Capabilities of Arc Customer 360

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Arc Customer360 is a business intelligence tool architected for retail marketers for customer analytics solution which provides a blend view of customer topography. It gives detailed analysis of what when and where they buy, what products they prefer along with the frequency of their purchase and what kind of offer’s will attract them to the same store back next time they purchase.

Key Capabilities of Arc Customer 360 are highlighted as follows:
1) Market Basket Analysis(MBA) :
This analysis helps in accessing the basket characteristics, popularity of an item, marketing events tracking and analyzing the affinity for products. MBA is considered as an inexpensive technique to identify cross sell opportunities. It provides insight in to Customer’s profile about who they are and what are the major purchases they make whenever they visit the store. This helps in determining the products tend to be purchased together and products which requires more marketing promotions or which needed to be go for sale or discount.

This analysis can be applied in various ways:
• Providing offer on products that are purchased together.
• Inventory control based on demand of products.
• Placing associated products together inside the store.

Market Basket Analysis is an excellent way to understand customer and their behaviors

2) Churn prediction :
Churn Rate is the number of customers who cut relations with the company (Store) during a given time period. Tracking of churn rate will be useful to the company in preventing to lose relations with an existing customer by taking appropriate measures. Churn Prediction emphasizes on predicting the probability that a customer will stop buying from the store and ...

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...360 as a customer analytic solution can gain benefits like
 Understanding Customers
• Profiling of Customers
• Customers trend and reach
• Segment Migration and Profiling

 Marketing Effectiveness
• Measurement of Return of Index
• Analysis of Performance Drivers
Sales Trend

 Campaigns
• Response of Campaigning, its frequency and reach
• Analysis of Return of Investment

 Promotions
• Effectiveness of the channel
• Experimental Analysis Design
• Analysis of Historical Promotion

 Purchase Behavior
• Purchase trends by individual customer or other segments
• Analysis of Sales- Channel
• Analysis of Store Migration

 Loyalty
• Performance of Loyalty Program
• Points flow Analysis
• Member Activity Analysis
• Customer Lifecycle Analysis

 Product Mix
• Products which have maximum affinity and concentration.
• Brand Migration Analysis
• Seasonality Analysis.

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