AI prompt

Prep for the three objections an account is likeliest to raise

Tools: Claude ▪ Lusha

The account in the live example is unnamed and the contact is described by title only. No emails or phone numbers are revealed in this play.

Generic sales objection handling prepares you for the objection any buyer could raise. This prompt prepares you for the three this account is likeliest to raise, using its own data through the Lusha connector for Claude: headcount by department, locations, funding dates and this quarter’s signals.

Each objection comes with the fact behind it, a response that uses that fact, a question to ask back, and the line not to say. The prompt also flags facts too old to bring up and fields Lusha had no data for.

The prompt

Open in Claude Open in ChatGPT

<context>
I sell: [your product, in one line].
The call is with: [name and title] at [company domain].
Call type: [first call, demo or follow-up].
Objections we hear often: [optional list].
</context>

<task>
1. Credits. Run account_usage, which is free, and estimate the run before spending anything.
2. Account facts. Pull the account's size, revenue range, locations and funding rounds with dates, headcount by department, and its signals from the last 90 days. Confirm the contact's current title.
3. Objections. Predict the three objections this account is likeliest to raise on this call. For each one, give:
   - the objection, in the words a buyer would use
   - the account fact that makes it likely, with its date
   - a response of two or three sentences that uses that fact
   - one question to ask back
   - one thing not to say
4. Gaps. If Lusha has no data for a field, say so and don't predict from it.
5. Stale facts. Flag any fact old enough to mislead on the call, such as a funding round more than 12 months ago.
</task>

<output>
- Account facts, each with a date
- Three objection cards
- One opening line for the call
- Fields Lusha had no data for
- The credits the run used
</output>

<constraints>
- Do not reveal emails or phone numbers.
- Do not state anything about the account that the data doesn't support.
</constraints>

What you'll get back

The situation

We ran the prompt on October 25, 2026 to prep a first call with the President of Global Sales at a US software company of 370 people, for an example seller of sales onboarding software.

Account facts

Fact	Value	Date
Headcount	370 employees, up from 314 three months earlier	Sep 1, 2026
Hiring	A new hiring surge: 3 job posts in a week against an average under 1	Oct 12, 2026
Sales and business development	29 in sales and 26 in business development	Oct 25, 2026
Locations	Offices in New York and Chennai	Oct 25, 2026
Revenue range	$10M to $50M	Oct 25, 2026
Last funding round	Series B	October 2024, flagged as more than 12 months old
Contact	President of Global Sales, confirmed on the enriched profile	Oct 25, 2026

The three objection cards

Objection 1

“We’re not big enough to need a platform for this.”

The fact behind it: 55 people across sales and business development today, total headcount up from 314 to 370 in three months, and a new hiring surge on October 12.

Response: That holds for a team that isn’t changing. Yours added more than 50 people in one quarter and started hiring again this month, so the next group of new sellers is already on the way. The question is whether their ramp runs on a program or on your managers’ calendars.

Ask back: How many of this quarter’s hires went into sales or business development?

Don’t say: “Every growing company needs this.” It isn’t about them.

Objection 2

“Our team is split across two countries. One program won’t work for both.”

The fact behind it: Offices in New York and Chennai.

Response: That’s the case for one program, not against it. New hires in both offices learn the same pitch on their own schedule, and managers in each office see the same progress.

Ask back: Where do new sales hires sit today, and who onboards them in each office?

Don’t say: “Time zones don’t matter.” They do, and the buyer knows it.

Objection 3

“There’s no budget for this until next year.”

The fact behind it: Last funding round in October 2024, revenue range of $10M to $50M, headcount still growing.

Response: Understood. When does planning for next year close? If ramp for this year’s hires is going to be in that plan, it’s worth 20 minutes before the plan locks.

Ask back: When does your planning cycle close?

Don’t say: “You just raised, so there’s budget.” The round is a year old, and the prompt flagged it for exactly this reason.

Opening line

“You’ve added more than 50 people since the summer and you’re hiring again this month, so I’d guess ramp is on your list. Is that right?”

What Lusha had no data for

Open jobs by department came back empty for this account, so the prompt could not confirm which teams the October hiring surge was in. It said so, and objection 1 asks the buyer instead of assuming. The funding summary field also returned an invalid date, so the prompt used the dated round list underneath it.

Credits the run used

7 credits: 2 for the company lookup, 3 for headcount by department and related fields, and 2 for the account’s signals. The credit check at the start is free.

Account data confirmed live via Lusha connector, October 25, 2026. The seller, product, responses and opening line are illustrative. The account facts, dates, gaps and credits are from the live run.

Why it works

An objection is usually a fact about the buyer’s company, said out loud. A team that thinks it’s too small, an org split across two countries, a budget that closed months ago: each one shows up in the data before it shows up on the call. Lusha in Claude reads the account’s headcount by department, locations, funding dates and dated signals, so each response rests on something true about this company rather than on a script. The prompt also stops two things that lose a call: quoting a fact that’s out of date, and guessing where the data is empty. Lusha collects business contact information only and does not scrape social platforms: data sources and the Trust Center.

FAQ

Does it reveal anyone’s contact details?

No. The prompt works from company data and the contact’s title only, so no emails or phone numbers are revealed and no contact credits are spent.

Why flag a funding round as stale?

Because “you just raised” is a line reps reach for, and it backfires when the round is a year old. The prompt flags any round more than 12 months back so nobody says it on the call.

What if Lusha has no data for a field?

The prompt lists the empty fields and builds no objection on them. In our run, open jobs by department was empty, so the first card turns that gap into a question for the buyer.

Can I give it the objections my team hears?

Yes. Add them in the context block and the prompt checks each one against the account’s data, keeping the ones the facts support.

What does it cost?

7 credits in our run: the company lookup, headcount by department and the account’s signals. Current plans: lusha.com/pricing.

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