The cost of poor timing in prospecting

In B2B prospecting, we measure everything: opening rates, response rates, appointments made. We almost never measure the variable that dominates all others: the moment we arrive. A great message sent at the wrong time loses to an average message sent at the right time. And contrary to popular belief, bad timing has a quantifiable cost — in both directions.

Too late: the deal has already been signed elsewhere

The scenario is familiar. You contact a company that perfectly matches your ICP. Polite response: “We have just equipped ourselves, come back in two years”. The company had the problem, the budget, the urgency — three months earlier. You just weren't in the conversation when it happened.

Let's take an order of magnitude. Take a team that addresses 1,000 accounts per quarter with an average basket of 15,000 euros and a conversion rate of 3% when it arrives in the purchase window. If 20% of its target accounts are contacted after the decision has been made elsewhere, these are 200 accounts sterilized per quarter - or, with equal conversion, the equivalent of 6 deals and around 90,000 euros of pipeline lost not for lack of product or speech, but for lack of clock. Over a year, the systematic delay weighs more heavily than most sequence optimizations.

Too soon: the invisible cost of stalled cycles

The opposite mistake is sneakier because it looks like a success. The prospect responds, accepts a meeting, shows interest — but he has neither allocated budget nor immediate pain. The deal enters the pipeline and stays there. Six months of relaunches, three demos, a champion who changes position, and an opportunity that dies in “no decision”.

The cost here is not the lost deal: it did not exist yet. This is the commercial time immobilized. An account executive who spends 15 hours on a premature opportunity means 15 hours taken away from the accounts that were in their window. Opportunities closed in “no decision” — often a third of B2B pipelines — are mostly timing errors, not targeting errors.

Timing is not an intuition, it is a reading of dated signals

The good news: purchase windows leave traces, and these traces are dated. Some examples of signals that precede a purchase:

• Job offers : a company that publishes 4 SDR offers will equip itself with commercial tools in the following months, not in two years. The date the offer is published is timing information, not just targeting information.
• Taking up positions : a new VP Sales or HR Director restructures his tools in his first two quarters. Afterwards, the window closes.
• The workforce trajectory : the increase from 45 to 70 employees in one year triggers predictable purchases — HRIS, ATS, management tools — at known thresholds.
• Republishing offers : an offer republished three times in six months signals a lasting recruitment problem, therefore favorable territory for any recruitment player.

Each of these signals is a dated fact. Their combination does not give certainty, but it gives better than an address book sorted in alphabetical order: a temporal priority queue.

What fresh data changes

The condition for reading these signals is brutal: they expire quickly. A job offer detected three months late has lost most of its timing value — the window it announced is closing. This is the difference between a static database, refreshed once a year, and an index fed continuously: the first tells you who to target, the second also tells you when.

This is precisely the layer on which sourcing.sh is positioned: an index of around 200,000 companies and 1.4 million job offers, maintained continuously by agents, where each signal arrives with its date — and delivered where your team works, in the CRM, via API or via Claude. Well-timed prospecting requires no more effort than random prospecting. It simply asks you to know what time it is for your prospects.