Outbound call center metrics and formulas

An outbound program produces more numbers than anyone can watch, and two reports that both say "contact rate" can be dividing by different things. This guide defines the metrics Impact Dialing uses across its guides, gives the formula for each, and sorts them into the ones that deserve attention during a shift and the ones that can wait for a weekly review.

It doesn't quote industry benchmarks. Published figures mix inbound and outbound centers, consumer and business lists, and different formulas, so your own trend line, measured the same way every week, is the comparison that holds up.

List and dialing metrics

These describe what happens between the dialer and the list, before an agent's skill comes into play.

Metric	Formula	What it tells you
Connect rate	Calls answered by anyone or anything ÷ dials	How much of the list picks up at all, voicemail included
Contact rate	Calls answered by a live person ÷ dials	How reachable the list is at the hours you call
Right-party contact rate	Conversations with the intended person ÷ dials	How accurate the list is, since a live answer from the wrong person can't convert
List penetration	Records attempted at least once ÷ records loaded	How much of the list has been worked
Attempts per record	Total dials ÷ records attempted	How hard the list is being worked, and whether retry rules are too aggressive

Some dialers report a "connect" whenever a call reaches any answer, answering machines included, while others count only live people. Before comparing campaigns or vendors, check which definition each report uses, because the same week of calling can produce very different numbers under the two.

Agent time metrics

Metric	Formula	What it tells you
Average handle time (AHT)	(Talk time + hold time + after-call work) ÷ calls handled	How long each conversation takes from the agent's side, wrap-up included
Idle time	Time logged in and available with no call ÷ time logged in	How much paid time goes to waiting, the number a predictive dialer exists to shrink
Occupancy	(Talk time + hold time + after-call work) ÷ time logged in	The share of a shift agents spend handling calls
Contacts per agent hour	Live contacts ÷ agent hours logged in	Output per paid hour, comparable across shifts of different lengths

AHT feeds a predictive dialer's pacing math directly, so a longer script or a new after-call form changes pacing even when nobody has touched the dialer settings. Keep AHT on the screen for the first few sessions after any script or workflow change.

Outcome metrics

Metric	Formula	What it tells you
Conversion rate	Successful outcomes ÷ right-party contacts	Whether the conversation works, separate from whether the list does
Outcomes per agent hour	Successful outcomes ÷ agent hours logged in	The combined effect of list, dialer, and script
Cost per contact	Program cost for the period ÷ live contacts	What reaching a person costs
Cost per outcome	Program cost for the period ÷ successful outcomes	What each result costs

Define the successful outcome before the campaign starts, whether that's a sale, a pledge, a completed survey, or a voter's commitment to a plan to vote, and keep the definition fixed for the life of the campaign. Dividing conversions by right-party contacts keeps a weak list from making a good script look bad.

Compliance metrics

Metric	Formula	What it tells you
Abandonment rate	Abandoned calls ÷ calls answered by a live person, per campaign, per 30-day period	Whether a telemarketing campaign is inside the federal 3 percent cap
Do-not-call request rate	Do-not-call requests ÷ live contacts	A rising rate points to a list, timing, or script problem
Calls outside the window	Calls placed outside the allowed local hours	Should always be zero, and any count means a scheduling or time-zone fault

Abandonment is the easiest of these to compute wrong. The rule's denominator is calls answered by a live person, so a report that divides by all dials or all connects, voicemail included, will understate it. Abandonment rate and the 3 percent rule walks through the calculation with an example.

What to watch during a shift

During a calling session, keep campaign-to-date abandonment, agent idle time, and contact rate by hour in view. Those three move quickly and respond to dialer settings, and the article on optimizing predictive dialer settings covers what to change when they drift. If you're comparing dialing modes, predictive, power, and preview dialing explains why idle time and abandonment pull against each other.

Conversion, cost per outcome, and list penetration change slowly enough that a daily or weekly look is plenty, and they say more about the list and the script than about the dialer. When conversion moves, check the script first, using the testing approach in writing outbound call scripts, and the list second.