CRM Important notions

CRM Key concepts

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CRM Important notions por Mind Map: CRM Important notions

1. Privacy and Ethics Considerations

1.1. Organizations have definitive or implied responsibility to adhere to a person’s privacy request

1.1.1. Be compliant with current and pending legislation Understand and meet or exceed customer and prospect privacy and ethics expectations Audit opt-in and opt-out practices Verify that the organization infrastructure supports respective privacy initiatives

1.1.1.1. Europe for example has a set of privacy regulations called GDPR - General Data Protection Regulation-

2. Definition: the customer journey spans a variety of touchpoints by which the customer moves from awareness to engagement and purchase Customer journey is the visualization of customers’ objectives, needs, feelings and barriers throughout the path to purchase for a product, service or brand

3. Companies that engage customers via social media are practicing social CRM

3.1. for example: Social media manager Online community manager Manager of multichannel marketing

3.2. Acquires new customers Provides a new channel perfectly attuned to increasing customer retention Wins them back should they defect

4. Session 1 to 4 - Terminology and theory

4.1. Important concepts (suite)

4.1.1. CLV

4.1.2. SLTV

4.1.3. Analytics maturity model

4.1.3.1. Descriptive

4.1.3.2. Diagnostic

4.1.3.3. Predictive

4.1.3.4. Prescriptive

4.1.4. The CRM discipline has 3 components -- slide 16 -- session 3

4.1.4.1. Strategic

4.1.4.2. Analytical

4.1.4.2.1. RFM

4.1.4.2.2. Segmentation

4.1.4.3. Operational

4.1.4.3.1. SFA

4.1.4.3.2. Service automation

4.1.4.3.3. Marketing automation

4.1.5. The CRM GOAL is to identify and attract profitable customers

4.1.5.1. A company should make its goal to attract the greatest number of profitable customers

4.1.5.1.1. CRM is founded on four tenets: Customers should be managed as important assets Not all customers are equally desirable Customers vary in their needs, preferences, and buying behavior By better understanding their customers, companies can tailor their offerings to maximize overall value

4.1.5.2. Pareto rule 20/80

4.1.5.3. Some goals of the CRM

4.1.5.3.1. Developing customers Cross-selling Upselling Managing migration

4.1.5.3.2. Servicing Retaining Increasing loyalty Winning back defectors

4.1.5.3.3. Identifying prospects Acquiring customers

4.1.6. Data warehouses

4.1.6.1. Contains many datamarts

4.1.7. The customer journey -- slide 52-- session 3

4.1.7.1. The notion of 'persona'

4.1.8. Enterprise Resource Planning (ERP) automates a company’s system integration through a software application. Manages the resources of the company

4.1.9. Why some systems fail Inadequate support from top management No CRM champion within the company Inadequate financial commitment Supply-chain partners not included No specification regarding who owns data Poor-quality data Technology the focus instead of customer Performance metrics not established Lack of change-management initiatives Employees not “sold” on customer-centric focus

4.2. Factors that gave birth to CRM

4.2.1. Service dominant logic

4.2.2. Traditional marketing silo mindset

4.2.3. B2B Culture, industrial marketing

4.2.4. Standards culture and total quality

4.2.4.1. ISO 9001

4.2.4.2. ISO 14001

4.2.4.3. OHSAS 18001

4.2.5. Supply chain culture of just in time

4.3. Theoretical models

4.3.1. The six market models

4.3.1.1. Internal markets

4.3.1.2. Referral markets

4.3.1.3. Influence markets

4.3.1.4. Recruitment markets

4.3.1.5. Supplier and alliance markets

4.3.2. Benefits added by a relationship

4.3.2.1. Meeting customer requirements

4.3.2.1.1. Personalization

4.3.2.1.2. Postponment

4.3.2.1.3. Bespoke

4.3.2.2. The personal touch

4.3.2.2.1. Personal service

4.3.2.3. Trust and belonging

4.3.2.3.1. Formal network: Sports Clubs Working Men’s Clubs Church Groups Professional Associations -Social Clubs and Societies -Alumni Groups -Rotarians -Freemasonry

4.3.2.3.2. Informal network Friends Family Neighbours Colleagues

4.3.2.3.3. Cultural network -Ethnic Background -Religion -Nationality -Language -Social Class

4.3.3. Share of wallet

4.4. Implementing CRM, dimensions to consider

4.4.1. Multiple dimensions People dimension Business dimension Technological dimension Time dimension New executive roles underline strategic importance Chief Data Officer (CDO)—owns data governance Chief Analytics Officer (CAO) Chief Customer Officer (CCO) + Chief Service Officer (CSO) Chief Internet of Things Officer (CIoTO)

