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Webinar Pricing Analytics_​English

Pricing Analytics

Pricing Analytics


Workflow of Webinar "Pricing Analytics" by STAR COOPERATION, co-hosted by KNIME, June 30th, 2020

Use-Case: Price optimization for an e-commerce shop (fictive data set)

Pricing Analytics is used to understand which factors influence performance on a granular level and how optimized pricing can be used to increase turnover and sales.
Pricing in combination with KNIME is a good way to use your data in a target-oriented way and with little manual effort, thus optimising your pricing.

The highlights of our webinar:
- Data preparation and analysis for pricing
- Integration of competition information
- Price optimisation approach of Value Based Pricing
- Price line optimisation and its implementation

Read data Data preparation and data transformation Data visualisationExemplary performance analysis Competition CheckWe would be happy to helpyou set up a web crawlingsystem using Java orPhyton. Price optimisation using various statistical modelsNote: This is an example of the application of a regression to explain sales prices. For a good prediction of sales prices it is necessary to test in advance which independent variables explain the current sales price. Thequality of the model must also be taken into account. We would be happy to advise you on which article groups such an approach is useful for, which variables can be taken into account and which different statisticalmodels can be applied and combined. Application of a value-based pricing approach (exemplary using sales development, distance to competitors and product value)We would be happy to advise you on which factors make sense for a value-based pricing approach in your industry and for your products and on the optimal weighting of the factors. Data export Webinar-Worklfow "Pricing Analytics" by STAR COOPERATION, co-hosted by KNIME, June 30th, 2020Use-Case: Price optimization for an e-commerce shop (fictive data set)Pricing Analytics is used to understand which factors influence performance on a granular level and how optimized pricing can be used to increase turnover and sales. Pricing in combination with KNIME is a good way to use your data in a target-oriented way and with little manual effort, thus optimising your pricing.The highlights of our webinar:- Data preparation and analysis for pricing- Integration of competition information- Price optimisation approach of Value Based Pricing- Price line optimisation and its implementation Competition Check ResultsAdds order dataNew columnYear of orderSales per year and product groupRemovescancelled ordersand returnsTurnoverCalculationBar chart: Sales development per product grioupGraphic: Turnover per product group over time Turnover per product groupand per yearAdds competitionpricesOverviewarticle price rangePrice predictionLearns regressionCreatestraining dataCalculation ofnew sales pricesNew sales priceSales per productand per yearSales development in percentFilterarticles with turnoverAggregationby article-IDScore assignment forsales developmentScore assignmentProduct ValueAveragecompetition priceScore assignmentcompetitive pressureArticle OverviewAdds scoresales developmentScore_OverallAssignsprice adjustmentData exportOrders 2019Turnover by product groupTurnover developmentin percentTurnover developmentin percent Turnoverby product groupOrders 2017-2018Excel Reader (XLS) Joiner String Manipulation Pivoting Row Filter Math Formula Color Manager GroupBy Bar Chart(JFreeChart) Line Plot Pivoting Color Manager Joiner Box Plot RegressionPredictor Linear RegressionLearner Partitioning Column Merger Round Double Pivoting Math Formula Row Filter GroupBy Rule Engine Rule Engine Math Formula Rule Engine Excel Reader (XLS) Joiner Math Formula Rule Engine Excel Writer (XLS) File Reader Searches for article"screw driver" MV Handling GroupBy Math Formula Calculates new sales price andreviews contribution margin Calculates new sales price andreviews contribution margin Math Formula GroupBy File Reader Concatenate Read data Data preparation and data transformation Data visualisationExemplary performance analysis Competition CheckWe would be happy to helpyou set up a web crawlingsystem using Java orPhyton. Price optimisation using various statistical modelsNote: This is an example of the application of a regression to explain sales prices. For a good prediction of sales prices it is necessary to test in advance which independent variables explain the current sales price. Thequality of the model must also be taken into account. We would be happy to advise you on which article groups such an approach is useful for, which variables can be taken into account and which different statisticalmodels can be applied and combined. Application of a value-based pricing approach (exemplary using sales development, distance to competitors and product value)We would be happy to advise you on which factors make sense for a value-based pricing approach in your industry and for your products and on the optimal weighting of the factors. Data export Webinar-Worklfow "Pricing Analytics" by STAR COOPERATION, co-hosted by KNIME, June 30th, 2020Use-Case: Price optimization for an e-commerce shop (fictive data set)Pricing Analytics is used to understand which factors influence performance on a granular level and how optimized pricing can be used to increase turnover and sales. Pricing in combination with KNIME is a good way to use your data in a target-oriented way and with little manual effort, thus optimising your pricing.The highlights of our webinar:- Data preparation and analysis for pricing- Integration of competition information- Price optimisation approach of Value Based Pricing- Price line optimisation and its implementation Competition Check ResultsAdds order dataNew columnYear of orderSales per year and product groupRemovescancelled ordersand returnsTurnoverCalculationBar chart: Sales development per product grioupGraphic: Turnover per product group over time Turnover per product groupand per yearAdds competitionpricesOverviewarticle price rangePrice predictionLearns regressionCreatestraining dataCalculation ofnew sales pricesNew sales priceSales per productand per yearSales development in percentFilterarticles with turnoverAggregationby article-IDScore assignment forsales developmentScore assignmentProduct ValueAveragecompetition priceScore assignmentcompetitive pressureArticle OverviewAdds scoresales developmentScore_OverallAssignsprice adjustmentData exportOrders 2019Turnover by product groupTurnover developmentin percentTurnover developmentin percent Turnoverby product groupOrders 2017-2018Excel Reader (XLS) Joiner String Manipulation Pivoting Row Filter Math Formula Color Manager GroupBy Bar Chart(JFreeChart) Line Plot Pivoting Color Manager Joiner Box Plot RegressionPredictor Linear RegressionLearner Partitioning Column Merger Round Double Pivoting Math Formula Row Filter GroupBy Rule Engine Rule Engine Math Formula Rule Engine Excel Reader (XLS) Joiner Math Formula Rule Engine Excel Writer (XLS) File Reader Searches for article"screw driver" MV Handling GroupBy Math Formula Calculates new sales price andreviews contribution margin Calculates new sales price andreviews contribution margin Math Formula GroupBy File Reader Concatenate

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Created by: CWinne
Created at: 2020-04-29
On NodePit since: 2020-06-30
Last update: 2024-04-26
Created with KNIME version: v4.1.3

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