A baseline survey is the first wave that decides what change can be evidenced — the methodology, the question families, the format, the report structure.
A baseline survey is the first-wave questionnaire that captures where participants stand before a program, so later waves can measure change. The design question that decides its worth is whether a follow-up will find the same person. Sopact runs the baseline onto the Outcome Thread, one participant record under a persistent Contact ID, so the midline and endline attach to that person instead of arriving as fresh anonymous rows.
Teams pour effort into the baseline questionnaire and almost none into how the next wave will rejoin it. Then the follow-up goes out as a new form, the responses come back anonymous, and matching them to the baseline becomes a spreadsheet chore that quietly loses everyone who changed a phone number or a name. The survey was good; the plan for continuity was missing.
Key takeaways
A baseline survey run in a standard tool produces a sheet of anonymous responses. Nothing in that sheet reserves a spot for the same respondent’s next answer, so when the follow-up arrives it is a second, unrelated sheet, and the link between them is whatever the analyst can reconstruct.
Sopact is record-centric: the baseline survey writes each response to a persistent Contact ID, so the follow-up attaches to the same Outcome Thread rather than a separate export you match by hand. See what makes a baseline worth keeping on baseline data, or the collection layer on longitudinal data collection software.
SurveyMonkey, Qualtrics, Google Forms, KoBoToolbox, SurveyCTO, and CommCare will all run a clean baseline, and most support a follow-up send. Each captures a wave well, and each stores that wave as its own dataset, so continuity across waves is left to whatever identifier you remembered to collect and can still trust later.
The one test that matters: ask the tool to open one participant’s record and show the baseline answer with a blank slot waiting for the follow-up, on the same ID. A form-per-wave tool cannot; it only has this wave. Sopact answers from the Outcome Thread, because the record persists between waves.
A baseline survey that rejoins cleanly does three things: it assigns a persistent Contact ID at first contact, it captures the open-text reason next to each rating so the follow-up has something to compare against, and it validates responses at intake so there is no cleanup debt carried into wave two.
Sopact does those three by default: the ID is persistent, the open-text is read on arrival against a codebook, and each response is checked as it lands on the Outcome Thread. That is what turns a baseline from a one-time file into the first entry on a record every later wave extends.
A standard baseline form ends when it closes; the Outcome Thread writes the baseline to a persistent Contact ID the follow-up rejoins. The difference is whether wave two matches automatically or by hand.
| The question | Baseline form | Outcome Thread |
|---|---|---|
| Reserve the person for wave two? | No: a standalone form | Yes: a persistent record |
| Match the follow-up? | By hand, on shaky IDs | Automatic, on one ID |
| Reason next to the rating? | In a separate column | On the record, on arrival |
| Cleanup before analysis? | Usually, per wave | No: validated at intake |
See what makes the baseline hold value on baseline data, or read a whole survey on survey analysis.
A finished dataset is a snapshot of where a cohort landed by the time you cleaned the last wave. The value of a response is highest the moment it arrives, when a participant slipping between the baseline and the midline can still be reached, not in a report written after the endline closed. That is the premise of the Loop, Sopact’s method for continuous intelligence: collect clean at the source, so each wave is validated at intake on a persistent Contact ID with no post-hoc cleanup; analyze on arrival, so each wave is read as it lands and the open-text is themed rather than set aside; improve in time, so a participant drifting between waves surfaces mid-program instead of after it.
The Loop is also what keeps a longitudinal finding defensible: every trajectory traces back to the same person’s answers across waves on one persistent ID, the standard detailed in Loop traceability, so a conclusion rests on the Outcome Thread rather than a hand-matched merge of three spreadsheets no one can re-check.
One method, three moves that never stop
Then the next wave reads a little sharper on the same record. Read the method: the Loop methodology →
The fastest way to see the continuity gap is to run it on your own data. Export a baseline and a later wave, each carrying a participant ID, then paste the prompts below into Sopact Sense’s Assistant, or reason through them with your team. The arrow above each links the Academy walkthrough with the expected output and tips.
Academy walkthrough → Analyze longitudinal survey data
Here are our baseline, midline, and endline responses, each row carrying the respondent’s persistent Contact ID: [ATTACH]. Match every wave to the same person by that ID, show each participant’s trajectory over time, quote the open-text behind any change, and keep it all on one Outcome Thread, so the change is a query over one record rather than a hand-matched join across three exports.
Academy walkthrough → Analyze pre, mid, and post data
Here are pre, mid, and post responses on the same participant IDs: [ATTACH]. For each person, line up the before, during, and after answers on their persistent Contact ID, compute the shift, quote the sentence that explains it, and keep every answer on the Outcome Thread, so a change is measured on one record instead of reconstructed from three anonymous sheets.
Academy walkthrough → Handle attrition across waves
Here are the responses to each wave with the respondent’s persistent Contact ID: [ATTACH]. Show me who answered the baseline but has not yet answered the latest wave, flag the drop-off by subgroup, and keep everyone on the Outcome Thread, so I can reach the people drifting away while the cohort is still reachable rather than discovering the gap after the study closes.
Academy walkthrough → Connect the number and the reason
Here is our quantitative data and the open-ended responses on the same participant IDs: [ATTACH]. For each rating, pull the open-text the same respondent wrote that explains it, quote the sentence, and show the number and the reason on one record, so a low score carries its reason on the Outcome Thread rather than sitting in a column with no explanation.
Each walkthrough is short and practical: what to do, the prompt to run, the output to expect, and the tips that keep it reliable.
Watch: collecting clean at the source on a persistent Contact ID and reading each wave on arrival, so a baseline and an endline attach to the same person on one Outcome Thread.
It is the first-wave questionnaire capturing where participants stand before a program, so later waves can measure change. Sopact runs it onto the Outcome Thread under a persistent Contact ID, so follow-ups attach to the same person rather than arriving as anonymous rows.
Assign a persistent ID at the baseline. Sopact does this by default, so the midline and endline attach to the same Outcome Thread instead of being merged by hand on name or email.
The measures you will re-ask later, plus an open-text reason next to each rating. Sopact reads that open-text on arrival on the Outcome Thread, so the follow-up has a defensible point of comparison.
Because they arrive as a new anonymous form and the join relies on data that changed. Sopact keeps every wave on one persistent Contact ID, so the match does not depend on a fragile identifier.
No. Sopact validates each response at intake, so the baseline is analyzable on arrival on the Outcome Thread rather than after a round of manual cleanup per wave.
Yes. Because everyone sits on the Outcome Thread, Sopact shows who answered the baseline but not the latest wave while you can still reach them, rather than after the study closes.
Those tools run each wave as its own dataset. Sopact writes the baseline to a persistent record, so later waves rejoin the same Outcome Thread instead of forming a separate export to match.
As many as the program runs. Sopact keeps every wave on one persistent ID, so a participant’s trajectory across baseline, midline, and endline reads from one Outcome Thread.
Next: see why the baseline holds value on baseline data, or run every wave on one record with longitudinal data collection software.
