How it works

How does our Dynamic Pricing tool work?

Our customizable Pricing Platform walks you through a simple 3 step process and gives you different options to build and implement your Pricing Strategies.

We set up for your business taking into account your constraints and level of pricing expertise and maturity.

Build a secure Data Lake

STEP

01

Our data model is fed with different internal and external data sets with the highest possible level of granularity. We consolidate all relevant data sources to be able to optimise your P&L:

Transactional Data

Product catalogue tree (SKU attributes), orders, basket components, shipping cost, revenue, marketing costs… broken down by many dimensions (Point of sale, device, marketing channel etc…).

Analytics Data

Coming from various sources such as Google Analytics (via API or Cloud ) or our own SDK.

Competitive data

We consume your feeds or those coming from our third party partners (WorkIt, Netrivals, Price2Spy) to be able to react to any market changes. 

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STEP

02

Launch the Learning Phase

We group products in different Portfolios and train our AI to compute and segment elasticity

Build Product Portfolios

We cluster your product catalogue into different portfolios based on your business knowledge and targets.

Launch the learning phase

We test 6 different price points (Min, Max, Avg, …)  for each products of each portfolio to be able to compute elasticity and have a starting point for optimisation.

Define the business targets

Using our simulator you can build scenarios and assign a Business Goal and its related constraints to each Portfolio. Eg: “I want to increase my revenue by 5% without decreasing my revenue margin by more than 2%”.

Pricing Optimisation at scale

At the end of the learning phase, the solution starts pushing regular price recommendations optimising towards the set business target.

STEP

03

Solution provides you recommendations for implementation

In using our price management software you can visualize & understand each price recommendation we make. You can then validate the pricing structure manually or automatically and export them in the format needed for implementation in your system.

Iteration & Learning Loop

Once the statistical significance is reached, our machine learning algorithms measure the outcome of the price change, understanding the dynamic environment, and computes an adjusted price recommendation for the next iteration.

Measure & Visualise Value creation

Our solution provides you with a clear, unbiased way to measure your performance vs the set target and the rest of your product catalogue.

Make Smarter Pricing Decisions

Book a demo of our dynamic pricing solution