Unit 2: CRM and marketing automation
Digital Analytics, AI and Marketing Automation notes · PTU syllabus (MBA 974-26)
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Unit summary
CRM and automation turn customer data into timely, personalised communication at scale. This unit covers CRM systems and customer lifecycle management, segmentation and personalisation, predictive customer analysis, email and marketing automation systems, chatbot applications, and CRM integration with digital marketing platforms.
After this unit you can
- Explain CRM systems and customer lifecycle management
- Apply segmentation, personalisation and predictive customer analysis
- Explain email and marketing automation and chatbots
- Integrate CRM with digital marketing platforms
PTU syllabus topics
- CRM systems and customer lifecycle management
- segmentation and personalization
- predictive customer analysis
- email and marketing automation systems
- chatbot applications
- CRM integration with digital marketing platforms
- 1. Acquire:
- 2. Onboard:
- 3. Engage: Personalised campaigns
- 4. Retain: Loyalty, service
- 5. Win back: Re-engagement
Topic 1
CRM systems
- CRM: strategy and technology to manage customer relationships and data across touchpoints.
- Functions: contact and lead management, sales pipeline, marketing automation, customer service tickets, analytics and segmentation.
- Tools: Salesforce, HubSpot, Zoho CRM, Microsoft Dynamics.
- Benefits: single customer view, personalised communication, better retention, measurable ROI.
Topic 2
Customer lifecycle management
- 1. Reach: Awareness
- 2. Acquisition: First purchase or sign-up
- 3. Onboarding: First experience
- 4. Engagement and growth: Repeat purchase, cross-sell, upsell
- 5. Retention: Loyalty programmes, service
- 6. Win-back: Re-engaging lapsed customers
- Metrics: CAC, conversion rate, average order value, repeat rate, churn rate, CLV.
Topic 3
Segmentation and personalisation
- Segmentation: demographic, behavioural (RFM — recency, frequency, monetary), lifecycle stage, value tier, preferences.
- Personalisation: tailored content, offers, recommendations, timing and channel for each segment or individual — dynamic emails, website personalisation, app push notifications.
Topic 4
Predictive customer analysis
- Models: churn prediction, purchase propensity, next-best offer, CLV prediction, lead scoring.
- Techniques: logistic regression, decision trees, gradient boosting, survival analysis.
Example
A telecom operator scores customers monthly on churn risk; those above 70% receive retention offers, cutting churn by several percentage points.
Topic 5
Email and marketing automation systems
Marketing automation uses software to automate repetitive marketing tasks and personalised customer journeys.
- 1
Trigger
Sign-up, download, cart abandonment
- 2
Segment
Based on profile and behaviour
- 3
Send personalised content
Email, SMS, WhatsApp, push
- 4
Score leads
Engagement-based points
- 5
Hand over to sales or offer
When score crosses a threshold
- 6
Measure and optimise
- Features: workflows, lead scoring, dynamic content, A/B testing, multichannel campaigns, CRM integration, reporting.
- Tools: HubSpot, Marketo, Salesforce Marketing Cloud, Zoho, MoEngage, WebEngage, CleverTap (Indian martech firms).
Topic 6
Chatbot applications
- Chatbots: rule-based (menu flows) or AI-powered (natural language) assistants on websites, apps and WhatsApp.
- Uses: 24×7 customer service, FAQs, order tracking, lead qualification, product recommendations, appointment booking.
- Integration: connect with CRM, order and payment systems; hand over to a human agent for complex issues; track resolution rate and satisfaction.
Topic 7
CRM integration with digital marketing platforms
- Integrations: website forms and landing pages to CRM, ad platforms (custom audiences, offline conversion uploads), email and SMS tools, social media and WhatsApp Business API, e-commerce platforms, customer data platforms (CDPs).
- Benefits: single customer view, closed-loop measurement (from ad click to sale), consistent personalisation across channels.
Key terms
- Customer lifecycle
- Stages of a customer's relationship with a brand
- RFM
- Recency, frequency, monetary segmentation
- Propensity model
- Predicts likelihood of an action
- Marketing automation
- Software-driven, triggered marketing communication
- Customer data platform
- System unifying customer data across sources
Quick revision
- CRM functions and tools.
- Lifecycle stages and metrics.
- Segmentation (RFM) and personalisation.
- Churn, propensity, CLV models.
- Automation workflows; chatbots; CRM integrations and CDPs.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.What is CRM?
- Q2.Name the stages of the customer lifecycle.
- Q3.What is RFM segmentation?
- Q4.Give two examples of predictive customer models.
- Q5.State two uses of chatbots.
- Q6.What is a customer data platform?
Long-answer questions
- Q1.Explain CRM systems and customer lifecycle management.
- Q2.Discuss segmentation, personalisation and predictive customer analysis.
- Q3.Explain email and marketing automation systems and chatbot applications.
- Q4.Explain the integration of CRM with digital marketing platforms.
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