---
title: 'Research Opportunity: Most Time-Consuming Tasks — Leanne'
source: notion
interviewee: Leanne
date: '2025-12'
type: opportunity-analysis
status: active
tags: [research, opportunities, fieldwork, ops, leanne]
---

> **Note:** A qualitative synthesis of this interview also exists at . This file contains the JTBD opportunity cards extracted from the same session.

---

# Understanding your most time consuming tasks - Leanne Dec 2025


### Opportunity #1: Reduce the time burden of multi-market data checking

- **Customer Statement:** “I [need]… it takes like *45 minutes an hour* to… check the data… because I have to go through each market individually.”
- **How Might We:** How might we help ops validate multi-market data quality without repeating the same checks market-by-market?
- **Context:** During fieldwork on multi-market trackers (e.g., Bord Bia Beef; 7–8 markets).
- **Supporting Evidence:**
    - Direct quote: “...it takes like 45 minutes an hour to like check the data because I have to go through each market individually...” (≈5:21)
- **Distinctness Check:** This is specifically about **multi-market repetition** (not the general pain of quality checks).

### Opportunity #2: Make survey-duration (LOI) checking easier in Decipher

- **Customer Statement:** “I [struggle]… with decipher… to get the duration of the survey you have to export a completely different set of data.”
- **How Might We:** How might we make LOI/duration validation available without separate exports?
- **Context:** Data checks in Decipher while fieldwork is live.
- **Supporting Evidence:**
    - Direct quote: “...with decipher the to get the duration of the survey you have to export a completely different set of data.” (≈5:21–6:10) EmpathyIQ Conversation_ underst…
- **Distinctness Check:** This is about **LOI extraction friction**, not bot/open-end review.

---

### Opportunity #3: Speed up open-ended response quality checks

- **Customer Statement:** “I [spend time]… scrolling and… looking for gibberish… classic bot responses…”
- **How Might We:** How might we help ops quickly detect gibberish/bot patterns in open ends?
- **Context:** First step of data checking; happens repeatedly during field.
- **Supporting Evidence:**
    - Direct quote: “...I check the open lens… just me scrolling and like looking for gibberish… the classic bot responses...” (≈6:35–7:20) EmpathyIQ Conversation_ underst…
- **Distinctness Check:** This is **open-end review** (separate from straight-lining, LOI, or trap questions).

---

### Opportunity #4: Handle multi-language open ends without manual translation hacks

- **Customer Statement:** “Unless the lead translated, which I just use excel’s little translate tool…”
- **How Might We:** How might we support reliable translation workflows for open-end review?
- **Context:** Open-end checking across markets/languages.
- **Supporting Evidence:**
    - Direct quote: “...unless the lead translated, which I just use excel’s little translate tool.” (≈6:35–6:55) EmpathyIQ Conversation_ underst…
- **Distinctness Check:** This is about **language/translation friction**, not the act of checking content.

---

### Opportunity #5: Catch “drop-off in effort” across multiple open ends per respondent

- **Customer Statement:** “Sometimes you’ll have someone who answers… fine, and then… next three… it’s like gibberish… they don’t care after that.”
- **How Might We:** How might we flag respondents whose quality degrades across later open ends?
- **Context:** Surveys with multiple open-ended questions.
- **Supporting Evidence:**
    - Direct quote: “...answers… the first time, fine… next three… it’s like gibberish… they don’t care after that.” (≈6:55–7:35) EmpathyIQ Conversation_ underst…
- **Distinctness Check:** This is specifically about **within-respondent quality drift**, not generic bot detection.

---

### Opportunity #6: Reduce subjectivity and inconsistency in quality decisions

- **Customer Statement:** “It seems like a very subjective process… I usually say… around four straight lined questions…”
- **How Might We:** How might we help standardise quality thresholds while still allowing context-specific judgement?
- **Context:** Removing respondents based on multiple signals (opens, straight-lining, LOI, traps).
- **Supporting Evidence:**
    - Direct quote: “...it seems like a very subjective process.” (≈10:12) and “...around four straight lined questions...” (≈9:00–9:40) EmpathyIQ Conversation_ underst…
- **Distinctness Check:** This is about **decision rules/governance**, not tooling mechanics.

---

## Individual JTBD Opportunity Cards

*The following cards were extracted from this interview session.*

---

# Align client expectations with realistic field timelines

Context (When/Where): Client-driven deadlines (esp. Musgrave).
Customer Statement: Clients want it tomorrow, but we can’t get 1000 completes in Ireland in four days; it’s minimum seven.
Distinctness Check: Expectation-setting distinct from provider tooling or QC operations.
How Might We: How might we set and defend realistic fieldwork timelines earlier to avoid crunch?
Opportunity #: 20
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈16:15–16:35
Supporting Evidence Quote: ...I'm not going to get 1000 people in Ireland in four days… it's a minimum of seven...
user: Leanne
---

# Avoid late-stage fieldwork extensions caused by delayed cleaning

Context (When/Where): Near end of field when cleaning reveals lots of removals.
Customer Statement: If we let the project fill up and then clean, we may need to go back out with only days left and extend fieldwork.
Distinctness Check: Timeline risk distinct from daily QC mechanics.
How Might We: How might we prevent end-of-field panic caused by late discovery of bad completes?
Opportunity #: 17
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈19:02–20:10
Supporting Evidence Quote: ...let the project fill up… cleaning… go back out… with only a day left… extend field work...
user: Leanne
---

