Customer Relationship Management A Databased Approach - ppt video online download
A comprehensive checklist for auditing different data types in a CRM or In this post I will look at how to audit customer data based on its type. Kumar and Reinartz's, Customer Relationship Management, a Databased Approach, stresses the development of an understanding of Customer Value as the. Customer Relationship Management A Databased Approach. V. Kumar. Werner J. Reinartz. Instructor's Presentation Slides. Chapter Six. Customer Value.
Some of the most common Web 2. Social software which consists of the applications created with Web 2. In social media which is the set of social software applicationsusers can find not only information, but are active contributors Lai and To ; Razmerita et al. Therefore, social media encourage the creation, sharing and exchange of data.
As stated above, there is a large variety of types of social software applications, such as Social Networks which allow social capital to be managed more efficientlyBlogs to communicate with others more effectivelyWikis and Social bookmarking to make better use of collective intelligenceGroup chats, Mashups, Multimedia Sharing, RSS, Folksonomy or Podcasts.
These technologies are open and are designed to encourage collaboration as well as to facilitate social interaction and the sharing of knowledge Dietrich et al. Social software only provides the framework, the content is provided by people Omerzel Furthermore, the number of people using social software is very important.
As more people use these applications, the overall value of knowledge will be significantly increased, i. Recently, the social media have become a strategic tool for organisations, since they allow companies to meet the needs of customers as well as to provide them with new services Go and You Social CRM CRM can take advantage of social media, whose relational properties and characteristics are particularly well suited to customer interactions Olbrich and Holsing This definition includes the central principle of customer engagement, which was missing in earlier CRM models, and social media technologies facilitate this customer engagement Olbrich and Holsing Therefore, for a Social CRM system to work, there must be an important cultural and behavioural change both in the company as well as in the customers, as they have to change the way in which they interact Greenberg Contribution, sharing, collaboration, dynamism and bidirectional trust between the company and customers become fundamental aspects in Social CRM Lee and Lan The concept of social customer thus appears, which can be defined as a new type of customer that uses social software to search for, compare and exchange views on products and services offered by a company, and who expects companies to not only be present in that social software but also to respond to questions and participate.
This customer acquires knowledge about new products and services through social channels and networks, prefers a conversation with the particular brand rather than it being just a way to send messages and at the same time wait for an answer, and wants the company to listen to and solve their problems quickly.
The social customer creates a new business model, called social business, which can help companies increase their profitability because it allows a number of qualitative and quantitative benefits to be obtained.
The qualitative ones include: Some the most significant quantitative benefits that could be achieved with the use of Social CRM are: Both good and bad news spread quickly; social software is not well controlled or censored, so anyone can publish anything good or bad about the company or its products or services; and problems regarding personal privacy and security can emerge as the user is required to share at least some personal data.
Big Data Moreover, Social CRM benefits from Big Data, which is based on the current ability to have a large amount of data and draw conclusions about all sorts of company-customer processes and interactions.
The digital world, mobility, and permanent connectivity have completely changed these processes and interactions over the last two decades. In addition, advances in infrastructure, storage techniques, and data-processing allow these huge volumes of structured and unstructured customer data to be analysed in a very fast and efficient way, and with an acceptable cost for most organisations.
Due to the amount and complexity of these data, it is difficult to process them using traditional tools, so the use of Big Data technology is essential in order to take advantage of this kind of data Syed et al. Big Data technology is able to overcome the difficulties involved in understanding and extracting relevant knowledge from different kinds of data, which include: Diversity in types of fonts, formats and languages; Unstructured information ideas, emotions, nuances, ambiguities, polysemy, etc.
However, the growing analytical arsenal and existing advanced modelling techniques applied to massive datasets by professionals with appropriate levels of creativity and expertise are currently reaching an enormous degree of success in discovering correlations in previously unknown customer knowledge.
Big Data in Social CRM Big Data is a technology with a real ability to transform very significant aspects of customer relationship management, thereby providing companies with a competitive advantage over its competitors.
Big Data technology allows knowledge to be extracted from customer information and converted, in an effective, secure and scalable way, into real business value. From customer information and through Big Data, a company is able to reveal hidden knowledge of the customer, turning it into opportunities to maximise the business value of each customer, to act preventively, to improve customer satisfaction, to identify new opportunities, or to predict their tendency and intention profile.
