Customer 360 Analytics is an integrated solution developed by TANI within Microsoft Dynamics 365 Customer Insights platform. It enables companies to see and analyse their CRM KPIs, Customer Segments, Churn Predictions and Potential Revenues with just a few clicks in order to make smarter and faster decisions.
TANI Customer 360 Analytics is designed especially for the companies that want the become more customer centric without losing any time. Customer 360 Analytics offers firms up-to-date CRM KPIs and automated action-based customer segments and uses the Azure Machine Learning(ML) environment to build ML based analytical models to help companies deeply analyse and understand their customers.
- Analyse your customer data
- Turn your data into actionable insights
- Make smarter & faster decisions
- Prevent churn & increase retention
- See a 360 degree view of customers
- Monitor your up-to-date CRM KPIs
Monitor trends in:
- Number of Total Customers & Transactions
- Average Basket Sizes and Customer Recencies
- Number of Active-Inactive-Lost-New Customer
- Customer Segmentation
- Predictive Churn Model
- Purchase Prediction Model
- Gain deeper insights
- Focus on most valuable customers
- Prevent churn
- Maximise customer revenues
- Demographics
- Average Spending
- Churn Score
- Customer Status (Active, Inactive, Lost)
- Favourite Category
market (Turkey) and Internationally.
Best Use of Technology
Best Use Of AI
Best Measurement Technology
Customer 360 Analytics involves TANI’s extensive CRM experience and integrates it with its broad data science capabilities.
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analytics@tani.com.tr
• Number of transactions per customer
• Average customer recencies
• Average basket sizes
• Comparative indicators between the last two periods
1. Customer Segmentation Model: A model using clustering algorithms to segment customers in terms of their recency, frequency and monetary values. The segments include “VIP Customers”, “Loyal Customers”, “Potential Customers”, “Less Valuable Customers”, “Inactive Customers” etc. The segmentation process runs parallel for the last 2 periods so the firm can see both the current and previous segments of customers and take actions based on the segment migrations. (e.g. Customers who used to be in VIP Segment but who are currently inactive)
2. Predictive Churn Model: A predictive churn model using ML algorithms to predict customers’ churn probability by taking their past transaction data and demographics into consideration. Model offers a churn score for each customer and a churn segment.
3. Customer Purchase Prediction Model: A predictive model using ML algorithms to predict customers’ spending potential for the next period by taking their past transaction data and demographics into consideration.
Based on all the customer and transaction data and outputs of analytical models, the platform will provide several customer segments of top priority, enabling to take quick actions with the objectives of preventing churn, reactivating customers, growing customer revenues, etc. Examples:
• Customers migrating from upper segments to lower segments
• VIP customers likely to increase their spending in the next period
• One-Category customers
• Customers likely to increase their spending in the next period
• Young and potential customers
• Customers having above/below average basket sizes
The platform includes a dynamic Customer 360 Analytics
monitoring tab containing all the derived CRM information for
each customer.
Customer-id based search is enabled to view a customer specific
page including info such as:
• Demographics
• Customer Segment
• Customer Status (Active, Inactive, Lost,etc.)
• Favourite Branch-Category-Transaction Time
• Spending Prediction
• Predictive Churn Score
