Reshaping E-commerce and Retail Amazon's strategic integration of AI has transformed the e-commerce landscape, setting new standards for personalization and efficiency. From the groundbreaking A10 algorithm to AI-driven logistics, Amazon is leading the way in retail innovation. Key insights: ? 63% of shoppers expect personalization as a basic service ? Amazon's AI-powered recommendations drive 35% of revenue ? AI-driven advertising platforms capture 76% of e-commerce ad spending ? Predictive analytics optimize inventory management and pricing strategies As we look to the future of retail, it's clear that AI will play a crucial role in enhancing customer experiences and driving business growth. How is your organization leveraging AI to stay competitive in the digital marketplace? Read the full article to explore Amazon's AI revolution and its impact on the retail industry: https://lnkd.in/eZSweSYs #AmazonAI #Ecommerce #RetailInnovation #AIinRetail

AI-based pricing algorithm increased an e-commerce store's revenue by 34.5% last month. No marketing tricks, no new products - just smarter pricing. The data speaks clearly - businesses see this level of revenue increase when they use AI to set their prices. This market is growing fast and experts predict it will hit $16.8B by 2027. The shift makes sense. Most shoppers (70%) are fine with prices that change, as long as they're fair and clear about it. Smart companies now use AI to look at what customers want, what competitors charge, and how much people buy. This helps them pick prices that work well for both the business and its customers. I've watched many retailers struggle with pricing before finding the right balance. The best approach combines careful data analysis with a deep understanding of what customers value. When companies get this right, they keep their customers happy while staying competitive. It's not just about charging more - it's about finding the right price at the right time. Good pricing helps businesses grow while giving customers fair deals. The companies that understand this are the ones pulling ahead in today's market. Share your experience: How has dynamic pricing affected your business decisions?

One of the most compelling applications of AI-powered Dynamic Pricing like Reactev is its seamless integration with ESL (Electronic Shelf Labels) technology. While it might seem straightforward, the synergy between these two innovations is not to be underestimated. ???? Imagine having both a price intelligence solution and an AI-powered dynamic pricing platform alongside ESL tech in your stores. This combination allows you to update prices in your brick-and-mortar locations as frequently as you desire. ???? Picture this workflow: From 2 am to 8 am, your price intelligence and monitoring solution gathers data on competitor prices. ???? At 9 am, your AI analyzes this data and suggests price adjustments to maintain your market position. ???? By 9:30 am, these prices are pushed to your ERP system, updating all ESLs in your store. ???? As the doors open at 10:00, you're confident that your store offers the best deals in town. ???? Now, consider the marketing opportunities: "Your company leverages AI to ensure it's customers get the best deals." Spotlighting a positive (non dystopian) use of AI in your business to show customers you are innovating with their best interests in mind. You can even craft marketing campaigns around this technology to manage demand spikes, such as: "Thanks to AI, every Tuesday from 12:00 - 15:00, we guarantee the best prices in town on XXXXX segment or product." The possibilities are endless. ???? #RetailTech #AIinRetail #MarketingStrategy #CustomerExperience #DataDrivenDecisions

The main advantage of ESL (Electronic Shelf Labels) is that they allow you to adapt prices to market needs quickly and easily. ??This is possible if you use an AI-Powered Pricing Tool, such as Reactev, that find the most appropriate prices for the different products in your assortment. #dynamicpricing #AI

Discover how AI is revolutionizing eCommerce, for better or worse, and how brands can protect themselves with a MAP policy.