# Capture feasibility feedback earlier at questionnaire stage

Context (When/Where): Questionnaire drafting → client approval stage.
Customer Statement: I’m not asked to give feedback on questionnaires; I want to review before it goes to clients.
Distinctness Check: Upstream prevention distinct from downstream QC or adoption enablement.
How Might We: How might we catch feasibility mismatches before client sign-off?
Opportunity #: 46
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈1:26–2:25
Supporting Evidence Quote: ...not… asked to give feedback on questionnaires… I want… reviewer questionnaire before it goes to clients…
user: Leanne
---

# Catch within-respondent quality drop-off across multiple open ends

Context (When/Where): Surveys with multiple open-ended questions.
Customer Statement: I see people answer fine at first and then later open ends become gibberish when they stop caring.
Distinctness Check: About quality drift within a single respondent over time, not generic bot detection.
How Might We: How might we flag respondents whose quality degrades across later open ends?
Opportunity #: 5
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈6:55–7:35
Supporting Evidence Quote: ...answers… the first time, fine… next three… it’s like gibberish… they don’t care after that.
user: Leanne
---

# Create a single operational tracker across proposals and projects (“The monster”)

Context (When/Where): Cross-project operational visibility.
Customer Statement: We used to have ‘The monster’ that tracked every proposal and project in one place.
Distinctness Check: End-to-end operational visibility broader than budget/CPI lookup alone.
How Might We: How might we give the team a single system of record across projects and steps?
Opportunity #: 29
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈29:55–30:40
Supporting Evidence Quote: ...something called… The monster… tracked every proposal, every project… in one place...
user: Leanne
---

# Deliver high-quality respondent data without consuming excessive ops time

Context (When/Where): During live fieldwork and pre-handoff cleaning (multi-market trackers, daily checks, removals)
How Might We: How might we help ops produce high-quality, analysis-ready respondent data with far less manual checking, exporting, and subjective decision-making?
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Sub-item: Reduce the time burden of multi-market data checking (Reduce%20the%20time%20burden%20of%20multi-market%20data%20checki%202e72425bf103819f962dfbafd46ec56e.md), Make survey-duration (LOI) checking easier in Decipher (Make%20survey-duration%20(LOI)%20checking%20easier%20in%20Deci%202e72425bf10381a7bd68f724918fdbee.md), Speed up open-ended response quality checks (Speed%20up%20open-ended%20response%20quality%20checks%202e72425bf1038123a3c4d8531808a846.md), Handle multi-language open ends without manual translation hacks (Handle%20multi-language%20open%20ends%20without%20manual%20tra%202e72425bf10381dd9994d9bbe1f075fd.md), Catch within-respondent quality drop-off across multiple open ends (Catch%20within-respondent%20quality%20drop-off%20across%20mu%202e72425bf103819f8116d3bf448d4d4c.md), Reduce subjectivity and inconsistency in quality decisions (Reduce%20subjectivity%20and%20inconsistency%20in%20quality%20d%202e72425bf103814d92a6f629c7fd099a.md), Support trap-question workflows that remove respondents after completion (Support%20trap-question%20workflows%20that%20remove%20respon%202e72425bf1038151ae13f195c9144517.md), Make straight-lining detection and removal more direct end-to-end (Make%20straight-lining%20detection%20and%20removal%20more%20di%202e72425bf10381b3bdeed0a320d561d1.md), Enable open-end cleaning/removal within the same tooling used for checks (Enable%20open-end%20cleaning%20removal%20within%20the%20same%20t%202e72425bf10381c9868cce348b23c648.md), Reduce “lots of downloading” during quality checks (Reduce%20%E2%80%9Clots%20of%20downloading%E2%80%9D%20during%20quality%20checks%202e72425bf103815a84c5da509afb3c96.md), Make it easier to apply “automatic exclusions” consistently (Make%20it%20easier%20to%20apply%20%E2%80%9Cautomatic%20exclusions%E2%80%9D%20con%202e72425bf10381d7b10fd52c74029e65.md), Support combined-signal scoring for borderline cases (Support%20combined-signal%20scoring%20for%20borderline%20cas%202e72425bf10381b78e33e378299afecb.md), Make “removal reasons” tracking less manual and less error-prone (Make%20%E2%80%9Cremoval%20reasons%E2%80%9D%20tracking%20less%20manual%20and%20le%202e72425bf103814ab9b6e905f250f6fe.md), Prevent trust-damaging quality issues that require retroactive explanations (Prevent%20trust-damaging%20quality%20issues%20that%20require%202e72425bf103812e93bbf29f8fd204f3.md), Improve handoff so researchers receive clean, understandable files (Improve%20handoff%20so%20researchers%20receive%20clean,%20unde%202e72425bf1038154af65f2bffefa213d.md), Reduce time spent answering researchers’ Q/Queue troubleshooting questions (Reduce%20time%20spent%20answering%20researchers%E2%80%99%20Q%20Queue%20t%202e72425bf103818398bad7032ee9b01f.md), Enable ops to deliver tables from tab specs so researchers don’t fight tooling (Enable%20ops%20to%20deliver%20tables%20from%20tab%20specs%20so%20res%202e72425bf10381d5910cfb82f2061e08.md), Enable bulk import/update to remove respondents (change status) efficiently (Enable%20bulk%20import%20update%20to%20remove%20respondents%20(c%202e72425bf10381788a9bc050cb26f07f.md), Make open-end coding decisions easier to explain and audit later (Make%20open-end%20coding%20decisions%20easier%20to%20explain%20a%202e72425bf10381f08adbde234448fcf3.md)
user: Leanne

## Definition:

Ensure respondent data is trustworthy and analysis-ready without requiring heavy manual effort. This includes faster multi-market validation, easier LOI/duration checks, scalable open-end quality review (including translation needs), clearer and less subjective removal rules (automatic and multi-signal), reduced tool-hopping/exports/downloads, bulk status updates, and automatic generation of removal logs and clean handoff files for researchers.

