Within a month of launching Dealavo AI Profit Optimization – price automation based on individual pricing rules – a client from the sanitary fittings industry gained an additional 82,380 PLN (EUR 18 470) of profit. Such an increase per year gives the result of almost PLN 1,000,000 of net profit. How was this achieved?
The primary goal was to optimize pricing policy based on competitor pricing and availability data, as well as to efficiently calculate established pricing rules. Before the introduction of price automation, they were changed manually.
The client created an appropriate list of products in XML format, containing the following data: EAN product name, purchase price, VAT rate, sale price, inventory. Although the data had to be gathered from more than one record system, the client quickly managed to submit the file.
The industry is very demanding when it comes to product search (numerous products and competitors) and matching (often unstructured names, mistakenly described products, e.g. EAN code of a single SKU for a multi-pack offer), which is why we decided to introduce two-step verification of matches not only by advanced algorithms, but also manually by the Quality Assurance team. Thanks to this, the customer could focus on creating pricing rules and analyzing their progress, instead of verifying data quality
Customer Success support
An equally important factor to achieve the client’s goal was the support of our Customer Success team. In the initial phase, our Customer Success spent with the client an average of 40 hours per month supporting them in creating pricing rules.
First pricing rules
The first product groups were selected. After over 30 days, we saw an average daily increase in conversion by 0.46pp (up to 1.43%), compared to the customer data from before using the tool and knowing competitive prices, when the conversion was at an average level of 0.9%.
In the following chart, data on profit (here shown in PLN), which was generated on automated product categories, are added.
AI Profit Optimization approach
These are the first successes, but the limited resources of the client to create and then compare the effectiveness of pricing rules for the entire range resulted in greater interest in artificial intelligence.
Initially, we recommended semi-automatic price management on selected product groups – the client had to accept/reject/complete a change suggested by the algorithms to provide further data to AI.
In a very short time we could observe measurable benefits:
Before launching the module (day 0), the average daily profit earned by the client was PLN 5,222, and the conversion 2.23%. After a month of running AI, the average daily profit is at PLN 7,968 and the conversion is 3.62%.
Dealavo together with the client generated an average 60% (1.39 p.p) increase in daily conversion, which translated into a 50% increase in profit in categories managed by AI.
Within a month of launching Dealavo AI Profit Optimization, the client gained PLN 82,380 (EUR 18 470). If you would like to find out more, you can read the full case study here.