Customer relationship management (CRM)
invloves managing all aspects of customer's relationship with an organization to increase customer loyalty and retention and an organizations profitability.
CRM analysis technologies
help organizations segment their customers into categories such as best and worst customers
CRM predicting technologies
help organziations make predictions regarding customer behavior such as which customers are at risk of leaving
supports traditional transactional processing for day-to-day front-office operations or systems that deal directly with the customers
supports back-office operations and strategic analysis and includes all systems that do not deal directly with customers
compile customer information from variety of sources and segment the information for different marketing campaigns
Campaign management systems
guide users through marketing campaigns performing such tasks as campaign definition, planning, scheduling, segmentation, and success analysis
Sale force automation (SFA)
is a system that automatically tracks all of the steps in the sales process
Primary operational CRM technologies a sales department can implement to increase customer satisfacation
1) Sales management CRM systems 2) Contact management CRM systems 3)Opportunity management CRM systems
Sales managment CRM systems
automate each phase of the sales process, helping individual sales representatives coordinate and organize all of their accounts
Contact management CRM system
maintains customer contact information and identifies prospective customers for future sales
Opportunity managemetn CRM systems
target sales opportunities by finding new customers or companies for future sales
CRM pointers for gaining prospective customers
1) Get their attention 2) Value their time 3) Overdeliver 4) Contact frequently 5) Generate a trustworthy mailing list 6) follow up
interactive voice response (IVR)
directs customers to use touch-tone phones or keywords to navigate or provide information
automatically dials outbound calls and when someone answers, the call is forwarded to an available agent
web-based self-service systems
allow customers to use the web to find answers to their questions or solutions to their problems
call scripting systems
acces organizational data bases that rack similar issues or questions and automaticallys generate the details for the CSR who can then relay them to the customer
Examples of sales metrics
number of prospective customers, number of new customers, number of retained cusomers, number of open leads, number of sales calls, number of sales calls per lead
Examples of service metrics
cases closed same day, number of cases handled by agent, number of service calls, average number of service requests by type, average time to resolution, average number of service calls per day
Examples of Marketing metrics
number of marketing campaigns, new customer retention rates, number of responses by marketing campaign, number of purchases by marketing campaign, rev generated by marketing campaign
occurs when a website can know enough about a person's likes and dislikes to fahsion offers that are ore likley to appeal to that person
Analytical CRM Information Examples
1) Give customers more of what they want 2) Find new customers similiar to the best customers 3) Find out what the organization does best 4) Beat competitors to the punch 5) Reactive inactive customers 6) Let customers know they matter
Supplier relationship management (SRM)
focuses on keeping suppliers satisfied by evaluating and categorizing suppliers for different projects, which optimizes supplier selection
Partner relationship managment (PRM)
focuses on keeping vendors satisfied by managing alliance partner and reseller relationships that provide customers with the optimal sales channel
Primary benefits of PRM (partner relationship management)
expanded market coverage, offerings of specialized products and services, broadened range of offerings,and more complete solution.
Employee relationship management (ERM)
provides employees with a subset of CRM applications available through a web browser. Many applications of this assist the employee in dealing with customers by providing detailed information on company products, services, and customer orders.
Business Intelligence (BI)
refers to applications and technologies that are used to gather, provide acces to, and analyze data and information to support decision-making efforts.
Reliable (BI Data Analysis)
the data have been documented as the certified or approved data for the enterprise. The business users are confident that the data are the best possible and that they suit the decision- making purposes
Consitent (BI Data Analysis)
the processes that deliver the data to the business community are well documented; there are no suprises such as a missing or inaccurate data in the mix, analytics that will not run, response times that are unpredicatble
Understandable (BI Data Analysis)
the data have been defined in business terms;calculations and algorithms are easily accessed for comprehension. These are documented in a data dictionary or metadata repository that is easy to access and understand.
Easily Manipulated (BI Data Analysis)
It is no longer required to have PhD in statistics to get sophisticated analytics delivered to users' fingertips. And it is just as easy to change the question or set different parameters to twist and turn the data in ways unimaginable just a few years ago.
helps with achieving long term goals, planning, results in marketing campaign. achieve long term organizational goals, primarily used by executives and managers. Months to years. Uses historical data metrics
helps with daily analysis, results in refind campaign. Primarily used by executives and managers. Day(s) to weeks to months. Uses historical data metrics
Helps with immediate actions, results in sales revenue, manage daily operations. Primarily used by managers, analysts, operational users. Intraday. Uses real-time data metrics.
Is the time it takes a human to comprehend the analytic result and determine an apporpriate action.
use a variety of techniques to find patterns and relationships in large volumes of information and infer rules from them that predict future behavior and guide decision making
a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible
reveals the degree to whcih variables are related and the nature and frequency of these relationships in the information
market basket analysis
analyzes such items as websites and checkout scanner information to detect cusomters' buying behavior and predict future behavior
performs such functions as information correlations, distributions, calculations, and variance analysis.
time-stamped information collected at a particular frequency. ex. web site visits per hour, sales per month, calls per day.
include working time saved in producing reports, selling information to suppliers, and so on
indirectly quantifiable benefits
indirectly quantifiable benefits can be evaluated through indirect evidence-improved customer service means new business from the same customer