How fast do unsold estimates go cold?
Faster than most owners expect, and the shape is specific to your business and job type. Build the curve from your own records: for every estimate presented, log the days between presentation and sale, then plot the cumulative share sold by day. It typically drops steeply in the first few days and flattens into a long, thin tail. The flat part is where follow-up effort earns almost nothing.
Build the curve before you argue about follow-up policy
Every company has an opinion about how long to chase an estimate. Almost none have measured it. The measurement is straightforward: for each sold estimate, compute days from presentation to sale, then express the results as a cumulative distribution. Half of your eventual sales will land inside some number of days. That number is the only follow-up benchmark that matters for your business.
Do it separately for urgent repair work and for planned replacement or project work. Urgent work resolves in days because the customer has a broken thing in their house. Planned work runs on the customer's financing, schedule and spouse, and its curve extends for weeks.
What the shape tells you operationally
A steep early drop with a fast flatline means your callbacks need to happen within a very short window and that a long nurture sequence is mostly theater. A flatter curve with a meaningful tail means systematic long-cycle follow-up genuinely produces revenue and should be staffed.
The tail is also where the arithmetic gets interesting. A low close rate on a large number of aged estimates can still be worth more than a high close rate on a handful of fresh ones. Compute expected value per contact attempt, not close rate, before deciding where the effort goes.
Things that distort the curve
- Reissued estimates. If a stale estimate gets rewritten as a new one, your curve looks artificially fast. Track the original presentation date.
- Seasonal timing. An estimate presented at the start of a busy season closes differently than the same estimate presented at the end of one.
- Financing changes. Introducing or removing a financing option can move the curve materially, so segment before and after the change.
- Silent closures. Estimates nobody ever formally closed sit open forever and flatten your tail with dead records. Enforce a close-out rule before trusting the data.
Turning the curve into a working process
Once you have the curve, pick a cutoff where marginal follow-up stops paying, and move everything past it into a low-cost channel rather than a person's call list. Then measure whether the cutoff was right by tracking sales that arrive after it.
The reason this is worth automating is that the trigger is time-based and per-record, which no one manages well by hand. Automated aging alerts and follow-up prompts fall squarely into operational AI rather than content generation, and they connect directly to the record in the field service system through the Bluefrog Intelligence Platform.
Topics: estimates · follow-up · aging · close rate · pipeline
Have a version of this question about your own business?
The useful answer usually depends on which systems you run and how they're connected. That's a conversation, not a blog post.