Helpdesk Ticketing Satisfaction Report

@emilesd617

Hi, I am a data analyst with 8 years of rich experience with a background in BI reporting and dashboards. I am familiar with SQL, Power BI, Excel, Data Analysis, Data Visualization. For this project, the most important part is transforming raw ticket data into clear satisfaction metrics. This helps identify issues in response time, resolution quality, and agent performance quickly. I will focus on building a simple dashboard with accurate KPIs, trend charts, and easy-to-read insights for managers. I'm an individual freelancer and can work on any time zone you want. Please contact me with the best time for you to have a quick chat. Looking forward to discussing more details. Thanks. Emile.

@vw1514518vw

The soultion will be a scalable Incident management database to log and categorize incidents, response, status and basic reporting for administartion follow up and a knowledge database for tech people to share their knowledge, spot and suggest best fixes for identical issues for faster, better and educated response. Optional adavanced module for insightful custom reports for analysis, development, aligning and decisions making. Starting with windows desktop MS Access database application, scalable to multiuser front end standalone exe with backend SQL database of a your choice from MS Access to SQL server. Cheers.

@nareshk44

As a seasoned data analyst with profound skills in utilizing Excel, Power BI, Tableau, and SQL‐based dashboards, I am well-equipped to transform your ticketing system data into actionable insights. Your request for trend charts, scorecards, and a summary narrative will be met with aplomb as it reflects my keenness on delivering reports that are easily comprehensible to even the most non-technical of individuals. In regard to the specific satisfaction drivers, response time, resolution quality, and agent professionalism, I can design elaborate metrics that assess those parameters effectively. My expertise in aggregating and calculating data, such as SLAs met and CSAT scores for instance, using Excel functions ensures both accuracy and efficiency in the process. For a clearer understanding of my plans, I will generate a sample layout for you to confirm before building the full report. Additionally, my broad background in office management and administration encompasses extensive experience in data entry and analysis, PDF design and editing as well as MS PowerPoint presentation creation - all complementing my report writing skills. Looking forward to being part of your team and contributing towards improving your IT help desk performance by presenting you with insightful reports as evidence of Naresh's commitment to quality service delivery.

@DevDataAnalyst

Hi there! ? I’ve spent the last 10+ years helping businesses make sense of their data — turning numbers and reports into clear, visual stories that drive smarter decisions. My expertise includes Power BI, Tableau (Desktop & Server), R, SQL Server, and KNIME for data prep and automation. Whether it’s building a simple KPI dashboard or a full-scale analytics solution, I focus on making your data work for you — easy to understand, easy to use, and built around your goals. If you’re looking for someone who blends technical skill with a business mindset, let’s connect and discuss how I can help bring your data to life.

@ShivaniGoyalsai

Hi I have 15+ years of experience in Business Intelligence and expertise in BI tool such as power BI, Tableau and Birst.I can help you turn your help desk data into a clear, actionable satisfaction report that leadership can easily understand and use for decision-making. I’ll connect to your ticketing data (Excel/SQL/API export) and build a clean dashboard (Power BI or Excel—your choice) focused on your three key drivers: response time, resolution quality, and agent professionalism. As an expert I will provide end to end soluiton from data connection to building interactive dashbaords. if interested, we can connect and get started. Thanks Shivani

@vishal1145

Your ticketing system is collecting satisfaction signals, but without proper segmentation you're flying blind on which agents or ticket categories are dragging down your CSAT scores. If response time looks good on average but 20% of tickets are breaching SLA by 3+ hours, that minority is poisoning your overall satisfaction metrics. Before I design the dashboard, I need clarity on two things: Does your ticketing platform expose API endpoints or direct database access for real-time refresh, or will this be a daily CSV export? And what's your threshold definition for "resolution quality" - are you tracking reopen rates, first-contact resolution, or post-closure survey scores? Here's the analytical approach: - POWER BI + SQL: Build a star schema connecting ticket metadata, agent performance, and CSAT responses with drill-through filters by department, priority level, and time period to isolate underperforming segments. - RESPONSE TIME ANALYTICS: Calculate P50, P90, and P99 percentiles (not just averages) to surface outlier tickets that skew perception, then overlay SLA breach rates with heatmaps showing peak failure windows. - RESOLUTION QUALITY SCORING: Track first-contact resolution percentage, ticket reopen rates within 7 days, and average closure survey ratings with conditional formatting that flags agents below 4.0/5.0. - AGENT PROFESSIONALISM METRICS: Parse free-text feedback using sentiment tagging (positive/neutral/negative keywords) and cross-reference with individual agent CSAT trends to identify coaching opportunities. - EXECUTIVE SCORECARD: Single-page view with KPI cards (avg response time, resolution rate, overall CSAT), 12-week trend lines, and a top-5/bottom-5 agent leaderboard that auto-refreshes on data source update. I've built similar BI dashboards for 4 enterprise service desks where we reduced average resolution time by 35% just by surfacing which ticket types were consistently missing SLA. Let's schedule a 15-minute call to review your ticketing schema and confirm the refresh cadence before I mock up the layout.

