Data - Driven
Innovation Services
Harnessing the power of Data and AI to create Business Value
86% of CEOs consider digital technologies and AI to be the priority № 1 for their companies
New types of income
New revenues will be obtained through the use of AI-based products and services (source: Gartner)
Improved Customer Experience
95% Customer interactions will be carried out using AI tools on 2025 (source: Servion)
Lower operating costs
Using AI for routine operations brings significant savings in operating costs
Increased productivity
By 2025, over 50 employers believe that managers in finance, marketing, and sales will require expertise in data analysis and AI (source: Business-Higher Education Forum).
Increase asset efficiency
AI can potentialy be used to manage assets, improve forecasting, detect defects and improve net savings
Risk reduction
AI is a tool to achieve the strategic goals to take decisions on risk assessment of Clients in real time
Advanced analytics & AI use cases
Sales
Challenge
Accurate sales forecasting is difficult due to various internal and external factors
Solution
Azure Machine Learning is used to train models on historical sales data, taking into account various factors like seasonality, promotional activities, and market trends. These models can then forecast future sales with a higher degree of accuracy
Benefits
Better inventory management, resource allocation and improved operational efficiency and cost savings
Challenge
Sales assistants need timely and relevant information to improve their sales pitches
Solution
A bot can provide real-time insights about customers and prospects, suggest personalized sales pitches, and automate routine tasks. Azure Bot Service powers the conversational interface, while Azure Cognitive Services provide intelligent insights
Benefits
Increased sales productivity, improved customer engagement, and enhanced sales effectiveness
Challenge
Pricing products in a competitive and dynamic market
Solution
Machine learning models are trained on historical sales, competitor pricing, and market demand data to suggest optimal pricing in real-time
Benefits
Increased sales, improved competitiveness, and maximized profit margins
Challenge
Identifying and prioritizing high-quality leads from a large pool of prospects
Solution
Azure Machine Learning is used to train models on historical sales data and lead interaction data. This model assigns a quality score to each lead, helping sales teams to prioritize their efforts on high-potential leads
Benefits
Improved sales productivity, increased conversion rates, and better alignment between sales and marketing teams
Sales
Challenge
Accurate sales forecasting is difficult due to various internal and external factors
Solution
Azure Machine Learning is used to train models on historical sales data, taking into account various factors like seasonality, promotional activities, and market trends. These models can then forecast future sales with a higher degree of accuracy
Benefits
Better inventory management, resource allocation and improved operational efficiency and cost savings
Challenge
Sales assistants need timely and relevant information to improve their sales pitches
Solution
A bot can provide real-time insights about customers and prospects, suggest personalized sales pitches, and automate routine tasks. Azure Bot Service powers the conversational interface, while Azure Cognitive Services provide intelligent insights
Benefits
Increased sales productivity, improved customer engagement, and enhanced sales effectiveness
Challenge
Pricing products in a competitive and dynamic market
Solution
Machine learning models are trained on historical sales, competitor pricing, and market demand data to suggest optimal pricing in real-time
Benefits
Increased sales, improved competitiveness, and maximized profit margins
Challenge
Identifying and prioritizing high-quality leads from a large pool of prospects
Solution
Azure Machine Learning is used to train models on historical sales data and lead interaction data. This model assigns a quality score to each lead, helping sales teams to prioritize their efforts on high-potential leads
Benefits
Improved sales productivity, increased conversion rates, and better alignment between sales and marketing teams
Sales
Challenge
Accurate sales forecasting is difficult due to various internal and external factors
Solution
Azure Machine Learning is used to train models on historical sales data, taking into account various factors like seasonality, promotional activities, and market trends. These models can then forecast future sales with a higher degree of accuracy
Benefits
Better inventory management, resource allocation and improved operational efficiency and cost savings
Challenge
Sales assistants need timely and relevant information to improve their sales pitches
Solution
A bot can provide real-time insights about customers and prospects, suggest personalized sales pitches, and automate routine tasks. Azure Bot Service powers the conversational interface, while Azure Cognitive Services provide intelligent insights
Benefits
Increased sales productivity, improved customer engagement, and enhanced sales effectiveness
Challenge
Pricing products in a competitive and dynamic market
Solution
Machine learning models are trained on historical sales, competitor pricing, and market demand data to suggest optimal pricing in real-time
Benefits
Increased sales, improved competitiveness, and maximized profit margins
Challenge
Identifying and prioritizing high-quality leads from a large pool of prospects
Solution
Azure Machine Learning is used to train models on historical sales data and lead interaction data. This model assigns a quality score to each lead, helping sales teams to prioritize their efforts on high-potential leads
Benefits
Improved sales productivity, increased conversion rates, and better alignment between sales and marketing teams
Our approach to implement Advanced Analytics and AI Solutions
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Package 1
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Package 1
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