Part of Lusha’s ongoing measurement of B2B buying signals. Every finding in one place: Five checks before you trust a buying signal.
Signal category descriptions and signal type definitions in this report are based on Lusha’s live signal database and product documentation as of June 2026. Mobility data is drawn from the Lusha B2B Contact Change Report Q2 2026. All data is aggregate and anonymised. No individual contact details are included or derivable from the figures presented.
Two identical emails, sent the same morning to the same job title at two similar companies. One lands the week the recipient started a new role and is rebuilding a stack from nothing. The other lands on someone eighteen months into a job with a signed contract and no reason to look.
The difference between those two emails is not the copy. It is timing, and timing is what a buying signal is for.
26 signal types. 1,470,414 B2B contacts changing companies in five months. This report maps what each signal category detects, how fresh each one is, and what stacking does and does not tell you.
The numbers at a glance
Part one: the four categories, and what sits in each
The 26 signal types group into four kinds of change. Each answers a different question about an account.
Plus two contact level signals, promotion and company change, which fire on people rather than accounts. Reading cadences come from live runs published in Five checks before you trust a buying signal, where one traffic reading was 84 days old and hiring readings were ten days old.
Part two: the mobility signal, sized
Of the 26, the contact level signals are the ones with published volume behind them. Between January 1 and June 1, 2026, Lusha detected 1,470,414 company changes and 194,165 promotions: an average of 13,600 people changing jobs every working day across 108 working days.
Every one of those is a signal in both directions. A record going wrong at the account they left, and a window opening at the account they joined. Whether either is worth anything depends on whether somebody is watching.
Sales is the busiest function in that total at 121,238 changes, IT second at 60,384, and C suite and VP level accounts for 23,301, which is 1.6% of the total and the slice with the largest consequences per move. The full breakdown is in the Contact Mobility Report.
Part three: stacking, and what it does not prove
An account firing three signals in a window is describing something different from one firing a single signal. Budget rising, hiring into a function, and a new executive in the seat together read as a company in motion. One hiring surge on its own reads as a company hiring.
What we can say. Stacking narrows a list. In a live run across 25 accounts, headcount decline alone fired on 13 and IT spend decrease alone on 9. Run together, six fired on both, and the two accounts in genuine contraction were among those six. The stacked list was under half the size of either single signal list, and every account on it had two independent reasons attached.
What we cannot say. That stacked accounts convert better. We have not measured conversion, and when we looked at stacking against a growth measure in a separate study, deeper stacks did not predict faster growth: companies firing all ten signal categories grew at effectively the same rate as those firing eight or nine. Stack depth counts how many kinds of activity were detected. It is a breadth measure, not a quality ranking and not a conversion predictor. That study is published in full, including the null result, in the Signal Stacking Report.
The version we can defend. Stacking is a filter, not a score. Use it to cut a list of 25 to a list of 6 where each account has a reason attached. Do not use it to claim those six will close, because nothing we have published supports that and we would rather say so than let the claim stand.
Part four: timing, as a planning frame
Different signals open windows of different lengths. The table below is drawn from how these situations tend to run, not from measured conversion data, and it is offered on that basis.
Part five: how to use this
1. Check the reading date before you write the first line. Signals read on different cycles. Hiring is weekly, budget and headcount are monthly, and in one live run a traffic reading was 84 days old. A rep who opens with “we saw your traffic jump this month” from a June reading is wrong in the first sentence.
2. Rank by size of change, not by percentage. A 33% hiring surge can be two job postings. An 81% surge can be 66 against an average of 36. Only one of those is a hiring drive.
3. Stack two signals to cut the list, then work it by hand. Two signals moving the same way tell you why something is happening. That is worth more than either alone, and it is still not evidence that the account will buy.
4. Separate the customer read from the prospect read. The same signal means opposite things. Budget cuts and headcount decline are churn warnings on a customer and consolidation openings on a prospect. One tag in the workflow keeps a CSM from receiving a cold sequence.
What this report cannot tell you
Conversion. Nothing here measures which signals produce meetings, pipeline or closed business. The outreach windows are a planning frame, and the stacking section says plainly what the one stacking study found, which was a null result on growth.
Detection, not events. Every count is of detected changes. A change nobody observed is not in the total, so all figures are floors. Our own measurement of detection lag found a three month window returning half the monthly rate of longer windows.
Signal magnitude. Category counts do not weight by size. One modest hiring surge counts the same as a large one in a category tally.
Methodology and data notes
Signal data source: Lusha live signal database, 290M+ verified contacts and 29M+ company profiles.
Signal definitions: category descriptions and signal type names reflect Lusha’s live signal database and product documentation as of June 2026. Reading cadences reflect observed behaviour in published live runs.
Mobility data source: Lusha B2B Contact Change Report Q2 2026.
Signal window: January 1 to June 1, 2026, 108 working days.
Outreach timing: windows are directional guidance based on observed patterns, not guaranteed conversion windows. Actual timing varies by industry, deal size and buyer persona.
Privacy and compliance: all data is aggregated and anonymised. No individual contact details are included or derivable from the figures presented. Current certifications are listed on the trust center.
