We delve into the strategies and techniques companies can employ to master long-tail pricing using advanced predictive pricing solutions.

Understanding the long-tail

The long-tail theory emerged at the beginning of the new millennium. With the possibilities of global e-commerce, the classic ABC model of product evaluation became obsolete. The globalized economy is lowering manufacturing costs and new distribution models and production on demand are reducing storage costs. The limited shelf space of brick and mortar stores is no longer a determining factor. 

Niche products can be sold successfully because online prospects can be targeted worldwide via search engines, advertising and social media. The long tail is now a potential goldmine for retailers. Typical examples of retailers with long-tail products are online fashion retailers, retailers of spare parts and electronics retailers. Kevin Kelly explains how to build an entire successful business by selling niche products in his bestseller “1000 true fans“. 

One challenge in the long-tail segment, however, lies in pricing: it is not cost-effective to set individual prices for large product ranges with thousands of niche products. This is why many retailers resort to cost-plus pricing – and thus give away massive amounts of profits. Also, it’s difficult to keep track of stock levels in such large numbers and to manage them effectively via price adjustments. Predictive pricing offers an intelligent solution to both problems. 

How 7Learnings optimizes for long-tail and niche product pricing

With predictive pricing, retailers now have a powerful tool at their fingertips to achieve price optimization for their niche products. Predictive pricing, as we’ve created at 7Learnings, uses AI algorithms that can analyze data of thousands of niche products in seconds, historical data as well as market trends, and forecast demand for long-tail items with accuracy.  

As a retailer you no longer need to identify relevant factors for price elasticity like season, competitor prices, return rates and stock manually which isn’t feasible in large assortments anyway. Instead you create a tailored pricing strategy for your long-tail products with just a few clicks in the 7Learnings solution. 

You reliably avoid overpricing or underpricing as our solution adjusts prices dynamically according to your business goals. Do you want to hit a specific revenue goal? Do you want to clear out stock or increase your margin? Once you set your goal, the AI algorithms steer your prices on autopilot in a way that you reach your goals faster with minimal effort.

There are lots of price optimization tools but one main advantage of 7Learnings is you don’t need lots of data to use it effectively. As our data models learn across product attributes, they work even if you only have scarce data. 

Optimizing long-tail pricing for increased profits

Artificial intelligence changed the game of price optimization for long-tail products. AI-based algorithms are much more powerful than traditional price optimization tools that use defined rules to adjust prices. AI is able to constantly learn from real business results and optimize its support. There are five ways in particular where AI-powered predictive pricing is superior to the old ways of price optimization – not only for nice product pricing. 

1. Granular analysis

AI algorithms can analyze historical sales data and customer behavior at a much more granular level than manual analysis or traditional tools allow. Retailers gain valuable insights into the demand for individual long-tail products and can align their business strategy accordingly.

2. Demand forecasting

In the pre-AI era, forecasting demand was only possible in a very imprecise way, especially for products sold in complex market dynamics. With AI, retailers can steer their prices for niche products on autopilot to reach maximum profit and maintain optimal stock levels.

3. Dynamic pricing

AI can continuously monitor market conditions, competitor prices, and customer preferences to dynamically adjust prices for long-tail products in near real-time. Traditional dynamic pricing tools linked price adjustments to just a handful of predefined rules and weren’t able to react as fast and as effective. 

4. Profit maximization

By leveraging demand elasticity and other factors to optimize prices for long-tail products, AI-powered predictive pricing solutions enable companies to maximize profits across their entire product range. While traditional price optimization helped lower manual pricing efforts and increased profits, only AI-based tools unlock the full profit potential of bestselling as well as long-tail products.

5. Automation & scalability

Traditional rule-based pricing tools still meant lots of manual effort, for example when new products were added to the assortment. With AI-driven price optimization, there is no need for tedious configuration. The algorithm will figure out what to do based on a given goal. Especially in long-tail price optimization, the automated analysis done by AI makes a huge difference in reaching KPIs.

Enhance your niche & long-tail pricing

Mastering long-tail and niche product pricing is essential for retailers to unlock untapped profit potential. Traditional pricing methods like cost-plus pricing or rule-based pricing are limited in their effect: They take few demand factors into account and cannot adjust prices as dynamically as our current markets require. 

AI-powered predictive pricing solutions, such as 7Learnings, revolutionize niche product pricing by analyzing data, forecasting demand, and adjusting prices in real-time. AI solutions eliminate manual effort and enable retailers to create tailored pricing that maximizes profits across the entire product portfolio.

The future of long-tail and niche product pricing lies in the continued development and adoption of advanced AI tools, fully realizing the profit potential of diverse product offerings and enhancing business sustainability.