ABC Sales AI · Working Session + Install
Fixes audit area B4a.k.a. The Offer Clinic
People who completely understood what you sell still say no, and no amount of follow-up fixes that. Your offer is a price list: nothing in it makes deciding today more sensible than deciding in March. You discount instead of giving a reason, your team all pitch it differently, and nobody has ever measured which part loses people.
We bring you the real reasons people said no, in their own words, with counts, then rebuild the offer with you: the core, bonuses that each answer one real objection, the guarantee, the believable reason why, and a deadline that is actually true. You leave with it live inside your own system, not written on a page.
Counted
the real reasons people said no, with counts, before any opinion
True
a reason why and a deadline you can actually defend
Live
the offer leaves the room inside your own system
What it is costing you
This is the only area in the audit that automation cannot fix. A better machine pushing a weak offer just reaches no faster.
Fill it in yourself:
Of the last ten people who fully understood what you sell, how many still said no? If it is more than half, is your problem really follow-up? Everything else you build will underperform until this is fixed.
How it works
Answered the way you are already thinking about it.
How would you know what my market objects to?
We do not guess. Your conversations already hold the answer.
Before anyone sits down, we run Objection Intelligence over your real conversations to cluster the actual objections, and the AI Manager's analysis to find where in the conversation people go quiet.
You get the real reasons people said no, in their own words, with counts, before anyone in the room has an opinion.
The session starts from evidence, not opinions.
So we sit in a room and talk?
It is a working session with an instrument in it, not a workshop.
A focused session on the offer itself: what you sell, to whom, what they are really buying, and what makes deciding now rational rather than pressured. The AI Manager works live in the room: it holds your sales context, so it generates offer angles, bonus ideas and reasons-why grounded in what your own customers have said, and we react to them together instead of staring at a blank page.
Then we rebuild it: the core, bonuses that each answer one real objection, the guarantee, the believable reason why, and a deadline that is actually true.
An offer that answers the objections your market actually has.
My team will still pitch it their own way.
One product should not sound like three.
We write the offer one-pager and the pitch script, so your whole team says the same thing. Then we load the rebuilt offer, its bonuses and its objection answers into the Knowledge Base and your AI Employee, so the AI pitches exactly what your humans pitch.
One pitch, said the same way by every human and by your AI.
How will we know it actually worked?
Every offer change should end in evidence, not a feeling.
We tag a test segment, set the measurement, and build the report that tells us whether the new offer moved anything. After the review we revise once, and feed the winning version back into the agent prompt, so it becomes the default.
Evidence about which change moved sales, instead of an opinion.
What we will do for you
Every install is two jobs: the thinking and the wiring. You should see both before you buy either.
The package
Included: the objection evidence with counts, the working session, the rebuilt offer, the one-pager and pitch script, the Knowledge Base and AI Employee install, the tagged test, the report, and one revision.
Not included: your pricing decision itself (we advise, you decide), and paid ads to promote the new offer.
What we need from you: access to your real conversations, the decision-maker in the room, and honest answers about what you sell.
Timeline: evidence is gathered before the session; the rebuilt offer goes live in your system within days of it, and the test reads out over the following weeks.
How this engagement is delivered
Every install is the deployment of an AI system into your business, delivered as a service. In the categories IRAS uses for qualifying AI business services, the work is:
Investment
No two businesses leak in the same place, so no two installs are identical. Your consultant scopes it with you, shows you exactly what it is worth against your own numbers, and quotes it. Every other system you buy performs to the ceiling this one sets.
Singapore company? Install work like this is the kind of AI spend the EIS 400% deduction covers for YA2027 and YA2028, roughly 51 cents saved per dollar for a profitable company at 17%. No application: when the work is completed and accepted we send the claim documents, and your accountant adds it to your normal return. Forward our accountant page, and confirm your own eligibility with your tax advisor.
We build a limited number of installs each month, so every system gets senior attention.
We say it honestly at discovery if your offer is not the problem, and we would rather point you at follow-up or capture than sell you a session you do not need. Then we do the work: the objections clustered with counts, the session run, the offer rebuilt and loaded into your system, the test measured. And we do not stop at one revision: if the new offer is not converting, we go back to the evidence and rework it until it does. If after that it still has not delivered what we agreed in writing, we refund half your fee, and you keep everything we built. The exact terms sit in your service agreement. Whatever your market decides, you keep:
Worst case: you finally know exactly why people say no, and your whole team pitches one offer the same way. Best case: the same leads you were already paying for start saying yes, and every system downstream performs better because of it.
Honest fit check
Before you ask
No. The AI Manager is the instrument in the room: it holds your sales context and generates angles grounded in what your own customers have said. And you leave with the offer live inside your own system, in the Knowledge Base and the pitch of your AI Employee, not written on a page.
That is part of the problem. Discounting teaches your market to wait for the next discount. A believable reason why, and a deadline that is actually true, give people a rational reason to decide now without cutting your price.
We tag a test segment, set the measurement, and build the report that tells us whether the new offer moved anything. You get evidence instead of opinion, and one revision based on what it shows.
Because the offer is the thing the machine carries, not the machine itself. A better machine pushing a weak offer just reaches no faster. Fix the offer once, and everything downstream works harder.
Yes, this is the kind of spend the scheme was built for: IRAS lists system development and deployment, consultancy and strategy, data and analytics, and training as qualifying AI business services. For YA2027 and YA2028 the EIS gives a 400% tax deduction on the first S$50,000 of qualifying AI spend per year, roughly 51 cents saved on every dollar for a profitable company at 17%. There is no application and no pre-approval: you claim it in the tax return you already file. Our part is to make it effortless. When the install is completed and accepted, we send the necessary documentation, itemised under this system's title, and we work with your accountant on anything else the claim needs from our side. Whether your company qualifies depends on your own situation, so confirm with your tax advisor.
ABC Sales AI · abcsales.ai · Every install is scoped to your business and quoted by your consultant. Outcomes depend on your market, offer and execution; the guarantee above is the promise we stand behind. You are responsible for the content you send; campaigns are vetted against your industry's rules before launch. ABC Sales AI is not a tax advisor; any Singapore EIS treatment is for your tax advisor and IRAS to confirm.
Bring the evidence, rebuild the offer, and leave with it live in your own system: one pitch, said the same way by every human and by your AI.