4.4.1.1. People dimension

4.4.1.1.1. Training and culture

4.4.1.2. Size

4.4.1.2.1. Big or small company advantages - see session 4

4.4.1.3. Type of structures

4.4.1.3.1. Functional (silo)

4.4.1.3.2. Geographic structure

4.4.1.3.3. Account management

4.4.1.3.4. Organization by industry

4.4.1.3.5. Matrix

4.4.2. Additional terminology

4.4.2.1. OEM

4.4.2.2. SaaS software as a service

4.4.2.3. Scalability (the capacity of the technological system to grow with time and needs )

4.4.2.4. POC = proof of concept

5. Session 9: Social CRM

5.1. Social media An online mass collaboration environment where content is created, posted, enhanced, discovered, consumed, and shared, participant to participant, without a direct intermediary

5.2. CRM : Trends, Challenges and Opportunities

5.2.1. New organization positions created to improve customer knowledge gathering

5.2.2. Existing organization positions are changing with more focus on data analytics

5.2.3. Better technology

5.2.3.1. Advances in processing power Increased communication bandwidths

5.2.3.2. Real-Time Data Analysis

5.2.4. New techonologies

5.2.4.1. Artificial Intelligence

5.2.4.1.1. For example: Intelligent virtual agents (IVAs) increase personalization interactions

5.2.4.2. RFID

5.2.4.3. Augmented Reality

5.2.4.3.1. Mobile devices used by consumer to download relative data into smart applications for their own analysis and use

5.2.4.4. Biometric technologies Study brain-wave responses to ads, brand names, and car designs

5.2.4.5. Network analysis Analyze social network sites to capture mood swings of the nation and predict changes

5.2.4.6. Crowdsensing Study how behavior and ideas spread through social networks

5.2.4.7. Crowdsourcing Study customer participation online in contributing to to a company’s marketing efforts

6. Session 8 CRM performance measurement

6.1. We have 3 CRM effectiveness measures: A- Basic Measures: Service Quality, Customer Satisfaction and Loyalty, and Retention B- The CRM Customer-Cycle Measures: Acquisition, Retention, and Win-Back C- Measures of Customer Value and customer Equity

6.1.1. A- Basic Measures: Service Quality, Customer Satisfaction and Loyalty, and Retention

6.1.1.1. 1- To measure Service quality, we use for example SERVQUAL SCALE (Parasuraman, Ziethaml and Berry 1988) Composed of two matched sets of 22 questions describing expectations for a particular service category and service provider

6.1.1.2. 2- Satisfaction and Loyalty can me measured via the (RFM) score

6.1.1.2.1. Recency: the date of the most recent customer transaction Frequency: the number of customer transactions with the organization within a specific period of time Monetary: the amount spent within the same specific time period used A score of 551 means a customer who bought recently (5), frequently (5), small monetary values (1) -the order is important- Best customers have a ranking of 555 Worst customers have a ranking of 111

6.1.1.3. Retention and churn rates

6.1.2. B- The CRM Customer-Cycle Measures: Acquisition, Retention, and Win-Back

6.1.2.1. 1- Acquisition Necessary to acquire new customers in order to feed a pipeline that is losing customers through attrition and defection

6.1.2.1.1. Various indicators can be used! Some examples are available on the slides (you don't have to memorize them because these are simply examples of possible indicators)

6.1.2.2. 2- Retention

6.1.2.2.1. Various indicators can be used! Some examples are available on the slides (you don't have to memorize them because these are simply examples of possible indicators)

6.1.2.2.2. Size of wallet: the total amount of a buyer’s spending in a category Share of wallet: the percentage of the total expenditures in a category that an individual store or brand satisfies

6.1.2.3. 3-Defection and Win-back Indicators

6.1.2.3.1. Various indicators can be used! Some examples are available on the slides (you don't have to memorize them because these are simply examples of possible indicators)

6.1.3. C- Measures of Customer Value and customer Equity

6.1.3.1. Customer lifetime value CLV is a measure of the future financial value of the customer’s purchases with an organization

6.1.3.2. Customer equity: equity value is the value of a company available to owners or shareholders

7. Session 7 CRM strategy and profit cycle

7.1. 3 strategies

7.1.1. Acquisition

7.1.1.1. Aimed at prospects, not customers

7.1.1.2. Companies mine databases to identify the types of prospects who are likely to respond to acquisition efforts and become customers

7.1.1.3. Good practices

7.1.1.3.1. Eliminate switching costs

7.1.1.3.2. Develop acquisition program through qualitative and quantitative marketing research

7.1.1.3.3. Present the offer at an appropriate time in life cycle

7.1.1.3.4. Encourage positive word-of-mouth referrals

7.1.2. Retention

7.1.2.1. Customer equity is more dependent on customer retention than customer acquisition. (Customer equity is the total combined Customer Lifetime Value (CLV) of all of a company's customers. )

