The easiest way to steer prices and increase profits
For the first step, we gather all the data relevant for your price optimization. Internal data – such as historical transactions and product attributes – is used in conjunction with relevant external data, such as weather, seasonal factors and competitor prices. Using this data, our team builds a predictive pricing model which is tailored for our customers’ business, managing the process from start to finish.
The foundation of our price optimizations is our forecasting technology. Our cloud-based software uses cutting-edge machine learning models to identify drivers of demand and price elasticity. Based on these drivers, it accurately forecasts profit and revenue for all relevant price points. Our extensive experience from ecommerce and the fashion industry enables us to effectively manage seasonal products, frequently changing assortments, and low selling products.
With our next generation pricing software, you can amplify your price strategy with the power of machine learning algorithms. The optimization is customizable, allowing users to integrate rules such as maximum discount amounts, competitor price matching, and much more. You can choose the granularity you need and create tailored price rules on the brand, category, or even individual product level.
To optimize your pricing using our software, simply set your revenue or profit target. Within a matter of minutes, our software calculates the prices that will maximize your business goals. Using our platform, you can easily adjust for different business scenarios to assess the impact of different targets. Price setting has never been simpler or more intuitive.
7Learnings’ innovative technology doesn’t stop at price optimization – it can also optimize coupons and SEA spending for you. This allows for powerful cross-marketing optimization capabilities. These tools give you the ability to gauge what strategy supports the most growth and profitability: by increasing or reducing your discounts, coupon rates, and SEA spending.