It is noteworthy that companies are harnessing the power of Big Data and analytics to apply it in customer relationship management Marshall et al. The business value is derived from the knowledge generated, once it is transferred to the design of products or services, to the segmentation of customers and markets, to the acquisition of new customers, to the understanding of customers, to the evolution of the portfolio, to the optimisation of any of the internal procedures and production processes, or to the changing way companies relate with employees, citizens, suppliers, partners or customers.
This methodology was supplemented, adapted and updated based on the review of the existing literature on Web 2. This initial version was then applied to one company with the aim of analysing, validating and refining it. This consists of the following stages: Design and planning of the case study; Preparation for data collection; Collecting evidence; Analysis of collected data; and Validation of collected data. Each of them is described below: Design and planning of the case study The aims of the case study are: The first task was to select the company in which the case study was to be applied.
The criteria underlying the selection of this company were essentially: The selected company was a SME from the metal sector with a workforce of employees. Their target customer ranges from large supermarkets to little grocery stores and individuals, from all over the world.
It is important to note that this company was already using a traditional CRM application. Preparation for data collection To begin the research work, an introductory series of group interviews were held in the company.
In order to undertake all the research tasks during the application of the methodology in the company, a mixed work team was set up with members that came from both the IRIS Research Group and the Social CRM team of the company. The company Social CRM project team was made up of five area managers, representing the main areas of the company: General management, Commercial management, Financial management, Technical management and Operations management. Qualitative data were used, which were collected through direct methods using an assortment of questionnaires and templates and independent methods copies of the documents and reports used in the company.
Acknowledgments We wish to thank Alan Zhang and Bharath Rajan for their assistance and contribution in the preparation of this text. We would also like to thank our colleagues in various universities for giving us valuable suggestions in developing this book. We owe additional thanks to Renu for proofreading the manuscript. Some of the key operational challenges include low product margins on its products and a lack of direct customer contact, among other region-specific challenges.
Henkel has managed to overcome these challenges by implementing customer relationship management crm practices. Management at Henkel realized the importance of identifying and understanding the needs of individual high-value customers, in order to target, establish, develop, and retain long-lasting relationships with customers. Through these practices, Henkel has actively pursued the development of strong relationships with its customers, and at the same time increased its profitability .
V. Kumar J. Andrew Petersen. Statistical Methods in. Customer. Relationship. Management - PDF
Just like Henkel, many corporations are increasingly adopting CRM as a means to forge their competitive advantage the ability to understand individual customer needs, and therefore to manage their marketing efforts more efficiently.
Such firms are also under tremendous pressure to adjust quickly to rapid changes in the marketplace with regard to the customer, technology and marketing functions. Customers are becoming not only more value-conscious, but also less loyal and less tolerant of low service levels.
Consequently, markets are becoming more fragmented, making differentiation more difficult and competition more intense. These changes are driving companies to be customer-centric, and shifting their marketing functions from product-based to customer-based ones. At the same time, the exponential growth in data storage technology has made it possible for firms to process a much more Statistical Methods in Customer Relationship Management, First Edition.
All of these changes have had a significant influence on the rapid growth, increasing the awareness and adoption of CRM worldwide. While most firms recognize the benefits of adopting CRM practices, not all firms have been successful in their CRM implementations. We believe that having the right approach to CRM planning is critical to a firm s success.
Over the years, while technology has played a key role in the success of CRM implementation, it is but one component of CRM implementation.
An important part of CRM is identifying the different types of customers and then developing specific strategies for interacting with each customer. Examples of such strategies are developing better relationships with profitable customers, not loyal customers. That means locating and attracting customers who will be profitable, and finding appropriate strategies for unprofitable customers, which could mean eventually terminating the relationship with customers who are causing the firm to lose money.
In this book, we discuss CRM and its related strategies from a modeling perspective, with a specific focus on methodologies that can be used to obtain insights on customer metrics within a company s own customer database. To help understand the discussion on CRM models and methodologies, we start this first chapter by providing an overview of CRM and its components.
First, we present a formal definition of CRM and discuss the relevant concepts in CRM, such as customer value and customer databases. Next, we explain what is required to implement CRM strategies from a manager s perspective.
In essence, managers ultimately want to evaluate their firms marketing performances based on quantifiable indicators called customer metrics. Managers usually have to go through several data-processing steps before being able to generate the customer metrics they want. In this section, we focus on the database sources, the impact of technology on the implementation process of CRM, as well as providing a list of common customer metrics used to evaluate managerial performance.
