The scoreboard, honestly: the hard targets, how often each one is actually looked at,
and the quiet human signals that never make it onto a dashboard.
Data Accuracy in Cleaned Datasets
The percentage of cleaned datasets that pass quality control checks without significant errors or inconsistencies.
Target · <2% error rateYou clean a dataset of 1,000 survey responses. If you find fewer than 20 minor errors (e.g., incorrect data types, missing values handled improperly) during a quality check, you're hitting the target.
Routine Report Turnaround Time
The average time it takes to deliver initial drafts of routine reports (e.g., concept test results, ad hoc survey summaries) from the moment final data is received.
Target · Within 48 hours for initial draftIf final survey data arrives on Monday morning, the first draft of the report should be in your manager's inbox by Wednesday morning, ready for review.
Survey Programming Accuracy
The percentage of surveys programmed that go live without requiring fixes to logic, skip patterns, or question display after the initial quality assurance (QA) check.
Target · 98% programmed correctly on first QAYou program 10 surveys in a month. If only one requires a minor tweak after QA (e.g., a skip logic error), you're doing well. If two or more need fixing, we need to look at the process.
Project Timeline Adherence
The percentage of research projects you own that are delivered on time, according to the agreed-upon project plan.
Target · 85% of projects delivered on scheduleYou manage 10 projects in a quarter. If 8 or 9 of them hit their deadlines, even with minor adjustments, you're on track. If more than two are consistently late, we'll need to figure out why.
Clarity and Actionability of Insights
How well your analysis translates into clear, understandable, and actionable recommendations for marketing teams.
- Stakeholders consistently say your reports are easy to understand and directly inform their next steps. They don't come back asking 'So what do we do now?' Your manager sees a clear story in your drafts, not just a dump of numbers.
Proactive Problem-Solving
Your ability to spot potential issues in data or project plans and suggest solutions before they become major problems.
- You flag potential issues with survey panel quality early on. You proactively suggest alternative analytical approaches when the data isn't quite right. Your manager rarely has to point out obvious problems you've missed.
Stakeholder Feedback on Collaboration
How effectively you work with internal marketing teams, understanding their needs and managing their expectations.
- Feedback from marketing managers indicates you're responsive, helpful, and good at explaining complex research concepts in plain English. They feel heard and understood, even if you can't always give them exactly what they want.
Methodological Soundness
The rigour and appropriateness of the research methods and statistical techniques you apply to projects.
- Your manager rarely finds methodological flaws in your analysis plans or reports. You can confidently explain why you chose a particular statistical test or sampling approach, and it stands up to scrutiny.