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Pricing - machine learning & algorithms

We help our clients make better pricing decisions and exploit the full potential of existing data through the use of prescriptive models and machine learning algorithms

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Value for customers

For B2B companies that offer a large number of product codes or families and serve customers operating in different sectors and in different geographical areas, the use of descriptive data analysis is often not enough. We create machine learning models for our customers that make it possible to evolve, simplify and make pricing decision-making processes more effective.

The challenges

The main decisions and challenges companies need to face to improve profitability and successfully compete on the market.

Segmentation

how we can leverage existing data to develop segmentation that takes into account the propensity to pay

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How can we prescriptively determine the customers with the greatest potential for improvement through pricing?

Pricing health per customer
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Price risk and price power

how can we dynamically adapt pricing levels according to the price risk or the pricing power of the company by segment?

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Customer health score

how can we adjust the price per customer according to the customer health score or the customer's risk of loss?

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How we help our customers
  • Data enrichment

  • Behavioral feature calculation

  • Influence factors analysis

  • Decomposition tree on price index

  • Classifying algorithms

  • Deployment on machine learning software (knime, rapidminer)

Machine learning models for segmentation
  • Multivariate regression on target price

  • Cross & up selling score

  • Churn score and price risk

  • Customer profiling based on the type of corrective action (price, volume, mix)

Machine learning models for the price target
  • Price risk by segment

  • Price power by segment

  • Health score per client

  • Price opportunity score per customer

  • Business intelligence deployment (Microsoft power BI, Qlik)

  • Design and training on decision-making processes

Price scoring
(Healh)
Expected results
Borsa giù

Predictive models for pricing

Development of predictive and prescriptive machine learning models for pricing based on enriched internal (transactions, offers, etc.) and (where available) external data

Analisi di mercato

Integration with existing systems

Integration of models with existing ERP and CRM systems


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Autonomy

Use of user-friendly and low-cost platforms to allow our customers to manage models and algorithms independently or with limited external support.

Why Alyant
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Specialization : experience focusing on the development of prescriptive models in the field of pricing

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User-friedly technologies : adoption of self-service machine learning software that does not require code development

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Integration : integration of models with existing systems (ERP, CRM, business intelligence)

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