ROI calculator

What does checking your campaigns actually cost?

The AdOps ROI calculator converts the time a team spends checking Meta Ads campaigns into a monthly cost in Rupiah, then places a published AdOps plan price next to it. It prices five inputs the reader supplies — monthly Meta ad spend, ad accounts, live campaigns, hours per week, and the hourly cost of the person doing the checking — and estimates no saving of any kind.

Two figures, side by side: what an hour of your attention costs multiplied by the hours you spend, and what the AdOps plan covering your monthly ad spend costs. The arithmetic is written out in full further down the page.

Your numbers

Price your own checking time.

Change any of the five fields and every figure recalculates. Nothing is sent anywhere — the arithmetic runs in this browser tab and nothing is stored.

Your inputs

Five numbers. Everything else is derived from them.

What your team spends on Meta in a calendar month. This picks the plan.

Meta ad accounts your team is responsible for.

Campaigns running across those accounts right now.

Time spent reading numbers and changing budgets, not building creative.

Fully loaded cost per hour, in Rupiah. Salary ÷ 173 hours a month is a fair start.

What that comes to

Checking time
26hours a month
Cost of that time
Rp 3.900.000a month, at your hourly cost
AdOps plan for that spend · Plan 1k
Rp 1.000.000a month
  • 65 minutes of attention per campaign, per month
  • 8.7 hours per ad account, per month

At these numbers, 26 hours of checking a month cost Rp 3.900.000. The AdOps plan covering Rp 250.000.000 of monthly ad spend is Plan 1k, at Rp 1.000.000 a month — 26% of that figure.

Rp 2.900.000 a month more for the checking time than for the plan.

This calculator prices your own inputs and puts a published AdOps plan price next to them. It does not estimate hours AdOps would remove from your week, and AdOps publishes no such figure.

Worked example

One team, five inputs, every step shown.

A team putting Rp 250.000.000 a month through 3 Meta ad accounts and 24 live campaigns, spending 6 hours a week checking them, at Rp 150.000 an hour. These are the numbers the calculator above starts on.

Worked example of the AdOps ROI calculator: Rp 250.000.000 of monthly ad spend, 3 ad accounts, 24 live campaigns, 6 hours a week of checking at Rp 150.000 an hour, and how each derived figure is calculated.
Figure Value How it is derived
Monthly Meta ad spend Rp 250.000.000 Entered by the reader
Ad accounts 3 Entered by the reader
Live campaigns 24 Entered by the reader
Hours a week checking and adjusting 6 Entered by the reader
Hourly cost of the person doing it Rp 150.000 Entered by the reader
Weeks in a month 4.33 weeks 52 weeks ÷ 12 months
Checking time a month 26 hours 6 hours × 4.33 weeks
Cost of that time a month Rp 3.900.000 26 hours × Rp 150.000
Attention per campaign a month 65 minutes 26 hours × 60 ÷ 24 campaigns
AdOps plan covering Rp 250.000.000 a month Plan 1k Cheapest published plan whose ad-spend band reaches Rp 250.000.000
Plan price a month Rp 1.000.000 Published on the pricing page
Plan as a share of the checking cost 26% Rp 1.000.000 ÷ Rp 3.900.000
Difference a month Rp 2.900.000 Rp 3.900.000 − Rp 1.000.000

Both figures in the last three rows are monthly and in Rupiah. Neither is a saving: the right-hand figure is a published plan price, not a projection of what a team would stop spending.

The AdOps rule log: fourteen runs of one rule across two ad accounts, each showing execution time, applied items and affected tasks, beside a Rule details panel listing the six actions in the rule and its 30-minute schedule. Sample data
Every run of every rule, with how many items it read and how many tasks actually did something. Read the details

Method

How the arithmetic works, and what it refuses to do.

Five steps, one constant, and a hard stop before the part where most calculators start guessing.

  1. 01

    Add up the monthly ad spend

    Total what your team puts through Meta in a calendar month, across every ad account you plan to connect. This is the only figure that selects an AdOps plan, because it is the only axis AdOps prices on.

  2. 02

    Count the ad accounts and live campaigns

    Count the Meta ad accounts your team is responsible for and the campaigns currently running across them. Neither is capped by any plan; both are used only to show how thinly the hours are spread — minutes per campaign, hours per account.

  3. 03

    Estimate the hours a week

    Add up the time spent reading numbers, comparing periods and changing budgets in a normal week. Exclude creative production and reporting — this calculator prices checking and adjusting, not the whole job.

  4. 04

    Set the hourly cost

    Use the fully-loaded hourly cost of the person doing the checking, in Rupiah. A monthly salary divided by 173 working hours is a defensible starting point; an agency can use its billed rate instead.

