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PROGRAM 09 · TEAM TRAINING

AI & Data for Customer Service Professionals

Answer faster, solve more, and turn every complaint into an insight.

8 sessions3 modules4 hands-on projects3 days · 9 am–5 pmCertificate on completion
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Who this course is for

  • Customer Service and Contact Centre Managers and team leads
  • Call centre, live chat and Facebook page support agents
  • Complaint management and quality assurance teams
  • Service teams in telecom, e-commerce, banking, MFS, ISPs, utilities and hospitality

What your team will be able to do

  • Write empathetic, on-policy replies in Bangla, English and Banglish
  • Build a clean knowledge base and a FAQ chatbot with a human handoff
  • Turn thousands of tickets into a clear root-cause report
  • Deploy four working automations in your own service team
How it runs

3 days at your office, 8 sessions

Three sessions a day plus a hands-on build lab every afternoon. Day 3 ends with capstone presentations.

Day 1

9:00 am – 5:00 pm

AI chatbots for replies and knowledge

9:00–10:30S1Prompt engineering for customer service
10:30Tea break
10:45–12:15S2The perfect reply: empathy & tone
12:15Lunch & prayer
1:00–2:30S3Knowledge base & FAQ chatbot design
2:45–4:30LABBuild lab: reply library for your top 20 questions
4:30–5:00Q&A and day recap

Day 2

9:00 am – 5:00 pm

Service analytics, then the first two builds

9:00–10:30S4Formulas & ticket data cleaning
10:30Tea break
10:45–12:15S5Service analytics & root causes
12:15Lunch & prayer
1:00–2:30S6Projects 01 & 02: Assistant & alerts
2:45–4:30LABBuild lab: dashboard, assistant and alerts on your data
4:30–5:00Q&A and day recap

Day 3

9:00 am – 5:00 pm

Last two builds and the capstone

9:00–10:30S7Project 03: Ticket tagging & escalation
10:30Tea break
10:45–12:15S8Project 04: Complaint letter extraction
12:15Lunch & prayer
1:00–3:00LABCapstone build clinic
3:15–4:30LABCapstone presentations
4:30–5:00Certificates and next steps
Group: 10–40 people from one organisationSame content and projects in both formatsBangla delivery with English technical termsEvery session ends with a deliverable
Curriculum

8 sessions, one build in each

3 modules · 8 sessions · 4 hands-on projects

PART 1AI Chatbots for Customer Service WorkSessions 1–3

Chatbot Landscape & Tool Selection

  • Gemini, ChatGPT, Claude, Copilot and DeepSeek: strengths for customer service work (reply drafting, Bangla and Banglish tone, knowledge base articles, ticket theme tables)
  • Free vs paid tiers; a workflow that needs no international payment card
  • Bangla vs English output quality; when to draft in English and translate
  • Which tool for a long document, which for a formula, which for a polished letter

Prompt Engineering Fundamentals

  • What a prompt is; why the same question gives different answers
  • The four-part structure: role, context, task, output format
  • Role prompting: act as a senior support agent, complaint resolution officer, QA coach or knowledge base writer
  • Controlling output: length, tone, language, table or bullet format

Advanced Prompting Techniques

  • Few-shot prompting: teaching the model with examples of your own customer service work
  • Step-by-step reasoning for multi-part tasks such as deciding whether a refund case is within policy or diagnosing a repeated delivery complaint
  • Constraint prompting: what to include, what to exclude, what to never assume
  • Chained prompts: breaking a complaint case (read → classify → check policy → draft reply → escalation note) into a sequence of smaller steps

Iteration & Prompt Library Building

  • Why the second prompt matters more than the first; refining instead of restarting
  • Diagnosing a bad output: vague instruction, missing context or wrong tool
  • Building reusable prompt templates for repeated customer service tasks
  • Testing a prompt before it goes into daily use

Data Privacy & Verification Discipline (Core)

  • What must never be pasted: customer phone numbers, addresses, NID and account numbers, OTPs or PINs, payment details, call recordings with personal data
  • Anonymising data before prompting; safe vs unsafe customer service use cases
  • Hallucination awareness; verifying every figure, date, name and legal reference
  • The verification rule: AI drafts, a person checks before anything leaves the building
DELIVERABLEa personal prompt library of 10 templates for your repeated customer service tasks.
PART 2Customer Service Data Analysis in Excel & Google SheetsSessions 4–5
PART 3Applied Projects: AI Assistants & AutomationSessions 6–8
Applied projects

Four automations, running in your organisation

01Session 6

Service Policy & Knowledge Assistant

Frontline agents and new joiners ask about refunds, returns or prices and get an answer with the section cited.