## Primary Outcome:

High-quality completes + faster, more defensible cleaning decisions
---

# Enable bulk import/update to remove respondents (change status) efficiently

Context (When/Where): Quality-based removals mid-field.
Customer Statement: I want to import data and change respondent status to remove people in bulk.
Distinctness Check: Bulk operations distinct from removal logging (Opp #13) and from detection signals.
How Might We: How might we let ops bulk-update respondent status using an import to speed removals?
Opportunity #: 39
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈35:33–36:05
Supporting Evidence Quote: ...ability to import data into a survey… remove people… import and just change their status...
user: Leanne
---

# Enable EmpathyIQ to support real-world study designs and adoption

Context (When/Where): Survey design/build decisions, capability-fit decisions, and internal adoption/enablement
How Might We: How might we make EmpathyIQ the default choice by supporting real-world methods and design patterns—while making constraints and best practices obvious to researchers?
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Sub-item: Reduce Decipher scripting time caused by unfamiliarity/complexity (Reduce%20Decipher%20scripting%20time%20caused%20by%20unfamilia%202e72425bf10381a386f7c14b342e7235.md), Reduce dependency on outsourced scripting for always-on trackers (Reduce%20dependency%20on%20outsourced%20scripting%20for%20alwa%202e72425bf103818480a9c4d88eea6ec3.md), Support advanced methods (MaxDiff, Conjoint) in EmpathyIQ (Support%20advanced%20methods%20(MaxDiff,%20Conjoint)%20in%20Em%202e72425bf103811b9d6fcfe18d8857c4.md), Support translations in EmpathyIQ for multi-language studies (Support%20translations%20in%20EmpathyIQ%20for%20multi-langua%202e72425bf103819a8802c5e90f384390.md), Support complex segmentations with reusable “golden scripting” logic (Support%20complex%20segmentations%20with%20reusable%20%E2%80%9Cgolde%202e72425bf1038115aa96c130f41f553e.md), Support split-sample list variants without complexity (Support%20split-sample%20list%20variants%20without%20complex%202e72425bf103811d933dd97faf165e8b.md), Support prioritisation rules (e.g., prioritise a brand/airline) as first-class logic (Support%20prioritisation%20rules%20(e%20g%20,%20prioritise%20a%20b%202e72425bf10381f68139e2345553749e.md), Enable rapid setup when time is compressed (avoid defaulting to Decipher) (Enable%20rapid%20setup%20when%20time%20is%20compressed%20(avoid%20%202e72425bf10381308666f67a40173d0d.md), Maintain a shared, visible list of platform constraints to reduce resentment (Maintain%20a%20shared,%20visible%20list%20of%20platform%20constr%202e72425bf10381e68605c49dca2544e9.md), Help researchers build firsthand understanding of platform constraints (Help%20researchers%20build%20firsthand%20understanding%20of%20%202e72425bf1038147a27ec3b23e42b6af.md), Prevent rework when researchers forget what’s feasible in Omni/platform (Prevent%20rework%20when%20researchers%20forget%20what%E2%80%99s%20feas%202e72425bf1038140a0b3e19ce7fe4d7b.md), Make duplicating/reusing an existing survey a fast, reliable path (Make%20duplicating%20reusing%20an%20existing%20survey%20a%20fast%202e72425bf10381b5b132dfe527005511.md)
user: Leanne

## Definition:

Enable EmpathyIQ to handle the study designs researchers actually need, while also reducing friction that drives teams back to Decipher. This includes supporting advanced methods (e.g., MaxDiff, Conjoint), translation workflows, complex segmentation and reusable logic, split-sample list variants, prioritisation rules, fast duplication/reuse for quick-turn work, and reducing scripting burden/dependency on external scripters. It also includes adoption enablement: keeping a shared constraints ledger, helping researchers build firsthand understanding of platform limits, and reducing rework caused by forgetting what is feasible.

## Primary Outcome:

More studies run in EmpathyIQ + less fallback to legacy tooling
---

# Enable open-end cleaning/removal within the same tooling used for checks

Context (When/Where): Using Display for straight-lining but open-end review elsewhere/manual.
Customer Statement: Display doesn’t help us check open ends and remove respondents based on them.
Distinctness Check: Specifically about open-end handling within Display; separate from straight-line detection itself.
How Might We: How might we let ops review + exclude poor open-end responses without switching tools?
Opportunity #: 9
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈8:55–9:25
Supporting Evidence Quote: ...display doesn’t have anything that will help us check the opens and remove them...
user: Leanne
---

# Enable ops to deliver tables from tab specs so researchers don’t fight tooling

Context (When/Where): Desired future workflow for next year role focus.
Customer Statement: I want to give researchers tables from their tab specs instead of them fighting their way through Queue.
Distinctness Check: About shifting output ownership (tables delivery), not only improving Queue usability.
How Might We: How might we streamline tab-spec → tables production and reduce researcher effort?
Opportunity #: 25
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈26:25–27:05
Supporting Evidence Quote: ...I give them tables rather than them having to… fight their way through queue.
user: Leanne
---

# Enable rapid setup when time is compressed (avoid defaulting to Decipher)

Context (When/Where): Time-compressed launches (e.g., client forgot to tell earlier).
Customer Statement: When I have to go quick, I default to copying/pasting in Decipher.
Distinctness Check: About speed under time pressure, distinct from feature gaps like MaxDiff/translation.
How Might We: How might we make rapid setup in EmpathyIQ as fast as “copy/paste and go” elsewhere?
Opportunity #: 43
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈39:10–39:40
Supporting Evidence Quote: ...had to go quick… I'll just copy paste in decipher...
user: Leanne
---

