Problem Statement: Design a product strategy to increase the return on investment (ROI) for incoming leads at a technology company. Case Study: A technology company faced challenges in maximizing the ROI from their incoming leads. To address this, they implemented a comprehensive product strategy that involved optimizing lead conversion flow, integrating relevant applications, leveraging analytics, AI, and automation, and defining key metrics/KPIs to measure the effectiveness of the strategy. The company's data-driven approach and continuous improvement efforts resulted in a significant increase in lead ROI, driving business growth and success.

1. 1
Agenda
Problem Statement
Design a product strategy to increase incoming leads RoI.
Scope
Scope is confined to optimizing the lead conversion process and
maximizing the Return on Investment (RoI) for leads and opportunities.
The scope
Current Lead Conversion Flow
Proposed Product Strategy
Integration of Relevant
Applications
Implementation Plan
Key Metrics and KPIs Expected Benefits and ROI
Product Strategy to
increase the incoming
leads ROI
Goal
This presentation aims to propose a strategic approach to enhance the RoI
of incoming leads.

2. 2
Current Lead Conversion Flow
1. Lead
Generation
2. Lead
Qualification
3. Needs
Assessment
4. Solution
Proposal
8. Closing
and Handoff
7. Proposal/
Pricing
6.
Opportunity
Creation
5. Follow-up
and
Nurturing
Lead Conversion Flow
Existing Challenges
▪ Low Conversion Rates
▪ Lengthy Response Times
▪ Lack of Follow-up
▪ Ineffective Lead Qualification
▪ Insufficient Communication
▪ Inadequate Solution
Presentation
▪ Lack of Sales and Marketing
Alignment

3. 3
Proposed Product Strategy
Enhancing Incoming Leads RoI
Increase lead conversion rates and maximize the value generated from leads.
Key Elements of the Strategy
▪ Streamlined Lead Qualification
▪ Personalized Solution Approach
▪ Accelerated Follow-up and Nurturing
▪ Seamless Integration of Applications
▪ Data-driven Decision Making
Assumptions Made
▪ Leads meet qualification criteria.
▪ Personalized solutions resonate.
▪ Prompt follow-up drives engagement.
▪ Smooth application integration enhances
workflow.
▪ Data-driven decisions optimize the process.

4. 4
Integration of Relevant Applications
01
Importance of Application Integration in Lead Conversion Flow
▪ Seamless integration of applications can enhance efficiency, effectiveness, and
overall productivity in the lead conversion process.
▪ Integrating applications allows for streamlined data flow, improved communication,
and automation of repetitive tasks.
02
Custom and Off-the-Shelf Applications
▪ Custom applications tailored to company’s needs provide unique functionalities,
flexibility, and scalability to address their challenges and processes.
▪ Off-the-shelf applications enhance lead conversion with proven functionalities,
integrations, and cost savings.
03
Examples of Applications that can be Integrated
▪ Customer Relationship Management (CRM)
▪ Marketing Automation Tools
▪ Communication and Collaboration Tools
▪ Analytics and Reporting Tools
▪ Lead Generation and Tracking Tools

5. 5
Analytics, AI, and Automation
The Role of Analytics, AI, and Automation in Lead
Conversion
▪ Analytics, AI, and automation technologies play a crucial
role in optimizing lead conversion rates and driving
efficiency in the process.
▪ They provide valuable insights, enable personalized
engagement, automate tasks, and enhance decision-
making.
Examples of Analytics, AI, or Automation
Techniques
▪ Lead Scoring: Use analytics and AI to score leads
based on attributes, activities, and engagement,
prioritizing high-value leads for attention.
▪ Chatbots: Use AI chatbots to engage leads, answer
queries, and provide personalized recommendations,
enhancing the customer experience and response
times.
▪ Workflow Automation: Implement automation
workflows to trigger actions based on lead
interactions, ensuring timely follow-ups and reducing
manual effort.
▪ Predictive Analytics: Leverage predictive modeling
and machine learning to forecast lead behavior,
identify churn risks and increase conversion rates.
▪ A/B Testing: Utilize analytics for A/B testing to
optimize conversion rates through data-driven
optimizations.
Leveraging Analytics, AI, and Automation for
Lead Conversion
▪ Analytics: Use analytics and AI to score leads based
on attributes, activities, and engagement, prioritizing
high-value leads for attention.
▪ Artificial Intelligence (AI): Harness AI and predictive
modeling to segment leads, personalize interactions,
and improve targeting for higher conversion rates.
▪ Automation: Implement automation to streamline
tasks, and follow-ups and nurture leads with timely
and relevant communications, ensuring consistent
engagement.

