Which film reached more households?
Compare viewing time, runtime and the households shown each film.
The question
You prepare a first-week audience review for two fictional films in the same market.
| Runtime (min) | Hours watched | |
|---|---|---|
| Film A | 120 | 180000 |
| Film B | 60 | 120000 |
These totals count watch time. The distinct-household report has yet to arrive.
- AI summaryFilm A reached more households because it had more hours watched.
“What can you tell programming about the two audiences?”
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A strong answer, step by step
Open each step in turn. This is one strong answer, not the only one.
Step 1: What do the watch hours show?
What would you do here? Open the move you’d make.
Rank household reach by hours watched.
Tempting, but it misses something. The same household can contribute many hours.
Report watch time and request the distinct-household measure.
The strong move. This states what the table measures and identifies the missing evidence.
Treat each hour as one completed film.
Tempting, but it misses something. The two films have different runtimes and may be watched in part.
See how a strong candidate says it
“Film A generated 180,000 watch hours and Film B generated 120,000. I need distinct household counts to compare reach.”
Why it works: The totals sum time watched across playback sessions.
Step 2: What changes after you account for runtime?
What would you do here? Open the move you’d make.
Report 90,000 and 120,000 as distinct households.
Tempting, but it misses something. Households are not counted in that calculation.
Divide both watch totals by 60 because B is one hour long.
Tempting, but it misses something. Use each film’s own runtime in the same units as watch time.
Report 90,000 for A and 120,000 for B as runtime equivalents.
The strong move. This compares watch time relative to each film’s length.
See how a strong candidate says it
“Divide by runtime in hours. A has 90,000 full-runtime equivalents. B has 120,000. Partial and repeat viewing contribute to those totals.”
Why it works: This expresses how many full runtimes fit in the aggregated watch time.
Step 3: What did the exposure records add?
A’s card was shown to 200,000 distinct households and 100,000 started it. B’s card was shown to 500,000 and 150,000 started it. Each start count is deduplicated within the title and limited to households shown its card that week.
What would you do here? Open the move you’d make.
Use 150,000 versus 100,000 as proof B draws more interest in the same placement.
Tempting, but it misses something. B was shown to a larger group. The figures do not compare matched exposure.
Report reach and starts among exposed households together.
The strong move. B had more starting households and A had a higher observed start rate.
Average the two rates and use that result to rank both titles.
Tempting, but it misses something. The two denominators and placements are different.
See how a strong candidate says it
“B had more starting households in the observed placements. A had a 50% start rate among households shown its card. B had 30%, a gap of 20 percentage points.”
Why it works: The start rate uses the households shown each film. The absolute count also reflects how many households saw it.
Step 4: What would you tell programming?
What would you do here? Open the move you’d make.
Give the headline slot to A because 50% proves the film caused more interest.
Tempting, but it misses something. The comparison needs matched exposure or a controlled placement test.
Choose B because it has more full-runtime equivalents.
Tempting, but it misses something. That measure does not answer how the films would perform under equal exposure.
Report both measures and request a comparable placement check.
The strong move. This gives programming the observations and the next decision evidence.
See how a strong candidate says it
“B had more observed starts. A had a higher start rate among households shown its card. I would compare similar placements and audiences before deciding which film draws more starts under the same conditions.”
Why it works: The current report describes what viewers did after different exposure.
The answer, in short
- Decision
- Report the observed reach and start rates, then check comparable exposure.
- Because
- The films had different runtimes and were shown to different numbers of households.
- What would change it
- Results from comparable placements or a controlled exposure test.
Common traps
- Calling watch hours viewers.
- Treating runtime equivalents as completed films.
Check your answer
- What does watch time measure?
- What is the denominator for each start rate?
- How does placement affect interpretation?
- What would you check next?
Last reviewed Nov 11, 2026