# Give Accounts access to the same operational truth (shared visibility)

Context (When/Where): Cross-functional coordination (ops and accounts).
Customer Statement: I need to send it to Kelly in accounts; they also want to look at it.
Distinctness Check: Stakeholder access distinct from building the tracker itself.
How Might We: How might we create shared visibility across ops + accounts without duplicate reporting?
Opportunity #: 32
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈30:55–31:15
Supporting Evidence Quote: ...send it to Kelly in accounts… an appetite… they can look at...
user: Leanne
---

# Give panel providers visibility into quotas/progress to reduce manual updates

Context (When/Where): Managing sample providers during fieldwork.
Customer Statement: If panels can access quotas, it takes work off me so I don’t have to update them daily.
Distinctness Check: External collaboration distinct from internal monitoring cadence.
How Might We: How might we share quota/progress views externally without extra admin work?
Opportunity #: 18
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈16:40–17:20
Supporting Evidence Quote: ...give panels access to like quotas… takes a lot of that off me... I don't have to… update them daily.
user: Leanne
---

# Handle multi-language open ends without manual translation hacks

Context (When/Where): Open-end checking across markets/languages.
Customer Statement: I need to check open ends in other languages, but I end up using Excel’s translate tool unless the lead translated.
Distinctness Check: Translation friction distinct from the act of open-end checking itself.
How Might We: How might we support reliable translation workflows for open-end review?
Opportunity #: 4
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈6:35–6:55
Supporting Evidence Quote: ...unless the lead translated, which I just use excel’s little translate tool.
user: Leanne
---

# Handle seasonality/holidays that reduce respondent availability

Context (When/Where): Fieldwork during holidays and seasonal lulls.
Customer Statement: During major holidays (Easter, summer, this time of year), people don’t want to take surveys and sample slows.
Distinctness Check: External seasonal constraint distinct from internal process/tooling.
How Might We: How might we plan and adapt sampling strategies around known seasonal response drops?
Opportunity #: 21
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈22:24–23:45
Supporting Evidence Quote: ...major holidays… people just obviously aren't… wanting to take a survey… Easter and the summer…
user: Leanne
---

# Help researchers build firsthand understanding of platform constraints

Context (When/Where): Internal adoption and learning.
Customer Statement: Because researchers aren’t using it, they don’t know what they don’t know.
Distinctness Check: Learning/engagement distinct from maintaining the constraints list (Opp #44).
How Might We: How might we encourage low-stakes usage so researchers understand capabilities before real projects depend on them?
Opportunity #: 45
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈42:30–42:55
Supporting Evidence Quote: ...they're not going in and using it… you don't know what you don't know...
user: Leanne
---

# Improve handoff so researchers receive clean, understandable files

Context (When/Where): End of field → analysis handoff.
Customer Statement: I need the data file clean and understandable before researchers get it.
Distinctness Check: Handoff quality to researchers distinct from respondent-level QC checks.
How Might We: How might we standardise exports so researchers don’t lose time fixing mislabeled variables/types?
Opportunity #: 23
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈25:30–26:25
Supporting Evidence Quote: ...make sure the data file is clean understandable… before the researchers get any of the files...
user: Leanne
---

# Improve invoicing operations so tracking isn’t ad-hoc

Context (When/Where): During/after projects; finance coordination.
Customer Statement: Invoicing on the operations side needs tracking; we’re trying to bring in a spreadsheet that tracks budgets.
Distinctness Check: Finance workflow distinct from launch handoff and project feasibility.
How Might We: How might we make invoicing status and budget tracking transparent and low-effort?
Opportunity #: 31
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈27:59–28:25
Supporting Evidence Quote: ...invoicing sort of operations… trying to bring in… a spreadsheet that tracks budgets...
user: Leanne
---

# Improve launch handoff so “this can go out now” includes the missing details

Context (When/Where): Internal handoffs from researchers to ops at launch.
Customer Statement: I get told ‘this can go out now’ and I’m like, ‘with what?’
Distinctness Check: Handoff completeness distinct from decision capture of costing options.
How Might We: How might we make ready-to-launch packages include all required parameters by default?
Opportunity #: 28
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈29:35–30:05
Supporting Evidence Quote: It'll just be like ‘this can go out now’ and I’m like, ‘with what?’
user: Leanne
---

# Improve workload visibility and team coordination

Context (When/Where): Team operations and project planning.
Customer Statement: There’s no communication on how busy people are; everyone is working individually rather than as a team.
Distinctness Check: Capacity visibility distinct from project-tracking/financial info availability.
How Might We: How might we help teams see capacity and project load without heavy process overhead?
Opportunity #: 33
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈31:00–31:35
Supporting Evidence Quote: ...no communication on how busy people are… everyone's just working individually, rather than a team.
user: Leanne
---

