Crede collects data, processes and provides analytical business solutions.
Crede tailors a customer segmentation based on the client’s strategy. Typical segmentation scenarios optimize actions in order to prioritize results for different goals such as x-sell, customer value maximization, introduce new products based on life style or payment behavior, tailor solution to a risk profile… Our segmentation models help our clients to understand their customers better and create customer action programs.
A typical project consists of the following phases:
Segmentation goal definition
Data mining and cluster grouping
Business touch: Segment profiling
Segment action programs
Analytical Sales Planning
During the last two decades, most of the competition have transformed their marketing and sales function from a market research / budget / communicate model to a sales conversion – CRM model. Current market leaders organize their sales function around lead generation. Both new and existing customers require an evaluation based on how promising the future relationship will be. Data development, enrichment and state of the art analytics are key parts of the solution. We provide the full spectrum of microtargeting services and can complement your data existing customer data, or alternatively provide fresh leads through a proprietary database that provides leads to you based on potential customers’ propensity to buy your services.
Crede optimizes the sales processes where there is a direct contact with the customer. We find ways to get the most out of your sales efforts by analyzing existing sales channels and proposing new channels if possible.
A typical project includes:
Data enrichment (if necessary)
Best sales segment mix recommendations
Next Best Product Analysis
Crede provides industry or business function focused analytical services. We aim to provide full-spectrum service beyond analytical modeling: We participate in the implementation of models and engage in periodical or in-campaign follow-up tuning.
We are capable of not only developing predictive models but also delivering end-to-end solutions for clients. Project phases we can get involved in include:
Business value definition
Conclusive reporting, Business Intelligence interphase and dashboard preparation
A typical project deliverable is a list of customers with potential to buy a given product and performance measurement reports. Through the customer lists generated by propensity models, sales conversion rates can be increased by up to 10 times.
Crede generates analytical churn prediction models that rank customers by their likeliness to leave the company meaning “churn”. A churn prediction model predicts customers who are likely to churn in the near future and the model owner can take preemptive actions.
Churn definition (for non-subscription based businesses)
Derived variable preparation
Data mining iterations
Crede also provides outsourced analytical hosting for segmentation and churn services.
Customer Lifetime Value Maximization
In the battle for customers, the least expensive way to increase your revenue is usually to deepen the relationship of your existing customers. Companies that are smart about customer value usually favor predictive analytics instead of analyzing the past profitability of a given customer. Most companies are able to calculate past customer profitability. Market leaders focus on customer lifetime value by using predictive analytics to determine future revenue streams.
Focusing on the key metric of customer lifetime value drives all analytic activities: Segmentation, loyalty schemes, churn models and cross-sell offers. Customer retention (churn prevention) actions focus on how the customer relationship will contribute to the company, instead of simply comparing cost of acquisition to cost of retention. The retention efforts are structured around our extensive experience in customer value, profitability and churn offer management.
Crede provides industry-specific models for customer lifetime value. Models are adapted to fast-changing conditions of emerging markets and tailored to the profitability models of a given project.
Customer Lifetime Value “CLTV” predicts/measures the value of a prospect or existing customer. CLTV model helps our clients to answer questions such as:
How much money per customer should I spend for customer acquisition?
Which segments of customers are profitable in the long run?
How much should I spend for the loyalty program? What level of loyalty award per customer is appropriate?
CLTV management is a framework for the sum of all acquisition, x-sell, up-sell, retention and winback efforts in terms of cost and benefit. It requires a 360 degrees view and analysis of client data but delivers a comprehensive understanding and action plan for each individual customer.
Deliverable of the project is a monetary value that represents the total expected benefit from each customer.
Customer Risk Scoring
Comprehensive assessment of receivables is a must for any monthly service contract. Whether you are underwriting a credit agreement or assessing subscriptions with overdue payments, diligence in risk assessment is a primary driver of profitability, frequently eating up a significant portion of your profit margin.
Assessment of credibility can happen at the origination of contract relationship, during the contract relationship, or eventuality when a debt is terminated – in order to estimate further collectibles via legal action.
Crede leverages the best practices of the financial industry that has a deep knowledge of the receivables markets and develops analytical models that can predict whether a customer will be delinquent in payments or default in the future. A risk scorecard helps a company to rank its customers by risk, predict a future loss and take preemptive actions.
A typical project phases are:
Data collections and derived variable preparation
Model performance management
Typical project deliverables are scorecards, associated algorithms and key performance indicators.
Crede develops comprehensive collections action in order its clients to improve receivable collections efficiency. Like all resources, collections resources are limited. Having optimized the collections process means that our clients know who to call up and are able to identify the self-payer and non-payer customers from their very first day of delinquency. Therefore, energy can be directed to where it is worthwhile to spend effort.
A typical project includes the following phases:
Analysis of existing collections tools and actions
Development of collections decision tree
Project deliverables are a collections decision tree and actions for the optimum cost-benefit results.