6. 6
Implementation Plan - Phase-wise Roadmap
01
02
03
04
05
06
Analytics and Automation Integration
▪ Implement analytics for lead insights.
▪ Deploy AI for automated lead scoring and
segmentation.
▪ Integrate automation for streamlined
workflows.
Training and Deployment
▪ Train team on new tools, technologies, and
workflows.
▪ Develop training materials and
documentation.
▪ Roll out updated lead conversion flow to the
team.
Testing and Refinement
▪ Test implemented solutions and workflows.
▪ Collect user and stakeholder feedback.
▪ Refine the system based on feedback and evaluations.
Monitoring and Optimization
▪ Monitor metrics to evaluate effectiveness.
▪ Analyze data for adjustments and
optimizations.
▪ Review and update strategy based on
market trends.
Assessment and Preparation
▪ Assess current lead conversion flow.
▪ Identify pain points and bottlenecks.
▪ Gather stakeholder feedback.
▪ Allocate resources and assemble the
implementation team.
Solution Design and Development
▪ Define app requirements or select off-the-shelf
solutions.
▪ Develop integrations and workflows for lead conversion
enhancement.
▪ Customize applications to align with the company's
needs.

7. 7
Key Metrics and KPIs
01
02
03
06
05
04
10
07
09
08
Sales Revenue
Track the total revenue generated from the
converted leads.
Average Deal Size
Assess the average value of closed deals.
Time to Conversion
Measure the duration it takes to convert a lead
into an opportunity or customer.
Lead-to-Opportunity Ratio
Monitor the ratio of leads that convert into
opportunities.
Lead Conversion Rate
Measure the percentage of leads successfully
converted into opportunities or customers.
Lead Velocity
Track the speed at which leads progress
through the conversion process.
Lead Quality
Assess the quality of leads based on
predefined criteria.
Cost per Acquisition (CPA)
Monitor the cost incurred to acquire each lead.
Conversion Time by Stage
Track the time taken for leads to move through
each stage of the conversion process.
Return on Investment (RoI)
Evaluate the ratio of revenue generated to the
cost invested in lead generation efforts.
Evaluating Strategy
Effectiveness
These metrics provide insights
into lead conversion performance
and help identify areas for
improvement in increasing
incoming leads RoI.

8. 8
Expected Benefits and ROI
01 03 05
02 04 06
Increased lead conversion rates
Implementation of the strategy aims to
increase conversion rates, leading to
more opportunities and customers.
Enhanced revenue generation
The strategy drives increased sales
revenue for the company by improving
lead-to-customer conversion.
Improved ROI
Quantify expected leads RoI increase by
comparing revenue gains with
implementation investment.
Return on Investment (ROI)
calculation
Demonstrate strategy value for the
company with ROI calculation based on
revenue increase and implementation
cost.
Cost savings
Optimizing lead conversion helps the
company to reduce acquisition costs and
achieve cost savings.
Cost-benefit analysis
Present a detailed analysis of strategy
costs and anticipated revenue growth
and ROI.

9. 9
Assumptions
Assumes seamless integration with existing
systems and infrastructure.
Compatibility of Integrated Applications
Assumes easy access and suitability of analytics,
AI, and automation technologies.
Accessibility and Suitability of Technologies
Assumes a stable target
audience throughout the
strategy implementation.
Consistent Target Audience
Assumes projections based
on realistic market
expectations.
Realistic Revenue Gains
and Cost Savings
Assumes the team has the
necessary skills and resources
for effective execution.
Adequate Implementation
Team Resources
Assumes metrics align with industry standards
for accurate evaluation.
Alignment with Industry Best Practices
Assumes a feasible timeline
within given constraints..
Reasonable and Achievable
Timeline

10. Challenges and Mitigation
Challenges/Risks
Mitigation Steps
▪ Thorough planning and testing
of integration processes.
▪ Comprehensive training
programs for team members.
▪ Implementation of robust data
privacy and security measures.
▪ Effective change management
strategies, including
communication and stakeholder
involvement.
▪ Integration complexities: Ensuring
seamless integration of relevant
applications.
▪ Adoption and training: Ensuring team
members are equipped with the
necessary skills and knowledge.
▪ Data privacy and security: Safeguarding
sensitive customer data throughout the
process.
▪ Change management: Overcoming
resistance to change and ensuring a
smooth transition.

11. 11
Conclusion
01 02 03 04 05
Recap
We explored a comprehensive
product strategy to increase
incoming leads RoI at Data
Axle.
Strategy Highlights
The proposed strategy focuses
on streamlined lead
qualification, personalized
solution approach, accelerated
follow-up and nurturing,
seamless application
integration, and data-driven
decision-making.
Benefits
By implementing this strategy,
Data Axle can expect improved
lead conversion rates, higher
revenue, and reduced
acquisition costs.
Alignment
The strategy aligns with Data
Axle's objectives to drive
growth and optimize lead
conversion performance.
Next Steps
We encourage further
discussion, questions, and
collaboration to refine and
implement the strategy
effectively.

12. Q&A and Feedback
16+ years | Product Management | Entrepreneurship | Marketing | Strategy
|Operations | Technology | Digital Transformation | Program Management
Prasanna Hegde