# Keep fieldwork on track despite provider and timeline constraints

Context (When/Where): Fieldwork operations, especially early-field monitoring and end-of-field risk periods
How Might We: How might we help the team hit completes on time without daily manual pushing, constant checking, or end-of-field surprises?
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Sub-item: Reduce dependency on daily manual checking to avoid quality surprises (Reduce%20dependency%20on%20daily%20manual%20checking%20to%20avoi%202e72425bf10381eabcefdafe32ddf6e7.md), Make soft-launch → full-launch validation more lightweight (Make%20soft-launch%20%E2%86%92%20full-launch%20validation%20more%20lig%202e72425bf10381c3aff0de3fa994b008.md), Reduce operational load when multiple projects run concurrently (Reduce%20operational%20load%20when%20multiple%20projects%20run%202e72425bf10381249db6f1962f41b4dd.md), Avoid late-stage fieldwork extensions caused by delayed cleaning (Avoid%20late-stage%20fieldwork%20extensions%20caused%20by%20de%202e72425bf103817c8f30cb1a88849870.md), Give panel providers visibility into quotas/progress to reduce manual updates (Give%20panel%20providers%20visibility%20into%20quotas%20progre%202e72425bf10381b1ab3be082ca981e2c.md), Reduce daily “push sample” effort required by self-serve providers (Reduce%20daily%20%E2%80%9Cpush%20sample%E2%80%9D%20effort%20required%20by%20self%202e72425bf103810b95ffca589d4df6e7.md), Align client expectations with realistic field timelines (Align%20client%20expectations%20with%20realistic%20field%20tim%202e72425bf103814484b3d152d6ef3e37.md), Handle seasonality/holidays that reduce respondent availability (Handle%20seasonality%20holidays%20that%20reduce%20respondent%202e72425bf103814fbf5ad01a5cb181ff.md)
user: Leanne

## Definition:

Keep studies moving to completion on schedule even when sample flow and capacity are constrained. This includes reducing reliance on daily manual monitoring and manual sample pushes, making launch validation lighter-weight, handling overlapping projects without linear time scaling, preventing late-stage extensions caused by delayed cleaning, giving providers visibility into quotas/progress, aligning client expectations with realistic timelines, and planning around seasonal/holiday participation drops.

## Primary Outcome:

Predictable timelines + fewer last-minute extensions and operational fire drills
---

# Maintain a shared, visible list of platform constraints to reduce resentment

Context (When/Where): Internal adoption of EmpathyIQ; expectation management.
Customer Statement: We should keep track of things we can’t do; otherwise resentment builds.
Distinctness Check: Change-management transparency distinct from building capabilities themselves.
How Might We: How might we maintain an up-to-date constraints ledger that reduces repeated surprises and rebuilds trust?
Opportunity #: 44
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈41:39–42:05
Supporting Evidence Quote: ...keep track of all the things that we can't do… resentment…
user: Leanne
---

# Make “removal reasons” tracking less manual and less error-prone

Context (When/Where): After removals; provider compliance and audit trail.
Customer Statement: I have to create a spreadsheet listing removals and reasons; it’s very manual.
Distinctness Check: Documentation/audit output distinct from making removal decisions.
How Might We: How might we auto-generate removal logs (IDs + reasons) as part of cleaning?
Opportunity #: 13
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈13:00–13:35
Supporting Evidence Quote: ...create a spreadsheet… all of the removals… reasons… It's very manual.
user: Leanne
---

# Make duplicating/reusing an existing survey a fast, reliable path

Context (When/Where): Reusing existing instruments (trackers/quick-turn builds).
Customer Statement: I want it to be easier to duplicate and go straight from there (instead of rebuilding).
Distinctness Check: Reuse/duplication distinct from general “go quick” time pressure (Opp #43).
How Might We: How might we enable fast duplication/reuse workflows so setup is consistently quick?
Opportunity #: 49
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈39:40–39:58
Supporting Evidence Quote: ...easier sometimes to just duplicate in decipher and then go straight from there.
user: Leanne
---

# Make it easier to apply “automatic exclusions” consistently

Context (When/Where): Respondent removal decisions during cleaning.
Customer Statement: Some cases are automatic: gibberish open ends or failing trap questions means they’re gone.
Distinctness Check: About consistent application of clear-cut rules, not detection.
How Might We: How might we codify “automatic exclusion” rules so removals are faster and defensible?
Opportunity #: 11
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈10:55–11:25
Supporting Evidence Quote: ...gibberish… you're gone… failing trap questions… Automatic exclusion.
user: Leanne
---

# Make open-end coding decisions easier to explain and audit later

Context (When/Where): Post-field questions from researchers/clients about coding decisions.
Customer Statement: When asked about open-end coding differences, I need to explain why I coded it differently.
Distinctness Check: Auditability of coding distinct from open-end quality review/removal (Opp #3/#9).
How Might We: How might we preserve rationale for coding changes so ops can answer questions quickly later?
Opportunity #: 47
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈2:52–3:35
Supporting Evidence Quote: ...asked… did some open end coding… coded it slightly different… explanation...
user: Leanne
---

# Make project launch and operations information discoverable and actionable

Context (When/Where): Pre-launch preparation, internal handoffs, and ongoing ops/finance coordination
How Might We: How might we ensure ops can launch and run projects confidently with a complete, up-to-date source of truth—without chasing people or spreadsheets?
Parent Opportunity: Make project launch and operations information discoverable and actionable
Sub-item: Provide a single place to find budget/CPI/specs at launch time (Provide%20a%20single%20place%20to%20find%20budget%20CPI%20specs%20at%202e72425bf10381abb13ed8103f46dc50.md), Reduce back-and-forth to confirm which costing option was approved (Reduce%20back-and-forth%20to%20confirm%20which%20costing%20opt%202e72425bf103819abc59f0414c761af5.md), Improve launch handoff so “this can go out now” includes the missing details (Improve%20launch%20handoff%20so%20%E2%80%9Cthis%20can%20go%20out%20now%E2%80%9D%20in%202e72425bf103819292eaf8866b0a1a31.md), Create a single operational tracker across proposals and projects (“The monster”) (Create%20a%20single%20operational%20tracker%20across%20proposa%202e72425bf10381a2ba18ce210a8f25b4.md), Track CPI and field changes as they evolve (live updates) (Track%20CPI%20and%20field%20changes%20as%20they%20evolve%20(live%20u%202e72425bf10381d5a0a1f51ab0b21f9a.md), Improve invoicing operations so tracking isn’t ad-hoc (Improve%20invoicing%20operations%20so%20tracking%20isn%E2%80%99t%20ad-%202e72425bf10381098699e7e1f1e2e4e7.md), Give Accounts access to the same operational truth (shared visibility) (Give%20Accounts%20access%20to%20the%20same%20operational%20truth%202e72425bf103811b9d1de25ce391737c.md), Improve workload visibility and team coordination (Improve%20workload%20visibility%20and%20team%20coordination%202e72425bf103814d9111e1282b355099.md), Provide a lightweight, reliable project-management workflow (beyond spreadsheets) (Provide%20a%20lightweight,%20reliable%20project-management%202e72425bf10381fca83eec7258bc3cc4.md), Capture feasibility feedback earlier at questionnaire stage (Capture%20feasibility%20feedback%20earlier%20at%20questionna%202e72425bf103811dae1ceb4f5f5bd655.md)
user: Leanne

