Outputs on this page come from a live run on September 10, 2026. Company names are masked to initials. No contacts were previewed or revealed.
An IT spend decrease signal is one of 24 company signals available through the Lusha connector for Claude. It is the mirror of the IT spend increase play, and it needs more care: a company cutting budget is not buying anything unless what you sell replaces two things they already pay for.
Check my account list for IT spend decreases and tell me who to protect and who to approach with a consolidation offer.
Before anything else, run account_usage and tell me my remaining credits. Do not run any signal call if fewer than 50 credits remain; stop and tell me.
Here is my list (domain, one per line):
[PASTE UP TO 25 DOMAINS]
Customer domains (or write "none"):
[PASTE]
Steps:
1. Run signals_companies_search on the list with signalTypes ["itSpendDecrease"], startDate 90 days ago, maxResultsPerSignal 3. Batch in groups of 25 if the list is longer. If a domain comes back "could not be identified," tell me and suggest the canonical domain to retry.
2. For every account that returned an IT spend decrease, pull the size of the decrease and the reading date. Keep accounts with no signal in the output as "no signal" so I see the full list.
3. Rank the hits: accounts with a decrease on two or more consecutive monthly readings first, then single readings by size. Flag any single reading larger than 50% as VERIFY; one reading that size is a data refresh until a second one confirms it.
4. Tag customers as CHURN RISK and route them to the account owner. Tag everyone else as CONSOLIDATION.
5. For the top 5 CONSOLIDATION accounts, write one opening line that offers to reduce tools or cost. Do not mention the size of the cut, do not use the words layoffs, struggling or downturn, and do not quote a figure the prospect cannot verify.
Output: one table with columns Account | IT spend signal | Reading dates | Segment | Opening line. Then two lines: what the ranking is based on, and credits used. Do not preview or reveal any contacts in this run.
The situation. A list of 25 B2B companies, 900 to 6,000 employees, across software, marketplaces, real estate tech and infrastructure. No customer domains supplied, so every hit is a prospect.
The run. account_usage first, at zero credits. Then one batch call on 25 domains for itSpendDecrease with a 90 day window. 9 of 25 fired, 15 signal events, 15 credits. One domain could not be identified (see Where this breaks).
What came back.
| Account | IT spend signal | Reading dates | Segment | Opening line |
|---|---|---|---|---|
| C.G. (edtech, ~1,000 emp) | -5%, then -77%, then -78% | Jul 8, Aug 8, Sep 3 | CONSOLIDATION | When a stack gets reviewed line by line, the tools that survive are the ones doing two jobs. Happy to show which two of yours we replace. |
| C.P. (real estate tech, ~4,000 emp) | -63%, then -51% | Aug 8, Sep 3 | CONSOLIDATION | Most teams we talk to are paying three vendors for contact data and using one. Worth twenty minutes to see if that is you. |
| O.D. (real estate, ~1,400 emp) | -54%, then -55% | Aug 8, Sep 3 | CONSOLIDATION | Fewer vendors, one credit balance, nothing to build. If a data line is up for review this quarter, this is the conversation. |
| B.C. (ecommerce platform, ~1,000 emp) | -16%, then -62% | Jul 8, Sep 3 | CONSOLIDATION | If your team is being asked to do the same pipeline with fewer tools, verified data is the piece that makes the rest of the stack smaller. |
| S.S. (work management, ~3,000 emp) | -52% | Sep 3 | VERIFY | Held pending a second reading. Opening line: the cheapest way to cut a data stack is to stop paying for records you already own. |
| R.S. (cloud services, ~6,000 emp) | -54% | Jul 8 | VERIFY | Held pending a second reading. |
| L.Y. (mobility, ~3,000 emp) | -41% | Jul 8 | CONSOLIDATION | |
| D.M. (analytics, ~900 emp) | -32% | Jul 8 | CONSOLIDATION | |
| Z.U. (billing software, ~1,600 emp) | -19% | Jul 8 | CONSOLIDATION | |
| 15 accounts | no signal | |||
| 1 account | not identified | Domain on a .social TLD; retry with the canonical .com domain. |
Ranking based on consecutive monthly readings first, then size. Single readings above 50% flagged VERIFY. Credits used: 15. Confirmed live via Lusha connector, September 10, 2026. Company names masked to initials.
What happens next. The CONSOLIDATION rows go to outbound with the opening lines above. The CHURN RISK rows (none in this run, because no customer domains were supplied) go to the account owner, not to a sequence: the right move on a customer cutting budget is a business review with a downsell option on the table, not a renewal push. To find the budget owner at the top five prospects, hand them to the decision maker play. This play does not preview contacts; the ranking comes first, the reveal decision after.
Most signal tools tell you a company is researching a topic. An IT spend decrease is a measured change in a budget line, with a date, and unlike an anonymous intent score it has a clear operational meaning for both halves of your book. Inside Claude, the Lusha connector runs the check as one batch, keeps the “no signal” rows visible, splits customers from prospects so the same signal routes to a CSM or an AE, and holds single outliers as VERIFY so a data refresh does not become a cold email. The run costs signal credits only. Every signal is sourced under Lusha’s data methodology and compliance framework.
A drop in the company’s estimated technology budget allocation compared with the prior reading. The signal carries a size, a date, and the budget it was measured against. It does not say which categories were cut.
Because the two directions are not symmetrical. Budgets double in a month (a new program, an acquisition) more often than they halve. A single reading showing half the technology budget gone is more likely a source refresh than a decision, so it waits for a second reading.
Because a customer cutting budget is deciding what to keep, and an automated email is the easiest thing to cut. A business review with a downsell or re tier option keeps the relationship. The play tags them CHURN RISK and stops; the conversation is human.
Yes. Paste both lists; the customer domains decide the tag. Running customers first is the better habit, because the churn read is time sensitive and the consolidation read is not.
Signal reads cost 1 credit per event returned. In the live run, 25 domains cost 15 credits. account_usage runs first at zero credits and the prompt stops under 50. No contact preview or reveal runs in this play.
Yes, as a second step. Use prospecting_company_search with a technographic filter for the competitor tool, validate the value with prospecting_company_filters first, and intersect with the CONSOLIDATION rows. Keeping it out of this prompt keeps the run at signal cost.
One data connection. Works in Claude, ChatGPT, your CRM, or any agent you build.
