AP Syllabus focus:
‘Benchmark polls establish baseline views of a candidate, while tracking polls show how opinions about a candidate change during a campaign.’
Campaigns rely on polling to diagnose where they stand and whether strategy is working. Benchmark and tracking polls serve different timing and analytical purposes, helping campaigns interpret movement, not just snapshots.
Purpose of Benchmark vs. Tracking Polls
Benchmark polls: establishing a baseline
A benchmark poll is typically conducted early (often before or at the start of a general election campaign) to measure initial conditions: name recognition, candidate image, and vote intention.
Benchmark poll: An early campaign survey used to establish a baseline measure of candidate support and perceptions before major campaign activity or messaging changes.
Benchmark results function as a reference point for future comparisons, guiding strategic decisions such as which voter groups to prioritise and what issues to emphasise.
Tracking polls: measuring change over time
Tracking polls focus on trends by repeating the same or very similar questions at regular intervals, allowing campaigns to observe whether opinions are shifting.
Tracking poll: A repeated survey (daily, weekly, or periodically) that measures changes over time in candidate support or perceptions during a campaign.
Tracking is especially valuable after major events (debates, scandals, endorsements, major ads) because it helps distinguish temporary bumps from durable changes.
How Each Poll Type Shapes Campaign Dynamics
Strategic uses in real-time campaigning
Benchmark polls help campaigns:
Identify strengths/weaknesses in candidate image (competence, empathy, trust)
Pinpoint low-awareness groups needing name-ID boosts
Choose initial messaging themes and test vulnerabilities to opponent attacks
Tracking polls help campaigns:
Detect momentum or erosion among key blocs (e.g., independents, suburban voters)
Evaluate whether messaging, advertising, or field operations are moving numbers
Decide whether to pivot strategy (issue emphasis, tone, turnout vs persuasion)
Interpreting movement: signal vs noise
Changes seen in tracking data can reflect real shifts, but they can also be artefacts of measurement. Students should focus on whether a movement is:
Sustained across multiple waves rather than a one-day spike
Consistent across pollsters (reducing “house effect” concerns)
Plausible given campaign events and media environment
Design Features That Affect Comparability
Consistency is the core advantage of tracking
Tracking polls are most useful when they keep key elements stable:
A curve showing how the maximum margin of error shrinks as sample size increases (at a 95% confidence level). The figure helps students see why smaller samples (or smaller subgroups within a poll) produce noisier estimates, which can complicate comparisons across tracking waves. Source
Similar question wording and order
Similar mode (phone, online, mixed)
Similar sampling approach and weighting rules
If a campaign changes the likely-voter screen or switches modes midstream, apparent “change” may reflect methodology rather than public opinion.
Rolling samples and trend lines
Many tracking polls use rolling averages (e.g., a multi-day moving window).
A time-series line graph with an overlaid moving-average trend line, showing how smoothing reduces short-term volatility. This is analogous to campaign tracking polls that report multi-day rolling averages to highlight underlying trends while potentially delaying the visible impact of sudden events. Source
This can:
Smooth random variation
Delay the visible impact of a sudden event (because earlier interviews remain in the average)
Common Misuses and How to Avoid Them (Campaign and Media)
Treating a benchmark poll as a permanent forecast rather than a starting point
Overreacting to small tracking shifts within the margin of error
Ignoring the difference between “registered voters” and “likely voters,” which can change as turnout expectations evolve
Cherry-picking a single tracking release to claim “momentum” without showing a broader pattern
What AP Students Should Be Able to Do
Distinguish the baseline function of benchmark polls from the trend function of tracking polls
Explain how tracking data can inform campaign choices (resource allocation, message adjustment)
Evaluate whether claimed “movement” is credible based on consistency and repeated measurement, not one isolated data point
FAQ
Often weeks to months, depending on the race. Some campaigns run a benchmark, then begin tracking only once advertising, debates, or heavy media coverage starts to create measurable volatility.
Rolling averages reduce random sampling variation and produce a clearer trend line.
However, they can make sudden shifts appear more gradual because older interviews remain in the calculation.
A house effect is a pollster’s consistent lean due to methodology (sampling, weighting, mode).
It matters because comparing trends across different pollsters can confuse methodological differences with real opinion change.
Yes. Campaigns sometimes field a second “benchmark-style” poll to reset assumptions after major changes (new opponent, redistricting, major national event), but it functions more like a new baseline than continuous tracking.
Likely-voter models incorporate turnout assumptions that can shift as enthusiasm and mobilisation change.
Registered-voter samples can look more stable but may be less predictive of the electorate that actually votes.
Practice Questions
(2 marks) Distinguish between a benchmark poll and a tracking poll in the context of campaign dynamics.
1 mark: Defines benchmark poll as establishing an early baseline of candidate support/perceptions.
1 mark: Defines tracking poll as repeated measurement showing how opinions change over the campaign.
(5 marks) Explain two ways tracking polls can influence campaign strategy, and explain one reason why apparent changes in tracking results might be misleading.
1 mark: Identifies a correct strategic use (e.g., reallocating resources to key groups/states, adjusting messaging/issue emphasis, evaluating debate/ad effects).
1 mark: Explains how that use follows from observing changes over time.
1 mark: Identifies a second correct strategic use.
1 mark: Explains the second use with clear linkage to trend data.
1 mark: Gives one valid reason changes may mislead (e.g., margin of error, methodology changes, mode effects, rolling average lag, house effects) with brief explanation.
