ChatGPT Enterprise training for sales & marketing teams in Singapore
ChatGPT Enterprise training for sales teams in Singapore: one hands-on day, onsite, on your own files. Account research. Proposals and campaigns.
ChatGPT Enterprise for sales & marketing teams
Sales and marketing teams need the same brief, the same tone and the same claims across every rep. This programme builds shared custom GPTs on your approved messaging so output does not drift person to person.
Where the work happens
- File analysis
- Custom GPTs
- Projects
- Canvas
The distinguishing exercise is building a custom GPT on your own files that a whole team can reuse, plus the verification standards that keep its answers trustworthy.
Who this programme is for
Sales, account management and marketing teams. Teams building shared internal tools.
- Account managers and sales teams preparing for discovery meetings and renewals
- Bid and proposal teams responding to RFPs and tenders
- Marketers adapting approved content across channels and audiences
- Sales and marketing leaders deciding which claims AI may draft and who approves them
Not the right fit
- Teams looking for a vendor demo rather than hands-on practice
- Anyone expecting AI to send customer communications or publish content without review
- CRM implementation or marketing-automation build projects — this is applied assistant training
What the day covers
Module 1: Account research
Account briefs are built from uploaded approved sources, with evidence and assumption separated in the output.
Exercise. Build an account brief from approved sources, distinguish evidence from assumptions and prepare discovery questions.
What you leave with. A referenced account brief and meeting plan.
Module 2: Proposals and campaigns
A proposal GPT is built on your own past proposals and approved claims, then tested against a live customer brief.
Exercise. Turn a customer brief into a proposal outline, campaign concept and audience-specific messages.
What you leave with. A proposal template and campaign brief.
Module 3: Content and follow-up
Approved content is adapted across channels, with brand and factual review before publication.
Exercise. Adapt approved content across channels and draft follow-ups from meeting notes with brand and factual review.
What you leave with. A content pack and follow-up workflow.
A worked example: An account brief that separates fact from guess
One exercise from the day, as it runs on your own material in ChatGPT Enterprise.
- What goes in
- A prospect's published annual report and your CRM notes export.
- What is asked
- Produce an account brief with two columns: what the sources say, and what we are inferring.
- What comes out
- A brief the account team can challenge line by line.
- What the reviewer checks
- Every item in the "sources say" column carries a page or note reference; anything without one moves to the inference column.
Singapore rules the exercises respect
Sales and marketing output in Singapore carries obligations on both data and claims.
- Prospect data used in research and outreach is subject to the PDPA, including the Do Not Call provisions for telephone and SMS marketing.
- Marketing claims are checked against the Singapore Code of Advertising Practice and your own approved claims list.
- Customer names and deal terms stay out of prompts unless your workspace terms and internal policy allow them.
What this day does not cover
Scope is agreed before the session so the day stays hands-on.
- API work, function calling or anything that requires writing code. This is a day for the people doing the business task.
- Admin configuration, workspace provisioning or SSO setup.
- Fine-tuning. The programme builds custom GPTs on your own files, which is a different thing and the one most teams actually need.
Before the session
- A licensed ChatGPT Enterprise seat for each participant
- Working knowledge of your own sales process, offer and brand guidelines
- Anonymised or sample working files — an account brief, a past proposal, approved product copy
- No coding background required
Format and schedule
- Delivery
- On site in Singapore or remote, delivered live. Cohorts are kept small enough that every participant works on their own files rather than watching a screen share.
- Duration
- Typically one full day, or two half-days scheduled around quarter-end. Module order is adjusted to your calendar and tool stack.
- How each module runs
- Each module follows the same pattern: a short walkthrough of the technique, a hands-on exercise on your own data, then a review of what the assistant got wrong and how to catch it.
- Afterwards
- Participants leave with the prompt patterns, templates and review checklists produced during the session, so the work continues after the training day.
How your data is handled
- Exercises run inside your own tenant and your own licences, so your data does not leave your environment for the training.
- Files shared with the trainer in advance are anonymised extracts; customer records, pipeline data and pricing stay inside your own tenant and licences.
- Every module includes verification: checking output against the source, confirming what the assistant left out, and marking what still needs a human read.
- Customer-facing output is reviewed before it is sent or published. The programme teaches AI-assisted drafting and research, never unattended outreach.
Who runs the session
Abhijit Ghosh
Founder, Eagentix · Data & Generative AI Practitioner · Singapore
The programme is delivered by Abhijit Ghosh, who has spent 25 years in data and AI, including roles at Accenture, IBM, Deloitte, Cloudera, Tibco and Wipro. Sessions are run by the practitioner, not handed to a junior facilitator.
Questions about ChatGPT Enterprise for sales & marketing
How do we stop messaging drifting between reps?
By building the brief once into a shared custom GPT on your approved claims, instead of each rep keeping their own prompt. The day builds it and tests it against a live customer brief.
What is a custom GPT and why does the day centre on building one?
It is a reusable assistant configured once with your own files and instructions, then shared with the team. It matters because it turns a good prompt one person wrote into a repeatable standard everyone uses — including the review checkpoints written into its instructions.
Is our uploaded material used to train the model?
Enterprise plans are sold on the basis that business data is not used for training, and your administrators can confirm the terms that apply to your workspace. We cover what to upload and what to keep out regardless, because access scope inside your own organisation matters as much as the vendor terms.
Can we put prospect lists into the assistant?
Only within your workspace terms and internal policy, and outreach still has to respect the PDPA's Do Not Call provisions. The session uses public sources and anonymised CRM extracts for the research exercises.
How do we keep generated claims accurate?
Every exercise works from an approved claims list. Anything the assistant produces outside that list is flagged for marketing sign-off before it reaches a customer.