  1. INService policy & FAQs
  2. AIGrounded Gemini assistant
  3. OUTAnswer with the section cited
Built with Google AI Studio
02Session 6

SLA, Contract & Service Alert Engine

Complaints nearing their SLA, promised callbacks, warranty expiry and software renewals checked daily, with alerts 30, 15 and 7 days ahead.

  1. INSLA & renewal tracker
  2. RUNDaily Make scenario
  3. OUTAlert to the right owner
Built with Make · Sheets · Gmail
03Session 7

Ticket Tagging & Escalation Workflow

Complaints from every channel tagged by category, urgency and sentiment, routed to the right team, with fraud and safety cases sent to a supervisor.

  1. INComplaints from every channel
  2. AIGemini tagging and routing
  3. OUTTicket with the right team
Built with Apps Script · Forms
04Session 8

Complaint Letter & Form Extraction

Complaint letters, warranty cards and service forms become clean rows, coded to your category list, with urgent cases flagged to a supervisor.

  1. INLetters, forms & warranty cards
  2. AIGemini structured extraction
  3. OUTCoded rows in your sheet
Built with Gemini API · Drive

Capstone presentation

Each person presents one automation built for their own workplace.

Day 3 afternoon
Applied across every session

Responsible & Ethical AI in Customer Service

Fairness & Non-Discrimination

  • Where bias enters customer service decisions: data, wording, criteria and past patterns
  • Proxy discrimination: address, age, gender or background inferred indirectly

Privacy & Data Protection

  • Data minimisation: collect only what the decision requires
  • Retention and deletion of customer and caller data

Honest Service & Customer Dignity

  • Telling customers when they are talking to a bot
  • Never hiding a known fault or giving false resolution times

Accountability & Human Oversight

  • Human-in-the-loop by design: AI recommends, a named person decides
  • Who owns an AI-assisted decision when it is challenged

Workforce Impact & Your AI Use Policy

  • Talking to customer service teams about AI without triggering job-loss fear
  • Reskilling and role redesign as AI absorbs routine work
Outcomes

By the end, your team can

  • Choose the right AI tool and write prompts that work first time
  • Maintain a prompt library covering your repeated customer service tasks
  • Write empathetic, on-policy replies and de-escalate difficult cases
  • Build a clean knowledge base and a tested FAQ chatbot design
  • Clean and code ticket data and produce a root-cause report
  • Build and deploy automations with Make, Apps Script and the Gemini API
  • Apply fairness, transparency and privacy to every AI-assisted decision

And leaves with

A 20-question reply library and de-escalation playbook
A knowledge base and FAQ chatbot design with human handoff
A service dashboard and root-cause report
A grounded service policy & knowledge assistant your colleagues can use
A sla, contract & service alert engine that reaches the right owner
Four deployed automations running in your own organisation
A written AI use policy for your own customer service team

Tools your team will use

Chatbots
ChatGPTGeminiClaudeCopilotDeepSeek
Content
CanvaGammaCapCutGoogle Slides
Data
Microsoft ExcelGoogle SheetsPower Query
Workspace
GmailCalendarMeetFormsDrive
Automation & AI builds
MakeGoogle AI StudioApps ScriptGemini API
Customer Service tools
Meta Business SuiteWhatsApp Businesschatbot buildersLooker Studio

What participants need

  • A laptop with Excel and a Google account
  • Basic Excel comfort (filters, Pivot Tables) and an anonymised export of tickets or chats
  • One real work file to practise on from Session 2
  • No coding background required; free tiers only

How your team will learn

  • build-along classes (you work while the trainer works)
  • practise on your own workplace file, not dummy data
  • every session ends with a deliverable
  • Bangla delivery with English technical terms
  • recordings, prompt library and setup guides
  • certificate after capstone submission
Request a proposal

Bring this program to your customer service team

Tell us about your team. We reply within one working day with a plan built around your own documents and workflows.

  1. 1 · A short discovery call with your customer service lead
  2. 2 · We tailor examples to your masked files
  3. 3 · Offline at your office, or online live classes
Chat on WhatsApp
Request a proposal