Customer Analytics




We are experienced with implementing, evaluating and upgrading analytical models. Within each stage of the analytical project, we cooperate with our clients by sharing knowledge regarding results, methods, interpretations and solutions.



Our confidence and experience regarding analytical projects covers: data gathering, data cleaning, data auditing, data quality and data analysis. We specialize in understanding client needs, identifying purchase triggers, uncovering mechanisms responsible for creating engagement and customer loyalty. We do this by using a wide variety of methods and approaches rooted in our experiences and scientific background.

We offer advice and guidelines on how to utilize customer data and analytical models. Our main business challenge is developing and refining analytical solutions so they can give our clients a solid background for their business decisions.

Customer Analytics - infographic


Our analytical support concerns key areas where business decisions require knowledge. 

  • Building customer segmentation strategies
  • Understanding customer decisions and customer activities
  • Designing predictive models that describe buying patterns
  • Basket analysis
  • Modeling data to recommend cross-selling or tie-in sales
  • Building retention programs
  • Designing churn models
  • Building customer activity KPIs

Loyalty program data analysis

  • Building parameters and analyzing the effectiveness of your loyalty program
  • Building targeted promotion strategies for defined segments
  • Fraud detection
  • Redemption patterns analysis
  • Measuring the accuracy of program benefits through the participants’ behavioral patterns


Promotion Performance analysis

  • Analyzing past promotion effectiveness
  • Using sales data to optimize product-based offers
  • Marketing scorecards – development and maintenance

Category management

  • Analyzing customer loyalty toward brands
  • Adjusting product category structures to customer segments
  • Diagnosing the sales growth of product categories, and brands
  • Evaluating the effectiveness of merchandising tools


Sales support

  • Assessing customer share of wallet
  • Identifying sales potentials and market niches
  • Uncovering reasons for switching between stores/chains
  • Identifying customers who leave and attracting valuable lost customers back
  • Analyzing the price elasticity of demand
  • Data quality improvement plans and maintenance
  • Creation and development of marketing databases
  • Data enrichment & integration
  • Building 360° customer views, analysis and reports
  • Designing marketing campaigns and measuring their effectiveness
  • Marketing automation
  • Couponing actions
  • Next-Best-Action Marketing
  • Acquisition & retention programs
  • Activation strategies for lost customers
  • Customer advisory board
  • Customer engagement programs
  • Net Promoter Score
  • Customer satisfaction monitoring
  • Customer-oriented research panels – development and maintenance
  • Mobile technologies and gamification
  • Identifying advocates, opinion leaders, their friends and followers
  • Thematic analysis of comments, suggestions regarding products and services
  • Identifying threats to corporate brands and reputation
  • Using sentiment analysis to identify the emotional bonds between customers and brands/products
  • Using text mining techniques to deal with the vast amount of textual data      
  • Analyzing reviews and opinions on brands, products and services
  • Contents of blogs and forums and web activity analysis



Building profitable relationships with your clients

  • Gain genuine customer insights: needs, behavior, decisions and engagement
  • Optimize performance of loyalty programs
  • Adjust brand offers to the needs of targeted customers (most active, most valuable, etc.)

Improve marketing strategies

  • Build client value by shaping purchasing patterns
  • Lower business risks thanks to the improved accuracy of forecasts
  • Increase ROI, response rates and conversion index by implementing effective marketing strategies
  • Adjust the average product margin per category
  • Understand brand position in customer basket 

Develop effective analytical models and tools

  • Make business decisions based on solid data-driven models
  • Enrich data with new measures and sources
  • Develop new strategies for loyalty programs and minimize time gap between discovering marketing ideas and action

Our Clients

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B2B Loyalty & Engagement Programs: Do They Really Work?

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