Chapter 5 - CRM, Big Data, and Marketing Analytics Flashcards
Customer Relationship Management
A comprehensive business model for increasing revenues and profits by focusing on customers.
3 CRM Major Objectives
1) Customer acquisition—acquiring the right customers based on known or learned characteristics that will drive growth and increase margins.
2) Customer retention—retention of satisfied and loyal profitable customers and channels, and thus growing the business profitably over the long run.
3) Customer profitability—increased individual customer margins while offering the right products at the right time.
Customer Satisfaction
The level of liking an individual harbours for an offering—that is, to what level is the offering meeting or exceeding the customer’s expectations?
Customer Loyalty
the degree to which an individual will resist switching or defecting from one offering to another.
customer lifetime value (CLV)
an important metric in CRM that demonstrates that successful long-term relationships with customers pay handsomely in terms of cost savings, revenue growth, profits, referrals, and other important business success factors.
Return on Customer Investment (ROCI)
A calculation that estimates the projected financial returns from a customer. It is a useful strategic tool for deciding which customers deserve what levels of investment of various resources.
Firing a customer
The shifting of investment of resources from a less attractive customer to more profitable ones.
Customer Touchpoints
Where the selling firm touches the customer in some way, thus allowing for information about him or her to be collected.
Data warehouse
a compilation of customer data generated through touchpoints that can be transformed into useful information for marketing management decision making and marketing planning
Data mining
a sophisticated analytical approach to using the massive amounts of data accumulated through a firm’s CRM system to develop segments and microsegments of customers for purposes of either market research or development of market segmentation strategies
Database marketing
Direct marketing involving the utilization of the data generated through CRM practices to create lists of customer prospects who are then contacted individually by various means of marketing communication.
Organizational Learning
The analysis and refinement phase of the CRM process that is based on customer response to the firm’s implementation strategies and programs.
formalization
The formal establishment of a firm’s structure, processes and tools, and managerial knowledge and commitment to support its culture.
Customer Mind-Set
An individual’s belief that understanding and satisfying customers, whether internal or external to the organization, is central to the proper execution of his or her job.
Big Data
the ever-increasing quantity and complexity of data that is continuously being produced by various technological sources
Structured Data
data that is generated in such a way that a logical organization is imposed on it during its generation, this enabling it to be more readily analyzable for knowledge creation
Unstructured Data
data that is generated in such a way that a logical organization is imposed on it during its generation, this enabling it to be more readily analyzable for knowledge creation
Semi-Structured Data
data that contains some elements of structure that makes it easier for machines to understand its organization, but still contains parts that do not possess an appropriate level of structure to make them readily analyzable by automated means for knowledge creation
Marketing Analytics
a set of methods facilitated by technology that utilize individual-level and market-level data to identify and communicate meaningful patterns within the data for the purpose of improving marketing-related decisions
Marketing Analyst
an individual familiar with different forms of market and customer data and who is trained to conduct different market analyses, as well as the computational costs associated with those analyses
Descriptive Analytics
an approach that utilizes data to provide summary insights
Diagnostic Analytics
an approach that utilizes data to explore the relationship between different marketing-relevant factors that influence the organization’s performance either directly or indirectly
Prescriptive analysis
an approach that involves determining the optimal level of marketing-relevant factors for a specific context by considering how adjusting their levels in varying ways will impact different marketing outcomes
Predictive analytics
an approach that utilizes data to make predictions about future marketing outcomes of interest
Sentiment analysis
a type of analytic method that identifies the general attitude (e.x. positive, negative, or neutral) contained within a message through an analysis of its content
attribution
a type of analytic method that identifies the general attitude (e.x. positive, negative, or neutral) contained within a message through an analysis of its content
content filtering
an analytical method that identifies which products or services to recommend based on a determination of how similar a product or service seems to be to those that the customer has demonstrated a preference for in the past, or is currently considering
Collaborative filtering
an analytic method that predicts a customer’s preferences for products or services based on the observed preferences if customers who are perceived to be similar
Marketing Dashboard
A comprehensive system of metrics and information uniquely relevant to the role of the marketing manager in a particular organization. Dashboards provide managers with up-to-the-minute information necessary to run their operation.
Return on Marketing Investment (ROCI)
What impact an investment in marketing has on a firm’s success, especially financially.
4 elements of the CRM process cycle
1) Knowledge discovery
2) Marketing planning
3) Customer Interaction
4) Analysis and refinement
To maximize a firms ability to successfully use touchpoints
- identify all potential touchpoints
- develop specific objectives for what kind of information can be collected at each touchpoint
- determine how that information will be collected and ultimately integrated into the firm’s overall customer database
- develop policies on how the information will be accessed and used.