Customer Relationship Management & Business Intelligence

Customer Relationship Management (CRM)
Involves managing all aspects of a customer’s relationship with an organization to increase customer loyalty and retention and an organization’s profitability.

Ex. Walgreens

CRM as Business Strategy
It is actually a process and a business goal enhanced by technology. Can help organization identify customers and design specific marketing campaigns tailored to each customer, increasing spending.
Ex. Eddie Bauer
RFM
Formula that industry insiders use to find its most valued customers–> Recency, Frequency, Monetary value
Evolution of CRM
3 Phases:
1. CRM reporting technologies: WHAT
-help organizations identify their customers across other applications

2. CRM analysis technologies: WHY
-help organizations segment their customers into categories such as best and worst customers

3.CRM predicting technologies: WILL
-help organizations make predictions regarding customer behavior such as which customers are at risk of leaving

Operational CRM
supports traditional processing for day-to-day front-office operations or systems that deal directly with the customers
Analytical CRM
supports back-office operations and strategic analysis and includes all systems that do not deal directly with the customers
(Marketing) List Generator
compiles customer info from a variety of sources, segment info for diff marketing campaigns–> type of customer needs to target for marketing campaigns
(Marketing) Campaign Management
guide users through marketing campaigns performing such tasks as campaign definition, planning, scheduling, segmentation, success analysis. can calculate ROI of campaigns
(Marketing) Cross-Selling and Up-Selling
Cross-selling: selling additional products or services to a customer
ex. McD’s asking if want apple pie with meal

Up-selling: increasing the value of the sale
ex. McD’s asking if want to supersize the meal

Things to remember
*Now about selling a customer as many products as possible (not as many customers for a product)
*Sales departments first to begin developing CRM
Sales Force Automation (SFA)
system that automatically tracks all of the steps in the sales process
(Sales Dept) Sales Management CRM System
automate each phase of sale process, helping individual sales reps coordinate and organize all their accounts
ex. alarm reminders, calendars
(Sales Dept) Contact Management CRM System
maintains customer contact info and identifies prospective customers for future sales
(Sales Dept) Opportunity Management CRM System
target sales opportunity by finding new customers or companies for future sales
Marketing
*Primary ones for marketing are
-List generator
-Campaign management
-cross-selling and up-selling
Sales Dept
-Sales Management CRM System
-Contact Management CRM System
-Opportunity Management CRM System
Customer Service
-Contact Center
-Web-based self service
-Call scripting
(Cust. Service) Contact Center
call center, where customer service reps answer cust inquiries
(Cust. Service) Web-Based Self Service
allow customers to use web to find answers to problems

feature can be a “click-to-talk” button

(Cust. Service) Call-Scripting
access organizational databases that track similar issues/ questions and automatically generate details for the cust. service rep who can then relay them to the cust.
Personalization
occurs when a website can know enough about a person’s likes and dislikes to fashion offers more likely to appeal to that person
Supplier Relationship Management (SRM)
focuses on keeping suppliers satisfied by evaluating and categorizing suppliers for diff projects, optimizing supplier selection
Partner Relationship Management (PRM)
focuses on keeping vendors satisfied by managing alliance partner and reseller relationships that provide customers with the optimal sales channel.
Employee Relationship Management (ERM)
provides employees with a subset of CRM apps available through a web browser.
Business Intelligence (BI)
refers to the application and technologies used to gather, provide access to, and analyze data and info to support decision-making efforts.

types:
Operational BI
Tactical BI
Strategic BI

Data Mining
the process of analyzing data to extract information not offered by the raw data alone

-summary of info level (coarse granularity)
-increasing detail (drill up)
-decreasing detail (drill down)

Forms
Cluster Analysis
Association Detection
Statistical Analysis

Data-mining Tools
use variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decisions

-classification
-estimation
-affinity grouping
-clustering (making more homogenous subgroups)

Cluster Analysis
data mining technique used to divide an info set into mutually exclusive groups, members of each group as close as possible, diff groups as far apart as possible
Association Detection
reveals the degree to which variables are related and the nature of frequency of these relationships in the info

ex. 50% of time A and B occur together

*Common form:
Market Basket Analysis- analyzes things like websites and checkout scanner info t detect customer’s buying behavior and predict future by iding affinities among choices of product/ service–> frequently used for CROSS-SELLING

Statistical Analysis
information correlations, distributions, calculations, variance analysis.
Forecasts
Predictions made on the basis of time-series information (time-stamped info collected at a particular frequency)