Roshanak Haghighi

The Distribution of CRM Tags To Decentralized Call Center

  • My Role: lead UX Researcher & design
  • Team Size: 8 person
  • Completion Date: Aug 2023
  • Duration: 5 months
  • Status: Released

Non-disclosure agreement

Due to my NDA, I have avoided providing detailed information

The Objective

The primary objective of this project was to optimize and decentralize Divar’s call center operations by reassigning Customer Relationship Management (CRM) tags. This initiative aimed to:

  • Reduce operational costs by decreasing the volume of daily incoming calls.
  • Improve user satisfaction through more efficient and effective issue resolution.
  • Transfer user issues to relevant teams to ensure inquiries are handled by specialists in each area.
  • Build foundational infrastructure for advanced support systems like AI-driven Interactive Voice Response (IVR) and Smart Support.
Impact
  • The successful execution of this project led to substantial, measurable outcomes:
  • Reduced Daily Incoming Calls: Decreased from approximately 10,000 to 3,000 calls per day, significantly easing the workload on the call center staff.
  • Improved User Satisfaction: Enhanced efficiency in resolving user issues led to higher satisfaction rates.
  • Cost Savings: Lower operational costs due to decreased call volume and optimized processes.
  • Enabled Advanced Support Systems: Provided the essential groundwork for launching AI-driven solutions like a dynamic IVR system and Smart Support features.
Context

During my final six months at Divar, a leading online classifieds platform, the company underwent a strategic shift toward a thread-based model. This transition required decentralizing the entire call center to align support services with specific product threads.

At that time, the call center was overwhelmed, handling about 10,000 calls daily. Users frequently expressed dissatisfaction due to unresolved problems and inefficient routing of their inquiries. Additionally, the high volume of calls resulted in increased operational costs and strained resources.

Recognizing these challenges, I took the initiative to lead a comprehensive CRM tags distribution research project within the support team’s call center division. The goal was to reassign and optimize CRM tags to facilitate the decentralization process and address the pressing issues affecting both users and the company.

Challenge

The project presented several significant challenges:

  • High Call Volume: The call center was inundated with calls, making it difficult to provide timely and effective support.
  • Inefficient Tagging System: Over 1,000 CRM tags were in use, causing confusion and inefficiency in issue tracking and resolution.
  • Decentralization Needs: Transitioning to a thread-based model required that each thread have its own dedicated support capable of addressing specific user inquiries.
  • Stakeholder Alignment: Multiple departments, including customer support, operations, technical teams, and product management, had varying priorities that needed to be harmonized.
  • Urgency: The project needed to be executed swiftly to keep pace with the company’s strategic shifts.
Research Questions

Main Questions

  • How can we effectively reassign CRM tags to support the decentralization of the call center?
  • How can we define new CRM tags to establish a robust user problem reporting system, enabling each thread to proactively address user issues?

Sub Questions:

  • Which CRM tags are related to specific threads within the thread-based model?
  • Which CRM tags can be merged, and which tags should be split into multiple, more specific tags to better convey user problems?
  • Which CRM tags are associated with two or more threads, and how does this overlap impact issue resolution?
  • How can the redesigned tagging system facilitate the implementation of an intelligent chatbot to effectively answer user questions within the support team?
  • What strategies can we employ to maintain and update the CRM tagging system to adapt to future changes in user needs and company services?
Research Plan

To answer these questions, I developed a structured research plan that included collaborative methods and data-driven analysis.

1. Collaborative Categorization Method

I devised a collaborative categorization method inspired by the Delphi approach, aiming to gather expert opinions and reach a consensus among key stakeholders. This method was essential to ensure that diverse perspectives were considered, and the new system would meet the needs of all departments.

2. Stakeholder Engagement

I engaged key stakeholders from various departments: Included the Operational Excellence Manager, Customer Support Manager, CRM Manager, Contact Center QA Manager, UX Designer, Technical Team Leader, and Product Manager

Their insights were crucial in understanding the complexities of the existing system and the requirements for an effective tagging structure.

3. Structured Meetings

I facilitated structured meetings to:

  • Categorize Tags: Worked collaboratively to assign tags to the appropriate threads based on a predefined framework.
  • Consensus Building: Iterative discussions to align on tag assignments.
  • Reach Consensus: Encouraged open dialogue to resolve disagreements and ensure that all departments were aligned.
  • Reduce Unnecessary Tags: Aimed to simplify the system by eliminating redundant tags.
4. Data Collection and Analysis for Unsolved Tags
  • CRM Tag Review: Conducted a thorough review of over 1,000 existing CRM tags to assess their usage, relevance, and redundancy.
  • User Interaction Analysis: Listened to call recordings, examined sample user interactions, and evaluated tag frequency to identify common issues and patterns.
  • Identification of Redundancies: Analyzed data to pinpoint overlapping or unnecessary tags that could be consolidated or eliminated.
Action Plan
Phase 1: Preparation
  • Compiled Tag Inventory: Created a comprehensive list of existing CRM tags.
  • Developed Framework: Established criteria for tag reassignment aligned with the thread-based model.
Phase 2: Execution
  • Stakeholder Workshops: Conducted collaborative sessions to review and reassign tags.
  • Data-Driven Decisions: Used analytical insights to guide discussions.
Phase 3: Implementation
  • Reduced Tags from 1,000+ to 200: Streamlined the tagging system.
  • Updated CRM System: Implemented changes across all relevant platforms.
  • Training and Support: Provided guidance to customer support agents on the new system.
Result

The project achieved remarkable results:

  • Call Volume Reduction: Daily incoming calls decreased from 10,000 to 3,000, a 70% reduction.
  • Operational Cost Savings: Reduced call center costs due to lower call volumes and more efficient processes.
  • Improved User Satisfaction: Users experienced faster and more effective resolutions to their inquiries.
  • Enhanced Efficiency: Simplified tagging allowed support agents to quickly understand and address customer issues.
  • Foundation for Advanced Systems: The optimized tagging system became the backbone for:
    • Dynamic IVR System with AI Solutions: Launched an AI-driven IVR to improve call routing and offer self-service options.
    • Smart Support: Implemented advanced support features to provide intelligent assistance within each thread.
Key Learnings
  • 1. Effective Collaboration is Essential
  • Engaging stakeholders from diverse departments ensured a comprehensive understanding of the challenges and facilitated the development of a robust solution that met cross-functional needs.
  • 2. Data-Driven Approaches Yield Better Outcomes
  • Utilizing data analytics to inform decisions led to more accurate and effective solutions, as changes were based on evidence rather than assumptions.
  • 3. Simplification Enhances Efficiency
  • Reducing complexity in the CRM tagging system streamlined operations, making it easier for support agents to manage inquiries and for users to receive timely assistance.
  • 4. Leadership in Cross-Functional Teams
  • Leading a multidisciplinary team required clear communication, strategic vision, and the ability to navigate differing priorities, demonstrating the importance of strong leadership skills.
  • 5. User-Centric Focus Drives Satisfaction
  • Prioritizing the needs and experiences of users resulted in tangible improvements in satisfaction and loyalty, highlighting the value of a user-centric approach.