As the conceptualizations of CRM have evolved significantly, there are various definitions of CRM depending on the perspectives looked at. An important concept in CRM is customer value.
Customer value is essentially the financial value of the customer relationship to the firm. It can be expressed in terms of contribution margin or net profit. Customer value is widely used by firms to evaluate their marketing efforts. However, it is a general term which does not refer to any specific time or duration. A better term that gives managers an idea of how the value of a client has evolved over time is customer lifetime value CLV.
This also involves automating, enhancing, and integrating core business processes such as production, operations, sales, marketing, and finance, among others. The power of CRM lies in its adaptability to further the performance of any individual activity of the business, or even the entire business as a whole.
V. Kumar J. Andrew Petersen. Statistical Methods in. Customer. Relationship. Management
Apart from evaluating the value of customers, such an approach to CRM activities also provides a basis for the competitive advantage of a firm: By improving customer satisfaction, and customer loyalty, CRM helps firms acquire and retain profitable customers, and reactivate dormant customers. The ultimate goal of CRM is to maximize the lifetime value of each individual customer to the firm, thereby increasing firm profitability.
In this regard, most of the CRM initiatives can be attributed to one of the following four categories: Customer acquisition is the process of acquiring new customers, the foundation step of the whole CRM process. Customer retention is the process of keeping and developing relationships with the customers after the company acquires them. Customer churn, sometimes referred to as customer attrition, is the process of managing the rate of existing customers leaving a firm.
Customer win-back is the process of reacquiring the customers that have left a firm through customer churn. Now that we have reviewed the reason for adopting CRM practices, in the next section we will discuss the essential inputs needed for any CRM implementation. The implementation of a CRM strategy is an ongoing process of developing and executing a series of small projects aimed at satisfying the business needs and enhancing the value proposition to customers.
In this section, we focus on three essential ingredients needed to implement CRM strategies from a modeling perspective: Companies gather information to store, analyze, and make marketing decisions based on the results of data analysis. This section provides a basic overview of the categories of databases and the sources from which data can be collected.
This can be done according to firms main business function, information contents, underlying marketing activities, or database technology. As the focus of this book is on data modeling, we look at the following two types of databases in detail: This database refers to all the information associated with the transactions that customers have made. Examples of this type of information are: What transactions have the customers conducted?
What type of product was purchased? How frequent is this type of product purchased by the customer? How much was spent in the transaction?INTRODUCTION TO CUSTOMER RELATIONSHIP MANAGEMENT
This database is essentially a collection of information about a firm s customers. In general, the following information may be included in customer databases: Over a period of time, databases will begin to comprise prospects who have yet to be acquired, along with active and inactive customers. Information on prospects and active and inactive customers are useful to marketers and should be included in customer databases.
While data from active customers help marketers learn what has been done well, data from inactive customers help marketers to identify what needs to be improved, and data from prospects who were not acquired show the effectiveness of acquisition efforts and the type of customer the firm has a hard time acquiring. For inactive customers, the following additional information would be important to document: How long have the customers been inactive?
How long have they been active? What was their purchasing pattern when they were active? How were they initially acquired?
Why are they inactive? For prospects who were not acquired, the following information would be important to document: How much was spent on the prospects? Is the profile of the prospects that were not acquired different from the profile of prospects that were acquired?
What types of prospects should the company target in the future? Why did these prospects choose not to adopt?
Customer Relationship Management A Databased Approach
Sources of databases Managers acquire databases from two main sources: Primary data are original data collected firsthand by the focal firm that are not available or cannot be derived from any other sources. Primary data collection is usually conducted in-house in the forms of experiments or survey methods such as questionnaires, interviews, or observations.
Adapted from Aaker, D. On the other hand, secondary data are data that have already been made available or published in any form. There are two types of secondary data sources: Information from internal records is the primary information that the firm obtains directly from its daily business operations e.
This internal information usually comes from various departments within the firm, such as the internal marketing research department, sales analysis group, accounting department, or corporate strategic planning unit.
Information from external sources is the secondary information obtained from non-internal sources. There are three main external sources: These data are made available in either electronic or printed form from official sources such as government organizations, trade associations, periodicals, newspapers, books, annual reports, and private studies. Standardized sources of marketing data sources. Besides published data sources, managers can look at information available from a wide variety of sources from retail stores, warehouses, scanner-based systems, and so on that help provide the managers with a full picture of the market situation of a product category or brand.
