The short answer
The Indellia voice of customer template is a free 13-column CSV for logging VoC records at SKU level. Columns: source, date, channel, SKU, ASIN, UPC, product name, review text, sentiment score, theme, priority, responded flag, response date. Open the file in Google Sheets or Excel and begin tagging. The template is the honest starting point for brands running VoC manually before moving to a platform.
What you get
A CSV file with 13 pre-defined columns and four example rows showing correct formatting for each source type (Amazon review, Walmart review, Zendesk ticket, Loop Returns return reason). The file weighs under 5KB and opens in any spreadsheet tool.
The template is intentionally minimal. It's the smallest schema that captures the information a consumer-brand VoC program actually needs. Anything narrower misses critical fields; anything broader adds columns most teams never fill in consistently.
The 13 columns, one by one
- source — the system or platform the feedback came from. Values: amazon, walmart, best_buy, costco, lowes, target, home_depot, bazaarvoice, zendesk, intercom, freshdesk, gorgias, loop_returns, narvar, typeform, etc.
- date — ISO date of the feedback record (YYYY-MM-DD). For reviews, use the review-posted date; for tickets, the ticket-created date.
- channel — a finer-grained source attribution. For example, source=amazon + channel=amazon_us, or source=zendesk + channel=support_ticket. Lets you filter by country or ticket type.
- sku — your internal SKU or Model#. This is the column that makes SKU-level analysis possible.
- asin — Amazon ASIN if the record came from Amazon or can be linked to an Amazon listing. Leave blank for non-Amazon records that don't have an ASIN.
- upc — the 12-digit UPC for the product. Cross-retailer linking via UPC is useful when SKUs don't match retailer-specific identifiers.
- product_name — human-readable product name. Helps during manual review.
- review_text — the verbatim text of the feedback. For surveys, include the free-text response. For tickets, include the customer's initial message. For returns, include the return reason text.
- sentiment — polarity score from -1.0 (strongly negative) to +1.0 (strongly positive). For manual tagging, use -1.0, -0.5, 0, +0.5, +1.0 as a five-point scale.
- theme — the primary theme from your taxonomy. Use lowercase-with-hyphens convention (battery-life, setup-difficulty, packaging-damage, documentation-unclear).
- priority — manual priority rating: low, medium, high. Drives which records get acted on first.
- responded — has a response been posted (for reviews) or sent (for tickets)? Values: yes, no.
- response_date — date the response was posted or sent. Blank if not yet responded.
How to set the template up
Step 1 — download the CSV. Step 2 — import it into Google Sheets (File → Import → Upload) or Excel (File → Open). Step 3 — delete the four example rows; keep the header row. Step 4 — set column data validations: source, channel, sentiment, theme, priority, and responded should all have drop-down lists rather than free text.
Step 5 — define the taxonomy (the set of valid theme values) in a second sheet. Share the taxonomy with Product, CX, and QA leads before logging starts. Step 6 — set a weekly cadence for review: every Monday, triage new records by priority, act on the high-priority ones, close the loop.
The template is the smallest schema that captures what a consumer-brand VoC program needs. Anything narrower misses critical fields; anything broader never gets filled consistently. Indellia — Template design
Taxonomy guidance
A good starter taxonomy has 15–25 top-level themes — enough to distinguish the common complaint and praise categories, few enough that every tagger remembers them without looking up.
Useful seed themes for consumer electronics and appliances: battery-life, setup-difficulty, design, build-quality, performance, features, accessories, packaging, shipping, documentation, app-experience, value-for-money, durability, customer-support, defect-reliability. Adjust for your category.
Document one-sentence definitions for each theme to keep tagging consistent across people. Two different taggers should arrive at the same theme 80%+ of the time on the same record; if they disagree more often, the definitions are ambiguous.
When to graduate from the template to a platform
Four signals that the spreadsheet has outlived its usefulness.
- Volume. Above 500 new records per month, manual logging consumes more than 4 hours per week and backlogs accumulate.
- Channels. Above 3 retail channels, keeping the mapping between retailer identifiers and internal SKU becomes a second spreadsheet job.
- Response discipline. If responded/response_date columns are consistently blank, the team is logging but not acting. A platform with response workflows produces different behavior.
- Anomaly questions. When leadership starts asking "what's changed in the last two weeks on the Model 7 family?" and the answer requires a 30-minute manual spreadsheet pivot, the pivot cost has exceeded platform cost.
The template is a 60–120 day starting point. Beyond that, the ROI math favors a platform — even at flat $495/month, Indellia's floor price is less than the cost of 6 hours of analyst time per month.
Graduate from the spreadsheet. Indellia ingests the same 13-column record type natively across every retail channel, ticket system, and returns platform. Start a free trial.