0.5% revenue growth achieved by optimizing pricing strategy through AI
0.5% revenue growth achieved by optimizing pricing strategy through AI
0.5% revenue growth achieved by optimizing pricing strategy through AI
We deployed Automated Data Prep & Time Series Forecasting to help Prio predict competitor retail pricing at a local level.
About the project:
Prio is the largest producer of biofuels in Portugal. More than 250 service stations are operated by the company, under the commercial brands Prio and Shell, both in Portugal and Spain. In order to supply its biodiesel plant, Prio uses residual raw materials from sectors as diverse as margarine production, sauces, olive oil, and coffee.
What we did:
Prio Achievements using AI in Customer Service
>90% More accuracy vs. the previous solution
Lead time 4 weeks – Faster than alternative data science approach
The challenge
Prio needed a solution to optimize its pricing strategy radically.
The main objective is to determine optimal retail pricing as a function of competitors & margins.
The solution
We deployed Automated Data Prep & Time Series Forecasting to help Prio predict competitor retail pricing at a local level.
The output is used to automatically optimize the pricing strategy
Impact:
0.5%
Increase in revenue derived from improved pricing strategy
>90%
More accuracy vs. the previous solution
Lead time 4 weeks
Faster than alternative data science approach
About the project:
Prio is the largest producer of biofuels in Portugal. More than 250 service stations are operated by the company, under the commercial brands Prio and Shell, both in Portugal and Spain. In order to supply its biodiesel plant, Prio uses residual raw materials from sectors as diverse as margarine production, sauces, olive oil, and coffee.
What we did:
Prio Achievements using AI in Customer Service
>90% More accuracy vs. the previous solution
Lead time 4 weeks – Faster than alternative data science approach
The challenge
Prio needed a solution to optimize its pricing strategy radically.
The main objective is to determine optimal retail pricing as a function of competitors & margins.
The solution
We deployed Automated Data Prep & Time Series Forecasting to help Prio predict competitor retail pricing at a local level.
The output is used to automatically optimize the pricing strategy
Impact:
0.5%
Increase in revenue derived from improved pricing strategy
>90%
More accuracy vs. the previous solution
Lead time 4 weeks
Faster than alternative data science approach
About the project:
Prio is the largest producer of biofuels in Portugal. More than 250 service stations are operated by the company, under the commercial brands Prio and Shell, both in Portugal and Spain. In order to supply its biodiesel plant, Prio uses residual raw materials from sectors as diverse as margarine production, sauces, olive oil, and coffee.
What we did:
Prio Achievements using AI in Customer Service
>90% More accuracy vs. the previous solution
Lead time 4 weeks – Faster than alternative data science approach
The challenge
Prio needed a solution to optimize its pricing strategy radically.
The main objective is to determine optimal retail pricing as a function of competitors & margins.
The solution
We deployed Automated Data Prep & Time Series Forecasting to help Prio predict competitor retail pricing at a local level.
The output is used to automatically optimize the pricing strategy
Impact:
0.5%
Increase in revenue derived from improved pricing strategy
>90%
More accuracy vs. the previous solution
Lead time 4 weeks
Faster than alternative data science approach