The Internet is an important and significant source of secondary information. Given the rapid growth of social media activities, managers are interested in both official and non-official information obtained from customers activities on the Internet, such as customer feedback, reviews about the firm s products and services, etc. The use of databases for collecting, storing, and analyzing customer data has been crucial for innovations in the CRM process.
Nevertheless, technology improvements have been a key driver in making database innovations and other CRM processes accessible, user-friendly, and affordable for firms Technology An important factor that drives CRM development in its current stage is the rapid growth of technology.
CRM implementation thus has evolved into a user-friendly, flexible, low-cost, and high-tech process. In particular, the three main components of CRM technologies, namely, customer touch points, CRM applications, and data storage technology, have gone through significant improvements.
Customer touch points have moved away from the traditional face-to-face interaction between customers and salespeople. With the introduction of Voice over Internet Protocol VoIP technology, speech recognition technology, and social networking applications, interactions with customers can be in various forms of Web-based25 web sites, Facebook, Twitter, etc.
All these developments and enhancements have two key implications for CRM analysts in the area of modeling and data analysis. First, as more data become available, the ways of obtaining them have also increased tremendously. This has given rise to creative ways of collecting customer data and adding more data points about a particular customer, thereby creating a more complete picture of the customer.
Metrics help companies track and assess their performance and, more importantly, evaluate the returns on their CRM initiatives. In the process of implementing CRM, managers have to deal with a huge amount of data with the ultimate goal of evaluating managerial performances based on the value that each individual customer brings to the firm.
In order to record and quantify those evaluations, managers need a set of indicators that measure customer values. Metrics perform this role. The benefits of developing and using metrics are significant to companies. Some of the key benefits that accrue to the firm are: There are two broad categories of metrics, brand-level and customer-level.
Brand-level metrics are metrics that measure the brand s competitiveness in the market, such as market share, customer equity, sales growth, and so on. Customer-level metrics break down those brand-level metrics to the individual customer, such as acquisition cost per customer, size of wallet, and so on.
When combined, brand-level and customer-level metrics give managers a complete picture of how the firm or the brand fares in the market, as well as how its customer needs differ on an individual level, and how to leverage these differences to enhance the overall competitiveness of the firm.
At this stage, the table is meant to provide a general view of the types of CRM metrics available. In the subsequent chapters, we will delve further with detailed discussions about these metrics. Metric Definition Use of metric 1. Market share The percentage of a firm s sales to the sales of all firms in a given market 2. Sales growth The increase or decrease in sales volume or sale value in a given period compared to that in the previous period 3.
Customer Relationship Management A Databased Approach - ppt video online download
Acquisition The proportion of prospects converted to rate customers 4. Acquisition The acquisition spending of a focal firm per cost prospect acquired 5. Defection rate The average likelihood that a customer makes a repurchase from the focal firm in period t, given that this customer has purchased in the last period t 1 The average likelihood that a customer defects from the focal firm in period t, given that this customer has purchased in the last period t 1 7.
Survival rate The ratio of customers who continue to remain as customers survive until a period t from the beginning of observing these customers 8. Average lifetime duration The average duration customers continue to remain as customers 9. P-active The probability of a customer making a repurchase being active in a given period Win-back The ratio of acquisition of customers who rate had been lost in an earlier period Share-ofwallet The ratio of total sales of all customers of the focal firm in a product category to the total spending of those customers in the product category across all different firms Size of wallet The total spending of a customer on a product category across all different firms Metric Definition Use of metric Past customer The gross contribution of a customer when value adjusted for the time value of money Recency indicates the most recent purchase date of a customer Frequency measures how often a customer purchases from the firm Monetary value measures the average per transaction spending of a customer Customer The total discounted contribution margins lifetime value of a customer excess of recurring revenues over recurring costs to the focal Customer equity firm over a specific time period The total lifetime value of all customers of the focal firm Customer-level Customer-level Customer-level Brand-level The important thing for a company to remember is that determining which metric s to measure and manage should depend on how each metric relates to the desired short-term or long-term outcome.
If the metric s chosen cannot be quantifiably related to desired outcome measures such as profitability and shareholder value, the metric s are not generally worth measuring and managing. For example, if a firm wants to maximize CLV, one proven strategy is to optimally allocate the marketing resources to each customer. However, this would not be possible if there were no statistical model created to link marketing activities to CLV. In this book, we create many linkages through statistical models to help acquire, retain, and win back profitable customers as well as identifying customer propensity to churn.