Customer Analytics
A deeper understanding of the customer has never been as important as it is today. Social media, open information, new business models, and ever increasing options make it paramount to understand the pulse of customers and predict their behavior.
CORE OBJECTIVE
The core objectives of customer satisfaction, loyalty, and value remain the same, however, the means to the end are changing rapidly. Combining in-store and online behaviors along with social hearing and surveys is giving organizations a 360-degree customer view.
HOW IT HELPS?
Analytics is helping organizations predict purchase patterns, customer behaviors, lifestyle preferences, and offering them hyper-personalized propositions. Data, technology, and predictive analytics are being used to redefine customer interactions.
WHAT IS THE ADVANTAGE?
Organizations that deeply understand their customers' buying habits and lifestyle preferences can more easily predict those people's behavior and, therefore, can optimize the customer journey. Accurate analysis requires large amounts of accurate data.
Understanding what?
For all types of customer analytics, you may need to use techniques like data collection and segmentation, modeling, data visualization, and more.
Customer journey
It is key to understand all the key factors of customer relationship. Because it is a lifeline of any business to keep customer in good mood.
Step 1 | Acquire |
Step 2 | Understand |
Step 3 | Grow |
Step 4 | Retain |
Aquire
Lead Scoring
Lookalike Modeling
Response Modeling
Understand
Customer Segmentation
Customer 360 View
Survey Analytics
Customer Experience
Grow
Pricing & Promotions
Personalization
Customer Lifetime Value
Up-sell/Cross-sell
Retain
Churn Modeling
Loyalty Analytics
Contact Center Analytics
Customer Service
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