  5. 05

    Read the two figures side by side

    The calculator multiplies hours a week by 52 ÷ 12 to get hours a month, multiplies that by the hourly cost, and prints the published price of the AdOps plan whose ad-spend band covers your monthly spend. Comparing them is your decision, not the calculator’s.

Every assumption, stated

  • A month is 52 ÷ 12 = 4.33 weeks. Using 4 would undercount the hours by 7.7%.
  • Checking time is assumed to be constant week to week. Launch weeks and sale periods are not modelled.
  • The hourly cost is whatever you enter. Nothing is inferred from your industry, seniority or location.
  • Plan prices are the published monthly prices in Rupiah, taken from the AdOps pricing page, before any tax your invoice applies.
  • The plan is selected by monthly ad spend alone — the cheapest published plan whose band reaches your figure. Nothing else about an AdOps account is capped by plan, so nothing else can move you up one.
  • A monthly spend above every published band selects Enterprise, which has no published price and so produces no percentage.
  • Spend is treated as a steady monthly figure. A month that spikes past the band means moving up a plan for that month, which this arithmetic does not pro-rate.

What this calculator does not say

It does not say AdOps saves you money, and it does not say AdOps saves you time. AdOps has no measured figure for hours removed from a marketer's week, so publishing one here would be an invention, and an invented number is worse than no number.

What the page does is narrower and checkable: it prices the hours you told it about at the rate you told it about, and prints a plan price that anyone can verify on the pricing page. What that comparison is worth is a judgement about your own team, and it stays yours.

See pricing

Your checking time has a price. Now compare it.

One rule, pointed at one ad account, does the work you just priced — and the plan that covers your spend covers every feature in the product. Decide whether the two figures are worth trading.

Contact us See pricing

Billed monthly in Rupiah · every feature on every plan

Inside the product

What the screens actually look like

Nine screens from the working dashboard — the rule builder, the metric picker, the dayparting grid and the log that records what happened. Scroll the strip.

  • The AdOps Performance Dashboard showing a Purchase ROAS card at 2.380x and an Aggregated ROAS card at 2.088x, both badged Profitable, a Monthly Budget card at Rp 155jt, and a Spend Breakdown ranking the top five ad accounts against a budget utilisation bar at 45.5 per cent.
    Performance Dashboard. Two ROAS figures to three decimals, a budget meter, and spend ranked by ad account — over Today, Last 7 days, Last 30 days or This month.
  • The AdOps rule list showing twelve automation rules, each with an on/off toggle, the ad accounts it manages, and when it last triggered — some minutes ago, others on a dated timestamp.
    Rule List. Every rule, what it manages and when it last fired. The toggle is the only thing between draft and live.
  • The AdOps condition builder showing a task with time-of-day conditions across seven day tags, a nested AND group holding a lifetime spend condition under 400,000, and a second task with four stacked metric conditions.
    Conditions. Metric, period, operator, value — joined with AND or OR, and nestable, so a rule can say something a dropdown cannot.
  • The AdOps metric picker open over a condition row: a panel with Meta Ads and Custom metrics tabs, a search box, and a scrolling list of metrics with Spend selected.
    Metric picker. Forty-five Meta metrics and your own sheet columns in the same list, each carrying a reporting period and any of six operators.
  • The AdOps dayparting timetable: a grid of hours against the seven days of the week, with the daytime hours filled navy for every day and the night hours and weekend evenings left empty.
    Dayparting grid. Or draw the hours instead. Anything outside the shape you fill in simply does not run.
  • An AdOps execution log detail: one campaign, two action panels badged Not Executed, each listing the action parameters and every condition evaluated with its actual value, its expected value and a Pass or Fail badge.
    Rule Log detail. Why a rule did nothing is recorded as carefully as why it did something — actual against expected, condition by condition.
  • The AdOps activity log listing budget increases and campaign renames, each row naming the affected campaign by id, the rule that caused it and how long ago it happened.
    Activity Log. One row per change AdOps made in your account, naming the campaign and the rule responsible.
  • The AdOps ad account list: eighteen Meta ad accounts with on/off toggles, account ids, Active or Inactive badges and this month’s spend in rupiah.
    Ad Accounts. Accounts discovered from Meta arrive switched off. Nothing is read, and nothing is changed, until you turn one on.
  • The AdOps custom metric editor mapping a Google Spreadsheet: a spreadsheet id, a sheet name, a column to match campaigns on and a column holding the values.
    Custom metric. Point AdOps at a sheet, name the matching column and the value column, and your own number joins the metric list.

Every figure is rebuilt from the product’s own interface and filled with invented data — no customer name, ad account or spend figure appears anywhere on this site. See how a run works