7.1.2.2. Good practices

7.1.2.2.1. Programmatic (automated) bonds Rewards programs and procedures that make it difficult for customers to switch providers

7.1.2.2.2. Humanistic bonds The treatment given to customers by highly trained personnel

7.1.2.2.3. Identify Moments of truth (these are critical moments where the company can’t afford a service failure)

7.1.2.2.4. Rewarding The company offers tangible benefits to its regular customers

7.1.2.2.5. Offer

7.1.2.2.6. Implement

7.1.3. Win-back

7.1.3.1. Companies need to concentrate more on retaining customers through CRM than attracting only new customers

7.1.3.1.1. Based on defection analysis, to identify why customers leave

7.2. Tiered servicing structures allow users to select from a small set of tiers at progressively increasing price points to receive the product or products best suited to their needs. Many applications exist for the internet, transportation and software industries.

7.2.1. Tiered servicing and pricing allows companies to charge differing amounts for different levels of servicing.

7.3. Focus on attractive customers. Pareto Principle. The top 20% of customers account for 80% of profits

7.4. Customer-Company (service) Profit Chain

7.4.1. The Service-Profit Chain is a theory and business model indicating a virtuous circle where quality leads to customer satisfaction. This in turn leads to customer loyalty … in particular, customer retention. This leads to increases in revenue and profit. Profit and growth are stimulated primarily by customer loyalty.

7.4.1.1. See slide 19

7.4.2. Satisfaction makes a difference in maintaining and developing customer relationships, and through better service would come higher profits

7.4.2.1. Dissatisfied customers share their bad experiences more often than satisfied customers share their positive experiences

7.4.2.2. is the consumer’s response to, and evaluation of, the perceived discrepancy between prior expectations (or some other norm of performance) and the actual performance of the product as perceived after its consumption

7.4.2.3. Satisfaction is the difference between expectations and current experiences. If service rendered exceeds what was expected, the consumer is satisfied If service rendered is below what was expected, the consumer is dissatisfied

7.4.2.3.1. Expectancy confirmation/disconfirmation model of satisfaction by Oliver (1977, 1980)

7.4.2.4. We distinguish between 2 types of satisfaction

7.4.2.4.1. Overall (cumulative) satisfaction = measures of service quality are more useful in determining the effectiveness of customer retention efforts Transaction-specific satisfaction = measures are more useful in determining the effectiveness of training or other quality improvement efforts

7.4.3. The 3 types of loyalty

7.4.3.1. Behavioral loyalty relies on a customer’s actual conduct, regardless of the attitudes and preferences that underlie that conduct Affect loyalty determined by looking at what is purchased and also by looking at a person’s “liking” and “preference” of the brand This is the most reliable type of loyalty of companies Situation-specific loyalty the customer may forgo purchasing a brand they like and prefer because of another brand’s promotion or availability

7.4.4. Loyalty Programs The extent to which a retailer offers tangible benefits such as pricing or gift incentives to its regular customers in return for their loyalty

7.4.4.1. frequent flyer programs customer loyalty bonuses free gifts personalized cents-off coupons other point-for-benefit “clubs”

7.4.4.1.1. Reasons for popularity: Provide companies with barriers to exit for current customers May move a company from an awareness set in a consumer’s mind to a consideration or choice set Provide members with financial incentives Structured to encourage positive word of mouth and offer incentives for bringing in friends and family Used to create a database and collect data Enable companies to obtain a greater share of wallet because members may consolidate their purchases with the company in order to earn greater rewards

8. Session 5 and 6 - Technology landscape and analytics

8.1. Definition: customer experience ( AKA CX) is the set of interactions between the customer and brand’s touchpoints (store, website, social media platform, sales force, call center, product…) that are supposed to generate a reaction or emotion

8.2. The type of channel interactions

8.2.1. Single channel

8.2.2. Multi-channel is a customer experience during which customers use one or more different contact points with a brand (physical store, smartphone, tablet, live chat, emails, social networks, messaging apps). These touch points are offered by the brand throughout the customer journey.

8.2.3. Cross-channel is a customer experience offered across all channels. In this case, all channels are complementary throughout the different stages of the customer journey. Each channel is deployed in connection with other channels to provide a smooth customer experience. Cross-channel is the next level up from multi-channel.

8.2.4. Omni-channel takes the notion of ubiquity into account: customers can use different channels at the same time (they can use their mobile while they are in a physical store). It suggests an even greater consistency between channels as customers navigate seamlessly from one to another.

