Scaler
Project briefing
How might we improve our ESG survey tool to better support property managers and consultants in collecting consistent, accurate, and complete data — while reducing the manual effort and back-and-forth communication that currently slows the process down?
Methods
- UX Research
- Design Workshops
- Prototyping
Tools
- Figma
- Miro
- PostHog
- Chat GPT
Scope
In scope
- Survey creation and recipient experience redesign.
- New information architecture for data collection flows.
- Survey logic and validation improvements.
- Prototype for survey input & review
- Templates for recurring ESG data collection
Out of scope
- Full integration with input portal & roadmap tool (handled in parallel tracks).
- Implementation of back-end changes.
Research sources
Quantitative research
We used PostHog to analyze usage patterns, completion rates, and drop-off points across active surveys to identify friction areas and dead ends.
Qualitative research
We conducted interviews with internal consultants, survey recipients (property managers), and platform users. Additional input was gathered through support tickets, field observations, and internal feedback sessions.
Quantitative results
Users are not using the current survey tool
There was poor adoption to the first version of the survey tool, therefore we need to identify why people are not using it.
Most survey tool use has been through consultants
Consultants are usually super users of the platform. Speak with them to see what their experience with the tool so far is and any improvements already identified.
Qualitative results
Consultants aren’t using the survey tool — they’re still using Excel.
Because of poor usability and limited flexibility, consultants fall back on sending Excel sheets to collect data. This creates a lot of manual back-and-forth, increases risk of human error, and adds overhead to track what’s missing, reviewed, or needs clarification.
Property managers struggle to understand what’s expected of them.
Surveys are often too complex, unclear, or overwhelming. Respondents don’t know what data is required vs. optional, don’t have contextual help, and aren’t given guidance on what each field means or how to fill it in. This leads to a lot of drop off.
Edits, empty fields and versioning aren’t handled well.
Once data is submitted, it’s hard to edit or review fields. Consultants want the ability to distinguish between editing current data vs. creating new versions, with full transparency on what’s been changed. Currently the whole process is very error prone.
Core issues identified
The scope and research combined we can define the following focus points for the redesign.
Clients are managing many assets per PM
Navigating between assets for a specific survey is time consuming as they need to return to the overview to do so. This is leading to recipients failing to complete all surveys.
Senders need the ability to send historic data
Users only had the ability to add new data, not edit any historical values. This essentially makes the tool useless as users cannot correct data when needed.
Handling empty fields and marking them with reasons
No way for the users to send back empty fields if they do not know certain data, or to leave comments per field if they do not know the answer.
Survey creator adding individual meters
The survey creators have no way to select individual meters, leading to a lack of knowledge of what they are actually sending to the recipients.
Additional painpoints from interviews
- “Surveys are not usable — they don’t know what they are looking for.”
- “We still rely on Excel templates and example files.”
- “Layout needs a full overhaul — too clunky.”
- “Survey forms aren’t mobile-friendly.”
- “They need to differentiate between current version vs. new version edits.”
- “No clear guidance on which surveys to fill out when.”
- “Requesting fields per asset is still too manual.”
Focus points
Survey clarity and context
Introduce help texts, tooltips, and better sectioning of questions by theme. Provide definitions inline to help users understand what each field means.
Flexible and modular survey creation
Let consultants select fields by section (e.g., Energy → Electricity Meters → Consumption), then select which assets and meters to include.
Better version control
Enable editing current data or creating a new version — clearly differentiate the paths and only show editable fields as needed.
Improved error handling and validation
Inline validation and warnings (e.g., both meter reading and consumption filled when only one should be), with suggestions and ability to add comments.
Handling unknown or missing data gracefully
Allow recipients to mark fields as unknown and add a reason why, reducing guesswork and clarifying missing inputs.
Review and comment workflows
Consultants can add comments per field and return only those with feedback, instead of sending everything back for review.
Forwarding and collaboration
Enable forwarding surveys internally within recipient organizations, tracking who fills in what.
Survey overview improvements
Visual progress indicators, field-level completion tracking, and outlier detection on consumption data for reviewers.
Concept definition & prototype
We created a new IA and interaction model in Figma, focusing on both sides of the journey:
Survey creator
Select fields → select assets/meters → assign recipients → send → review if needed → request changes → approve
Survey recipient
See assigned assets → guided data entry per section → submit → reviewer comments if needed
Validation & Implementation
We ran multiple feedback sessions with internal teams and external test users, testing key flows like survey creation, editing, field-level review, and forwarding. We also worked closely with consultants from Cooltree and CBRE to validate real use cases and fine-tune language and structure.
Lessons learned
Excel will always be part of the journey — embrace it.
Rather than fight it, we added functionality to export surveys as Excel templates and allow bulk re-uploads. This better fits property manager workflows and reduces friction.
Small UX improvements go a long way.
Just adding explanations, comments per field, and outlier warnings significantly improved the perceived usability of the tool.
Survey design is not just a data entry form — it’s a communication tool.
Clarity, flexibility, and feedback loops matter just as much as the actual fields. This project was as much about improving human collaboration as it was about improving forms.