@AITSoft

Hello, I understand you need a clear and easy-to-understand report showing how satisfied users are with your IT help desk, focusing on response time, resolution quality, and agent professionalism. I will gather the necessary data from your ticketing system and create a simple, visual report using whichever tool you prefer, like Excel, Power BI, Tableau, or SQL dashboards. The report will include trend charts, scorecards, and a short summary so managers can easily see what's working well and what needs fixing. Before finalizing, I'll share a brief outline of the data I'll use, how I'll calculate key metrics like averages and CSAT scores, and a sample layout for your approval. To get started smoothly, I have a few questions for you:What specific fields or data points does your ticketing system capture related to response time, resolution quality, and agent professionalism? How frequently does the ticketing system update, and do you need the report refreshed in real time or on a set schedule? Are there any current benchmarks or target goals for satisfaction scores or service levels I should be aware of? Would you prefer a more visual dashboard style or a detailed report with narratives and scorecards? Is access to the ticketing system or data export ready for me, or will data delivery need coordinating on your side? Looking forward to working together. Best regards,

@MIndlabsAi6

Hello, I am Vishal Maharaj, with 20 years of experience in SQL, Data Visualization, Power BI, and Tableau. I have carefully reviewed your project requirements for the Helpdesk Ticketing Satisfaction Report. To tackle this project, I will first extract relevant data from the ticketing system focusing on response time, resolution quality, and agent professionalism. I will then utilize advanced analytics to calculate averages, SLAs met, and CSAT scores to provide a comprehensive view of end-user satisfaction. Using Power BI or Tableau, I will create visually appealing trend charts, scorecards, and a narrative summary for easy interpretation by non-technical stakeholders. I will also provide a sample mock-up for your approval before finalizing the report. Looking forward to discussing this further. Cheers, Vishal Maharaj

@emanz03

Turning raw helpdesk tickets into something leadership can actually act on usually fails at metric definition not visuals. Built a support dashboard where response time and resolution quality looked fine until segmented by agent and ticket type. That exposed SLA breaches hiding inside averages and led to a measurable CSAT lift. I’ll map your ticket fields into response time, resolution quality proxies, and professionalism signals, then build a clean dashboard with trends, SLA tracking, and a short narrative layer. You’ll get a refreshable model plus a simple mockup before build. Which ticketing system are you using and do you already capture CSAT or should we derive it from ticket behavior?

@Midorijn

Hi there, I can build a clear, data-driven dashboard that transforms your existing ticketing system data into an easy-to-understand view of end-user satisfaction. The goal is to help non-technical managers quickly see performance trends and identify improvement areas across your three key drivers: response time, resolution quality, and agent professionalism. I can deliver this in Power BI, Tableau, Excel, or a SQL-based reporting layer depending on your preference. My recommendation is Power BI due to its strong visualization, automation, and refresh capabilities.

@brianj75

Hello As a Business Consultant with a unique blend of skills in data analysis and strategic planning, I am well-equipped to tackle your project on helpdesk ticketing satisfaction reporting. My proficiency in Excel, Power BI, Tableau, and SQL-based dashboarding confirms my flexibility in tailoring the report to your needs. The core of my approach is rooted in the use of data-driven insights a strength that resonates well with the actionable output you are seeking for. Leveraging my decade-long experience, I will meticulously extract and analyze the raw data from your ticketing platform, calculating key performance indicators such as response time, resolution quality, and agent professionalism. Overall, innovative strategies and high-quality deliverables are what you can expect when you choose me for this project. Your vision aligns with mine in prioritizing client satisfaction; thus I look forward to partnering with you on this journey of transforming raw data into valuable insights that drive positive change for your IT help desk system. Together we can ensure that your organization makes informed decisions for the betterment of your end users' experience. Thanks Brian

@Sarsimbek

Hi, I can help you build a clear, data-driven helpdesk satisfaction report from your ticketing data. My background is in data analysis, reporting, and process-focused technical work, and I have also worked in detail on helpdesk/ticketing-system structure, including ticket workflows, incident handling, escalation logic, SLA tracking, knowledge-base usage, and user-support reporting. That helps me approach this project not just as a dashboard task, but as an operational support-analysis task. For this project, I can help with: * reviewing and structuring the raw helpdesk or ticketing data * cleaning the dataset and standardizing key fields * defining the most useful satisfaction and service KPIs * building a report/dashboard in Excel, Power BI, or your preferred format * highlighting the main service issues, trends, and improvement opportunities Useful report views can include: * CSAT / satisfaction trends over time * satisfaction by category, priority, team, or support channel * first response time and resolution time analysis * SLA performance and escalation patterns * repeat issue themes and backlog overview * management summary with practical recommendations My goal is to deliver something that is both technically sound and useful for decision-making, not just a set of charts. If you share a sample export from your ticketing system, I can quickly review the fields and suggest the cleanest reporting structure. Best regards Sergej W.