Best Practices for Pricing in E-commerce Retail

I've seen countless companies relying on outdated models or gut instincts for price changes. That often leads to tactical, knee-jerk pricing, missed profits, or constant battles to justify pricing & promotional plans to supply chain partners. I just recorded a quick video explaining exactly how we combine four different approaches to model elasticity accurately: 1. Double Machine Learning (DML) - Delivers a robust causal estimate by predicting sales and price from confounders, then regressing the residuals. - We typically build one DML model per SKU. In our experience, this often reflects real-world behavior best. 2. Log-Log regression models - It is simple and interpretable - perfect if you have lots of historical data, a high volume of transactions, or price variation. - The log price coefficient directly translates to elasticity. It is quick to implement, though it often oversimplifies and is not a good method for B2B. 3. ElasticNet - A regularized linear model balancing Lasso and Ridge methods. - If you have many variables, such as our promos, competitor promos, distribution, comp distribution, etc., it helps prevent overfitting. 4. Random Forest - Handles non-linearities pretty well without having to do complex data engineering. - We use price perturbation, simulating different price points to see how predicted demand changes, thus estimating implied elasticities. In the video, I also share how we compare the four methods, track metrics like RMSE or MAPE, and deliver scenario-based recommendations about price, promotions, and competitive moves, helping you go from reactive to proactive pricing. The real payoff is that you can: 1. Proactively manage pricing: estimate the impact of competitor actions and optimize your strategy. 2. Maximize promotional ROI: estimate what truly drives incremental volume vs. what's wasted spend. 3. Earn insights-backed credibility: support your pricing with robust elasticity metrics that show retailers how you got to your recommendations. I'd love to hear your thoughts. If you're ready to take a deeper look at these elasticity models (complete with a whitepaper, sample code, and practical examples), check out the comment section for links and more details!

Competing on low price? That’s a race to the bottom. Instead, attract customers with a 𝑝𝑠𝑦𝑐ℎ𝑜𝑙𝑜𝑔𝑖𝑐𝑎𝑙 𝑝𝑟𝑖𝑐𝑒. Why? Let’s look at the reality: Amazon is a fiercely competitive marketplace. If you think you can win by simply having the lowest price, here’s what will happen: 1) You’ll crush your profit margins. 2) The customers you attract with low prices will jump ship as soon as they find a lower one. And business isn’t a joke. Every strategy needs to drive profitability. If you’re acquiring customers but losing money, what’s the point? So, how do you create a pricing strategy that pulls in customers while protecting your bottom line? The answer lies in using pricing tactics strategically: ➤ Dynamic Pricing Adjust prices based on demand, competition, and inventory levels in real-time. (Pro tip: Use tools that track real-time ASIN data. Here’s one to try: https://t2m.io/ZC5KWuye) ➤ Psychological Pricing Prices like $19.99 instead of $20 trigger the perception of getting a deal. ➤ Competitive Pricing Benchmark against competitors to stay relevant without slashing your profit margins. ➤ Penetration Pricing Start low to capture market share, then adjust as your brand gains traction. ➤ Value-Based Pricing Set prices based on the perceived value to the customer—not just the cost. ➤ Keystone Pricing Double your wholesale cost to set a standard retail price. ➤ Bundle Pricing Combine multiple products at a discounted rate to increase perceived value and move inventory faster. ➤ Discount Pricing Offer temporary price reductions to clear stock or boost sales. ➤ Loss Leader Pricing Price certain products at a loss to attract customers who will make additional, profitable purchases. ➤ Skimming Pricing Begin with a high price and gradually lower it as demand shifts. ➤ Premium Pricing Maintain higher prices to signal exclusivity and premium quality. ➤ Cost-Plus Pricing Add a fixed markup to the cost of goods to ensure a stable profit margin. The key? Leverage these tactics strategically. Every pricing strategy should align with your business goals and attract the right kind of customers—the profitable ones. Let me know if there’s a strategy you want to dig into further! P.S. We’re launching an exclusive program for established brands ready to dominate Q4 with data-driven strategies. Message me ‘QUALIFY’ to see if you’re a fit. As trusted partners of Alibaba and Amazon, we’ve helped sellers and agencies generate over $200 million in revenue. Are you next?

If you’re not tracking real-time pricing signals, you’re making blind decisions in a volatile market. Let me explain. 👇 Tariffs, supply chain shifts, and aggressive discounting are creating pricing chaos across durable goods. The brands that win won’t be the ones reacting last…  They’ll be the ones anticipating where the market is moving before their competitors do. With Competitive Pricing Intelligence, you can: ✔ Monitor same-day price shifts in key product categories to get ahead of sudden increases. ✔ Track competitor promotions to see who’s absorbing costs vs. protecting margins. ✔ Identify SKU-level price discrepancies across retailers to optimize your pricing strategy. ✔ Adjust regional pricing and inventory placement to maximize profitability. ✔ Understand consumer price elasticity to know how much room you really have to adjust. If your competitors are adjusting prices and you don’t know why, you’re already behind. Read the full report to see how leading brands are staying ahead: https://lnkd.in/eStrM9NH #PricingStrategy #CompetitiveIntelligence #MarketData #RetailAI