> ## Documentation Index > Fetch the complete documentation index at: https://docs.famulor.io/llms.txt > Use this file to discover all available pages before exploring further. # Outbound playbook > Who to call, when, what to say, and what to measure — a research-backed starting point for cold outreach Outbound calling works best as a system you keep tuning, not a script you set once. This page distills published sales research into a starting playbook for your campaigns — check it against your own numbers and adjust from there. ## Who to call Define your ideal customer profile before writing a single line of script: * **Company fit** — size, industry, region, and technology stack. * **Persona fit** — role, goals, pain points, and what triggered the outreach (a funding round, a new hire, a renewal date coming up). Store these as [custom attributes](/audience/contacts#custom-attributes) on your contacts — industry, use case, funnel stage, intent signal — then [save a segment](/audience/call-qa#filter-builder-and-saved-segments) for each combination worth targeting on its own. A value proposition tailored to one segment, kept to a sentence or two, consistently beats a generic pitch aimed at everyone. ## When to call Connect rates vary sharply by time of day, and speed of follow-up matters even more: * **B2B**: late morning (10am–12pm) and late afternoon (4–5:30pm) local time tend to connect best; Wednesday and Thursday usually outperform Monday and Friday ([Gong](https://www.gong.io/blog/best-time-to-call/), [XANT/InsideSales](https://www.xant.ai/blog/best-time-to-call-prospects/)). * **B2C**: 11am–1pm and 5–7:30pm local time tend to work well — avoid very early mornings and late evenings ([HubSpot](https://blog.hubspot.com/sales/cold-calling-stats)). * **Speed beats timing**: reaching a new lead within five minutes can improve connect odds by an order of magnitude compared with waiting even an hour ([Harvard Business Review](https://hbr.org/2011/03/the-short-life-of-online-sales-leads)). Set [calling windows](/campaigns/dialer-and-compliance#calling-windows) per campaign so dialing only happens in your best hours, and turn on [retry until a human answers](/campaigns/dialer-and-compliance#retry-until-a-human-answers) — a retry lands at a different hour automatically, which is exactly the kind of variation the data above rewards. ## What to say Lead with listening, not pitching. The **LAER** framework, from [Carew International](https://www.carew.com/blog/the-laer-method/), keeps a call centered on the customer instead of the script: * **L**isten — let them finish before responding. * **A**cknowledge — reflect back what you heard. * **E**xplore — ask what would make this relevant to them. * **R**espond — offer a specific next step, not a generic pitch. Calls where the rep talks less — roughly 40–50% of the time — consistently correlate with higher conversion ([Gong](https://www.gong.io/blog/talk-listen-ratio/)); the same logic applies to how long your assistant's turns run. A handful of objections cover most calls. Keep a short response ready for each: | Objection | A workable response | | -------------------- | ---------------------------------------------------------------------------------------------------------- | | "Not interested" | Ask for 20 seconds to explain, then lead with one concrete number relevant to them. | | "Send me an email" | Ask what the two most important decision points are, then offer a short meeting once those are addressed. | | "No budget" | Ask what the current problem is already costing them, then propose a small pilot with a clear success bar. | | "Not the right time" | Lock in a specific callback time rather than leaving it open-ended. | Turn these into your assistant's actual guidelines and response patterns in [Prompt writing](/assistants/prompt-writing). ## Improving the script Treat your opening and objection handling as something to keep testing, not something to finish once: Conversion, median call duration, and where calls drop off — start from the campaign's own [progress and delivery figures](/campaigns/overview#monitoring-a-running-campaign) and the call-level detail in [History](/monitoring/history). For example: "a shorter opening increases appointment rate," or "naming the industry up front reduces early hang-ups." Split your audience into two comparable segments — a [custom attribute](/audience/contacts#custom-attributes) such as `test_group` is the simplest way to do it — then run the current script and the variant as two campaigns over the same window, so nothing but the script differs. Keep the winner, stop the losing campaign, and move on to the next hypothesis. ## What to measure Track the funnel stage by stage rather than a single top-line number — connect rate, meeting rate, and close rate each have different levers: | Metric | What it tells you | | ----------------------------- | ---------------------------------------------------------------------------------------- | | Reachability | Share of leads actually contacted | | Median call duration | Engagement — very short calls usually mean an early hang-up | | Appointment / deal conversion | How well a connected call turns into a next step | | Minutes per outcome | Cost efficiency, in the [minutes and credits](/billing/minutes) your plan already tracks | Compare cohorts — time window against time window, script version against script version, segment against segment — rather than reading a single campaign's numbers in isolation; the difference is what actually tells you something worked. Published SDR benchmark reports such as [The Bridge Group](https://www.bridgegroupinc.com/) are a useful outside reference for what "good" looks like at your stage. [Call QA averages](/audience/call-qa#call-qa-average) and [cohort QA runs](/assistants/ai-quality-assurance) add a quality signal alongside these outcome numbers. See also [Dialer, retries & compliance](/campaigns/dialer-and-compliance) and [Prompt writing](/assistants/prompt-writing).