## Definition:

Make it easy for ops (and adjacent teams like Accounts) to find and act on the information needed to launch and run projects. This includes having a single place for budget/CPI/specs, capturing which costing option was approved, ensuring 'ready to launch' handoffs include all required parameters, maintaining an end-to-end operational tracker across proposals and projects, tracking CPI/field changes over time, improving invoicing/budget tracking, enabling shared visibility with Accounts, improving workload/capacity visibility, and capturing feasibility feedback earlier at questionnaire stage to prevent downstream rework.

## Primary Outcome:

Fewer launch delays + fewer clarification loops + better cross-team alignment
---

# Make soft-launch → full-launch validation more lightweight

Context (When/Where): Launch moments (soft launch and immediately after full launch).
Customer Statement: I check at soft launch like it’s full launch, then do the biggest check after full launch.
Distinctness Check: Specific to launch checkpoints, not ongoing monitoring.
How Might We: How might we validate launch readiness with fewer steps while preserving confidence?
Opportunity #: 15
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈14:03–14:40
Supporting Evidence Quote: ...when I soft launch, I'll check… then after the full launch… biggest data check...
user: Leanne
---

# Make straight-lining detection and removal more direct end-to-end

Context (When/Where): Data cleaning mid-field; switching between tools.
Customer Statement: To check straight-lining I export an SPSS file and load it into Display to run the report.
Distinctness Check: Focused on workflow fragmentation across tools for straight-line detection.
How Might We: How might we reduce exports and tool-hops required to detect straight-liners?
Opportunity #: 8
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈8:45–9:20
Supporting Evidence Quote: I'll export the SPSS file and put it in the display app to then do a straight line… report.
user: Leanne
---

# Make survey-duration (LOI) checking easier in Decipher

Context (When/Where): Data checks in Decipher while fieldwork is live.
Customer Statement: I struggle to get the duration of the survey in Decipher because I have to export a completely different set of data.
Distinctness Check: About LOI extraction friction, not open-end review or straight-lining.
How Might We: How might we make LOI/duration validation available without separate exports?
Opportunity #: 2
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈5:21–6:10
Supporting Evidence Quote: ...with decipher the to get the duration of the survey you have to export a completely different set of data.
user: Leanne
---

# Prevent rework when researchers forget what’s feasible in Omni/platform

Context (When/Where): Study design and build decisions before field.
Customer Statement: We need researchers to remember what is feasible and what shouldn’t go in (Omni).
Distinctness Check: Feasibility memory aid distinct from general platform learning (Opp #45).
How Might We: How might we reduce rework by surfacing feasibility constraints at design time?
Opportunity #: 48
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈35:16–35:23
Supporting Evidence Quote: ...providing the researchers remember what is actually feasible and what should and shouldn't go in [Omni]…
user: Leanne
---

# Prevent trust-damaging quality issues that require retroactive explanations

Context (When/Where): After issues slip through (e.g., quality problems in a market).
Customer Statement: Having to retroactively explain issues is embarrassing and puts quality into question.
Distinctness Check: Trust/reputation impact distinct from operational time savings.
How Might We: How might we reduce the chance of quality incidents that damage trust and create rework?
Opportunity #: 22
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈19:50–20:52
Supporting Evidence Quote: ...retroactively explain… it's embarrassing… you don't want… quality… thrown into question...
user: Leanne
---

# Provide a lightweight, reliable project-management workflow (beyond spreadsheets)

Context (When/Where): Organisational operations improvement (after notable project pain).
Customer Statement: There’s appetite for a more organised workflow so projects stay on track and workloads are managed.
Distinctness Check: About workflow/process enablement, distinct from visibility (Opp #33).
How Might We: How might we implement simple PM workflows that prevent work slipping without bureaucracy?
Opportunity #: 34
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈30:55–31:30
Supporting Evidence Quote: ...appetite to get… a bit more of an organised workflow… projects staying on track… managing people's workloads...
user: Leanne
---

# Provide a single place to find budget/CPI/specs at launch time

Context (When/Where): Project launch prep, especially for projects costed before she joined.
Customer Statement: There’s no easy place where the budget and CPI are placed; it’s not readily available.
Distinctness Check: Information retrieval at launch distinct from invoicing workflow execution.
How Might We: How might we make project financials/specs discoverable at the moment ops needs them?
Opportunity #: 26
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈28:19–28:55
Supporting Evidence Quote: ...no easy place where the budget has been placed. The CPI... none of that information is readily available.
user: Leanne
---

# Reduce “lots of downloading” during quality checks

Context (When/Where): Routine daily checking workflows.
Customer Statement: I spend a lot of time downloading/exporting during checks, and that’s why it takes so long.
Distinctness Check: Meta opportunity about volume of exports/download steps (cross-cutting).
How Might We: How might we minimise export/download steps required to validate data quality?
Opportunity #: 10
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈9:35–10:05
Supporting Evidence Quote: There’s a lot of downloading that happens. This is why it takes so long.
user: Leanne
---

