The Pricely system calculates price recommendations in accordance with the pre-defined periodicity. Moreover, it provides additional recommendations in response to changes, eg. changes in competitors’ pricesor the product elasticity
To calculate price recommendations we use a dynamic model based on Machine Learning. It ensures adaptation to the changing conditions of the store environment and changes in consumer habits.
Our customers receive first recommendations even in one month. Software integration takes up to two months. We’re flexible in adding new features and in consulting.
Advanced reporting shows how historical pricing strategies of retailers affected results in the past and how new recommended prices can change the results in the nearest future. Reporting is based on Microsoft Power BI system.
We created Pricely with particular regard to simplicity of usage, so that every user, after a short training course, could run a simulation of new prices and implement them without going into details of strategies applied.
In one scenario you can manage the whole range of products in the stores or you can configure many scenarios, separately for each store or product category.
Price optimization enables the most effective profit margin increase in retail chain stores.
What do we get from the 1% change?
Change of operational costs by 1%
generates up to 4% increase in profit margin value
Change in the cost of products by 1%
generates up to 6% increase in profit margin value.
Change in product prices by 1%
generates up to 11% increase in profit margin value.
A chain with revenue 100m PLN* can generate
additional 2m PLN profit
*Result for average chain
We have been operating in the retail sector for many years and we have observed dynamic changes taking place on the market. Retailers struggle with problems related to constantly growing competition (both brick and mortar and online stores), and as a result profitability of the traditional stores drops. There are big disproportions between e-commerce and traditional stores with in the range of available price management tools.
Expert in pricing strategy, price management and promotion policy with a track record of 40 projects including industries such as FMCG, retail, pharma and e-commerce.
18 years’ experience in retail and market research. 10 years’ as an advisoer and category manage ment manager in Carrefour and Casino Group (Poland and France); specializes in price market research; built a system monitoring prices of competitors.
IT architect, developer and project manager with more than 15 years of experience in designing and implementing IT solutions for companies in the commercial, financial and insurance industries.
Over 20 years’ experience in designing and implementing IT solutions in retail trade, banking and the public sector in CEE; among others, worked for Wincor Nixdorf, Deutsche Telekom, holds PhD in technical sciences.
Manages VC funds from Rubicon Partners group, responsible for implementation and supervision of start-up investments. Member of Supervisory Boards and CFO in portfolio companies. Gained professional experience in seed/VC funds and consultancies.
Entrepreneur experienced in running start-up projects in the area of new technologies based on innovative combining of loT, SaaS solutions and unconventional business models. Worked on advisory projects for companies investing in technological companies in their early stages of development.
Data base analyst, Data Mining and Machine Learning expert. Responsible for adaptation of algorithms computing new prices (regular, promotional and sale) and recommending assortment changes.
An expert in the field of optimization, computing strategies and use of artificial intelligence in recommendation systems, 13 years’ experience in Data Science.
17 years’ experience in development and management of IT products for retail chains and banks; specialized in security and efficiency issues in BigData processing.
As a production and retail company operating in dynamically changing market environment (strong competition, price variance, demand and supply seasonality), on multiple occasions we have used the expertise of the Team and the functionality of the Pricely software in the area of forecasting the price of the product offered by our company. We are very happy with the effects of our collaboration which enabled CTE to maximize economic benefits resulting from a given market situation while building long term satisfaction of our clients.
The solution developed by Pricely has drawn our attention mainly due to the fact that in the Polish retail market, dominated by big food chains, there has been no effective tool for small and medium retail chains enabling them to compete with the big players effectively. We are very glad of the Pricely system development dynamics, effects of the past implementations and translating the extensive knowledge of the Pricely Team into practical, working solution, generating real and tangible benefits to the clients.
In 45 minutes we will convince you that the implementation of Pricely in your network will open new opportunities for development.
Pricing Tags sp. z o.o.
ul.Gałczyńskiego 62/1
10-089 Olsztyn
NIP: 7393889421
KRS: 0000640138
REGON: 365543924
Contact:
biuro@pricingtags.pl
+48 665 558 555
Recruitment:
rekrutacja@pricingtags.pl
