You see the total invitations, daily volume, and an estimated cost.
The planner turns a complete-response target into estimated invitations, daily pace, and cost. It divides the target by your expected invitation completion rate, rounds invitations up, and uses the entered cost and collection days for the remaining outputs. The tool does not sell an audience, send invitations, or guarantee participation; every planning assumption comes from your inputs.
To collect 500 responses at an expected 25% rate, plan for 2,000 invitations. Over 10 days, that is 200 invitations and 50 responses per day. At $0.20 per invitation, estimated cost is $400, or $0.80 per response.
Add your numbers or start with sample data.
Complete the fields to see the result and interpretation here.
Here, expected completion rate is the share of invitations that become completed responses; it is not a standardized AAPOR response rate.
Channel, audience, survey length, and reminders all affect that rate.
Planning a buffer helps avoid finishing below the target.
Invitations = round up(responses ÷ expected rate). Per day = round up(invitations ÷ days); cost = invitations × cost per invitation.
The estimate depends on the rate you provide and cannot guarantee timing, cost, or participation.
No. This tool only calculates a plan from your inputs. Audience selection, channels, contacts, consent, and delivery remain your responsibility.
Use results from collections with a similar audience, channel, topic, and length. Without history, start conservatively and update the plan as the actual rate develops.
Estimated cost is invitations multiplied by cost per invitation. Cost per response divides that total by the complete-response target.
No. It uses exactly the rate entered. To create a buffer, use a more conservative expected rate or manually increase the response target.
The references support the definitions and assumptions. The formula used is shown on this page and covered by automated tests.
Put the learning into a real survey and track every response in NPSLab.