# Reduce back-and-forth to confirm which costing option was approved

Context (When/Where): After quotes return and project gets go-ahead.
Customer Statement: After we provide options, I still have to ask which option we went for.
Distinctness Check: Decision capture distinct from storing budget/CPI info.
How Might We: How might we lock decision context (selected option + rationale) so ops can act without chasing?
Opportunity #: 27
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈29:00–29:35
Supporting Evidence Quote: ...shopping trolley of options... and then... which option have we went for?
user: Leanne
---

# Reduce daily “push sample” effort required by self-serve providers

Context (When/Where): Fieldwork with PR Spectrum (self-serve).
Customer Statement: With PR Spectrum being self-serve, I have to push sample anyway (often daily).
Distinctness Check: Provider-specific operational burden distinct from QC checking.
How Might We: How might we keep field momentum without constant manual sample deployments?
Opportunity #: 19
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈15:40–16:10
Supporting Evidence Quote: ...PR spectrum… being self-serve you have to anyways...
user: Leanne
---

# Reduce Decipher scripting time caused by unfamiliarity/complexity

Context (When/Where): When scripting changes on trackers in Decipher.
Customer Statement: Decipher takes me longer to script because I’m not familiar with XML.
Distinctness Check: Authoring friction distinct from fieldwork QC and provider management.
How Might We: How might we reduce the learning curve and time cost of Decipher scripting?
Opportunity #: 35
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈32:12–32:55
Supporting Evidence Quote: ...it takes me a little bit longer to script in decipher… not familiar with XML...
user: Leanne
---

# Reduce dependency on daily manual checking to avoid quality surprises

Context (When/Where): Fieldwork operations cadence; early field especially.
Customer Statement: I always check daily—especially the first five days—so issues don’t slip through.
Distinctness Check: About monitoring cadence, not a specific QC task.
How Might We: How might we detect quality issues early without requiring daily manual vigilance?
Opportunity #: 14
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈13:38–14:10
Supporting Evidence Quote: ...I will always check stuff daily… in the first… five days it's daily...
user: Leanne
---

# Reduce dependency on outsourced scripting for always-on trackers

Context (When/Where): Continuous trackers and frequent tweaks.
Customer Statement: Because trackers are always on, I don’t get enough time, so it’s easier to hand changes to an external scripter.
Distinctness Check: Operational dependency distinct from general Decipher scripting difficulty (Opp #35).
How Might We: How might we make routine tracker changes easier to implement without external handoffs?
Opportunity #: 36
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈33:39–33:55
Supporting Evidence Quote: ...they're always on… I don't get as much time… it's just easier to be like to JTS...
user: Leanne
---

# Reduce operational load when multiple projects run concurrently

Context (When/Where): Multiple omnis/tracker projects overlapping.
Customer Statement: If I have three projects out at the same time, checking takes about an hour to an hour and a half.
Distinctness Check: Concurrency across studies distinct from multi-market complexity within one study.
How Might We: How might we help ops manage concurrent studies without linear time scaling?
Opportunity #: 16
Parent Opportunity: Keep fieldwork on track despite provider and timeline constraints
Parent item: Keep fieldwork on track despite provider and timeline constraints (Keep%20fieldwork%20on%20track%20despite%20provider%20and%20timel%202e72425bf10381c18173e4a86f97861b.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈14:40–15:10
Supporting Evidence Quote: ...all three… at the same time… about an hour and an hour and a half...
user: Leanne
---

# Reduce subjectivity and inconsistency in quality decisions

Context (When/Where): Removing respondents based on multiple signals (opens, straight-lining, LOI, traps).
Customer Statement: Quality removal feels subjective; I usually decide based on patterns like around four straight-lined questions.
Distinctness Check: About decision governance/consistency, not any single QC check workflow.
How Might We: How might we help standardise quality thresholds while still allowing context-specific judgement?
Opportunity #: 6
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈9:00–10:12
Supporting Evidence Quote: ...it seems like a very subjective process… I usually say… around four straight lined questions…
user: Leanne
---

# Reduce the time burden of multi-market data checking

Context (When/Where): During fieldwork on multi-market trackers (e.g., Bord Bia Beef; ~7–8 markets).
Customer Statement: I need to check the data across markets, but it takes like 45 minutes to an hour because I have to go through each market individually.
Distinctness Check: Specific to repetitive market-by-market checking (separate from general QC tasks).
How Might We: How might we help ops validate multi-market data quality without repeating the same checks market-by-market?
Opportunity #: 1
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈5:21
Supporting Evidence Quote: ...it takes like 45 minutes an hour to like check the data because I have to go through each market individually...
user: Leanne
---

# Reduce time spent answering researchers’ Q/Queue troubleshooting questions

Context (When/Where): Post-field tabulation and troubleshooting.
Customer Statement: I field a lot of Queue questions because Queue behaves weirdly and you have to do a lot of stuff.
Distinctness Check: Analysis tooling friction distinct from fieldwork/scripting issues.
How Might We: How might we make tables/export behaviour predictable so researchers can self-serve?
Opportunity #: 24
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈26:05–26:50
Supporting Evidence Quote: ...field a lot of queue questions… queue just sometimes is like… and then you've got to do a whole lot of stuff.
user: Leanne
---