8.3. Disparate databases (SQL-NOSQL)

8.4. Customer Data Integration CDI

8.4.1. A data management process where all customer and prospect data is consolidated to create a single accurate view of the customer

8.4.2. A persona in marketing is a fictional character created to represent a user type that might use a site, brand, or product in a similar way.

8.5. Data latency

8.6. Big data Term used to describe the combining of data with a process

8.6.1. Data can be structured or unstructured Structured—relational with defined variables Unstructured—streaming data (e.g. mobile, GEO apps)

8.6.2. Four “V’s”—velocity, variety, volume, veracity

8.7. Technology and Data Platforms

8.7.1. Data lakes Data captured and stored in native format

8.7.2. Geofencing is a location-based service in which an app cellular data to trigger a pre-programmed action when a mobile device enters or exits a virtual boundary set up around a geographical location.

8.7.3. Real-time bidding (RTB)

8.7.3.1. Advertisers bid in real-time on ads to be placed and distributed in a publication, app, feed, network or other media of your choosing.

8.7.4. Retargeting

8.7.4.1. Retargeting is one marketing strategy within a larger practice called programmatic advertising. Programmatic advertising refers to buying and selling available ad spaces, or inventory, online. Today, programmatic advertising is typically bought through real-time bidding (RTB).

8.7.5. Database marketing Sophisticated data collection and management used to promote dialogue with “push” and “pull” strategy Push: promote product (traditional approach) , the company uses emailing most of the time Pull: attract the leads (modern approach, the company attracts the customers via content marketing (white papers, infographics, etc))

8.7.5.1. Programs supported by statistical models

8.7.6. Focus on 2 analytical methods

8.7.6.1. unstructured data (text)

8.7.6.1.1. 1- Sentiment analysis refers to the use of natural language processing (NLP), text analysis, computational linguistics to systematically identify, extract, quantify, and study affective states and subjective information

8.7.6.2. structured data

8.7.6.2.1. 2- Segmentation: Segmentation is the process of categorizing customers into groups (a.k.a. segments, clusters)… …So that customers within a segment are similar enough to be treated similarly (economies of scale, coherence), yet different enough from customers in other segments (worthy of differenciation).

8.7.7. Types of data storage

8.7.7.1. Operational data store (ODS) Designed to contain limited amount of information used for current marketing activity Quick data trivial capability

8.7.7.2. Data marts (DM) Subsets of data warehouse

8.7.7.3. Data warehouse (DW) Designed as a repository for all customer, prospect, product/service, and related marketing information

8.7.8. ISO 27001 (standard for systems and data security)

8.7.9. Technology landscape

8.7.9.1. Cloud computing technology Essential characteristics On-demand self-service Resource pooling (multiple customers) Rapid scaling Measured service

8.7.9.1.1. 3 service models

8.7.9.1.2. 3 cloud types

8.7.9.2. Virtualization is technology that allows you to create multiple simulated environments or dedicated resources from a single, physical hardware system.

8.7.9.2.1. A thin client is a computer that runs from resources stored on a central server instead of a localized hard drive. Thin clients work by connecting remotely to a server-based computing environment.

8.7.9.3. Other technologies

8.7.9.3.1. Radio Frequency Identification (RFID) Uses radio waves to communicate between two objects

8.7.9.3.2. Internet of Things (IoT) Devices embedded with computer chips or sensors, which are connected to the internet

8.7.9.3.3. In store beacons (Beacons are small, wireless transmitters that use low-energy Bluetooth technology to send signals to other smart devices nearby)

8.7.9.3.4. Optical Character Recognition. It is a widespread technology to recognize text inside images, such as scanned documents and photos

8.7.9.3.5. Robotic Process Automation (RPA) enables you with tools to create your own software robots to automate any business process. Your "bots" are configurable software set up to perform the tasks you assign and control. RPA bots can learn.

8.7.9.3.6. Process mining is a family of techniques in the field of process management that support the analysis of business processes based on event logs.

8.7.9.3.7. Computer telephony (CT)

8.7.9.4. Social media

8.7.9.4.1. Most applications are single-point solutions Solves one business problem

8.7.9.4.2. ATAWAD: is an acronym for “anytime, anywhere, any device”

8.7.9.4.3. Examples of social media usage and integration with CRM

8.8. Database and Customer Data Development

8.8.1. Types of data

8.8.1.1. Primary data Acquired from the original source Secondary data Acquired from some party other than the party from which the data represents Derived data Information created from other data Individual data Attributed to a specific person Household data View of data from a household perspective

8.8.1.2. Real-time versus batch data processing: Marketers need data to be captured and disseminated at different situations Data captured may need to be processed and action taken as soon as possible

8.8.1.3. Convert data into information (ETL)

8.8.1.3.1. Data Transformation -- Extract Transform Load