# Speed up open-ended response quality checks

Context (When/Where): First step of data checking; repeated during fieldwork.
Customer Statement: I spend time scrolling through open ends looking for gibberish or classic bot responses.
Distinctness Check: Specifically about open-end review; separate from LOI, traps, or straight-lining.
How Might We: How might we help ops quickly detect gibberish/bot patterns in open ends?
Opportunity #: 3
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈6:35–7:20
Supporting Evidence Quote: ...I check the open lens… just me scrolling and like looking for gibberish… the classic bot responses...
user: Leanne
---

# Support advanced methods (MaxDiff, Conjoint) in EmpathyIQ

Context (When/Where): Methodology requirements drive platform choice.
Customer Statement: MaxDiffs and conjoints can’t currently be done in EmpathyIQ.
Distinctness Check: Capability gap distinct from translation support or workflow speed.
How Might We: How might we make advanced quant methods possible so studies don’t need to stay in Decipher?
Opportunity #: 37
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈34:00–34:10
Supporting Evidence Quote: Max diffs, conjoints… currently can't be done in empathy IQ.
user: Leanne
---

# Support combined-signal scoring for borderline cases

Context (When/Where): Borderline respondents where no single signal is enough.
Customer Statement: If it’s not automatic, you need two or more issues to remove someone.
Distinctness Check: Decision logic for borderline cases, distinct from the signals themselves.
How Might We: How might we help ops combine weak signals into a clear remove/keep outcome?
Opportunity #: 12
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈11:20–12:10
Supporting Evidence Quote: ...if it's not… automatic, you have to be two or more to… be removed...
user: Leanne
---

# Support complex segmentations with reusable “golden scripting” logic

Context (When/Where): Studies relying on pre-defined segmentation schemes and logic.
Customer Statement: We need some sort of golden scripting to input proper segmentation.
Distinctness Check: Advanced routing/logic distinct from advanced methods (Opp #37) or translations (Opp #38).
How Might We: How might we support segmentation logic that is reliable and reusable across studies?
Opportunity #: 40
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈36:13–36:40
Supporting Evidence Quote: ...need… golden scripting… input like a proper segmentation…
user: Leanne
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# Support prioritisation rules (e.g., prioritise a brand/airline) as first-class logic

Context (When/Where): Survey designs requiring ordered exposure or prioritised elements.
Customer Statement: Clients need prioritisation (e.g., prioritise SuperValu; prioritise Ryanair in conjoint).
Distinctness Check: Priority ordering rules distinct from split-sample or segmentation.
How Might We: How might we encode and manage prioritisation rules without fragile custom work?
Opportunity #: 42
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈38:44–39:20
Supporting Evidence Quote: ...prioritisation… prioritising brands… prioritise super value… Ryanair…
user: Leanne
---

# Support split-sample list variants without complexity

Context (When/Where): Common client design requests (trackers and other quant studies).
Customer Statement: Half the sample needs to see a list one way and the other half another way; sometimes split into three groups.
Distinctness Check: Experimental design pattern distinct from segmentation or prioritisation rules.
How Might We: How might we make split-sample list presentation easy to implement and verify?
Opportunity #: 41
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈38:09–38:44
Supporting Evidence Quote: ...half the sample needs to see the list one way… split sample into three groups…
user: Leanne
---

# Support translations in EmpathyIQ for multi-language studies

Context (When/Where): Multi-language client requirements (e.g., French Canadian).
Customer Statement: Translations are a big reason we keep surveys in Decipher; I had to do English and French Canadian in Decipher for translation.
Distinctness Check: Translation enablement distinct from advanced methods (Opp #37).
How Might We: How might we streamline multi-language survey authoring and deployment in EmpathyIQ?
Opportunity #: 38
Parent Opportunity: Enable EmpathyIQ to support real-world study designs and adoption
Parent item: Enable EmpathyIQ to support real-world study designs and adoption (Enable%20EmpathyIQ%20to%20support%20real-world%20study%20desig%202e72425bf1038102b1a6f519a2e5e922.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈34:18–34:55
Supporting Evidence Quote: ...one in English and one in French Canadian… asked me to do… in decipher so that we could have the translation…
user: Leanne
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# Support trap-question workflows that remove respondents after completion

Context (When/Where): Data-quality design + cleaning workflow (e.g., Musgrave).
Customer Statement: I need to let people complete the survey and then remove those who fail trap questions.
Distinctness Check: Trap-question mechanics distinct from straight-lining or LOI checks.
How Might We: How might we enable trap-question handling that doesn’t interrupt field but cleans data reliably?
Opportunity #: 7
Parent Opportunity: Deliver high-quality respondent data without consuming excessive ops time
Parent item: Deliver high-quality respondent data without consuming excessive ops time (Deliver%20high-quality%20respondent%20data%20without%20consu%202e72425bf1038162a542c3f72f07f483.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈8:05–8:45
Supporting Evidence Quote: ...let them go through the whole survey… and just remove them as fails trap questions.
user: Leanne
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# Track CPI and field changes as they evolve (live updates)

Context (When/Where): When sampling costs or field conditions change midstream.
Customer Statement: We need a tracker with live updates of CPI changes and any changes in field.
Distinctness Check: Dynamic cost drift distinct from initial budget discoverability.
How Might We: How might we keep pricing/time-in-field changes visible and propagated automatically?
Opportunity #: 30
Parent Opportunity: Make project launch and operations information discoverable and actionable
Parent item: Make project launch and operations information discoverable and actionable (Make%20project%20launch%20and%20operations%20information%20dis%202e72425bf10381268a9cd51c803f4fd5.md)
Source Document: EmpathyIQ Conversation_ understanding your most time consuming tasks (3).docx
Supporting Evidence Location: ≈30:25–30:55
Supporting Evidence Quote: ...a survey costs tracker… live update of CPI changes… any changes in field...
user: Leanne