Workflow Templates for Google Sheets
Overview
Workflow templates turn a multi-step data cleaning job into one click. Each template chains Standardize, Fuzzy Match and, where the job needs it, Find Duplicates steps automatically, then writes the results to a review sheet so your source data is never touched. If the result sheet already exists, the template reuses it and replaces its previous results.
Templates are available in four categories: Accounting, E-Commerce, HR / RevOps and Research and GLAM. They are a Essential or Extended Pass feature, so every template works exactly the same regardless of your dataset size.
| Template | Category | What It Does | Best For |
|---|---|---|---|
| AP Vendor Reconciliation | Accounting | Matches an accounts payable list against your master vendor table with a confidence score | Vendor master data clean-ups and supplier onboarding |
| Order-to-Shipping Reconciliation | E-Commerce | Matches orders against your shipping log and flags unfulfilled orders | Fulfilment audits and customer support triage |
| User List Consolidation | HR / RevOps | Merges two user lists and flags people who appear in both systems | CRM, HR and RevOps system migrations |
| Wikidata Reconciliation | Research and GLAM | Matches names against a Wikidata label table and returns the best QID with a score | Collection metadata, author lists and authority work |
Worked example. The four templates on recurring jobs, with thresholds and review sheets, are shown in Workflow Templates Case Study for Google Sheets.
How to Open Templates
In Google Sheets, go to Extensions > Flookup Data Wrangler > Standard Data Cleaning > Templates. Templates is the first card in the Standard Data Cleaning sidebar, above Fuzzy Match Data. You will see the template browser grouped by category. Click a template to open its detail view, set your inputs and run it.
How Templates Work
Every template follows the same flow:
- Set your inputs. Enter the ranges and column numbers the template asks for. Most inputs have sensible defaults; only the range inputs are required.
- Click Run. The template standardises names, fuzzy-matches your records in sequence and flags internal duplicates in the templates that include that step.
- Review the results. The result sheet contains a review table that shows each source record with its best match, match score, status and confidence label.
The template remembers the inputs from your last successful run. Open the same template again and click Use last run settings to restore the ranges and column numbers, then adjust anything that changed before you run it.
Templates are a Essential or Extended Pass feature and are included in every Essential or Extended Pass purchase. The cleaning operations themselves draw on the pass work balance; every run is subject to the pass row limits. AI assistant steps run on your own key, and every run is subject to the menu function limits.
Output and matching caveats
- The result sheet is reused when it already exists. Its previous template results are replaced.
- !No match found means that no record met the selected match threshold. Review the threshold and source ranges before treating the result as final.
- Output rows are generated by the selected fuzzy matching threshold. They are candidates for review and are not proof that two records refer to the same entity.
- Confidence labels summarise the match score. They do not replace checking the underlying values.
- Duplicate groups depend on the first-column key used by Find Duplicates. Records with different first-column values can remain in the same broader review group or be left unresolved.
- The Wikidata template compares each name twice, once to return the QID and once to return the label, so a very large list takes longer than a single-match template.
Template errors
- No data found in the selected range. Select a range containing the records required by the template.
- The range is larger than the row limit allows. Reduce the range size or use Data Cleaning Automation for larger datasets.
- This feature needs a licence. Templates need an active Essential or Extended Pass. Open the Flookup Dashboard to see your trial and purchase options.
- Timed out before completion. Reduce the range size and run the template again.
AP Vendor Reconciliation
Match an accounts payable list against your master vendor table. The template standardises vendor names, flags duplicate entries and matches each AP record to the best master vendor with a confidence score. Results are written to the AP Vendor Recon result sheet, which is reused when it already exists.
Workflow
Standardize → Find Duplicates → Fuzzy Match → Review
Inputs
| Field | Required | Description | Default |
|---|---|---|---|
| AP list range | Yes | The range containing your accounts payable records | - |
| Vendor name column in AP list | No | Column number holding the vendor name in your AP list | 1 |
| Master vendor table range | Yes | The range of your master vendor table | - |
| Vendor name column in master table | No | Column number holding the vendor name in the master table | 1 |
| Match threshold (0-1) | No | How strict the fuzzy match should be | 0.82 |
Output Columns
| Column | Meaning |
|---|---|
| Source Vendor Name | The vendor name as it appears in your AP list |
| Standardized Name | The cleaned vendor name used for matching |
| Best Match | The closest vendor from your master table |
| Match Score | Similarity score of the best match |
| Status | Matched or unmatched |
| Confidence | High, medium or low label derived from the match score |
Order-to-Shipping Reconciliation
Match orders against your shipping log and flag unfulfilled orders. The template standardises customer names from your orders export and matches each order to the best record in your shipping log using fuzzy customer matching. Results are written to the Order Ship Recon review sheet, which is reused when it already exists.
Workflow
Standardize → Fuzzy Match → Review
Inputs
| Field | Required | Description | Default |
|---|---|---|---|
| Orders list range | Yes | The range containing your orders export | - |
| Order ID column in orders list | No | Column number holding the order ID | 1 |
| Customer name column in orders list | No | Column number holding the customer name | 2 |
| Shipping log range | Yes | The range containing your shipping log | - |
| Order ID column in shipping log | No | Column number holding the order ID in the shipping log | 1 |
| Customer name column in shipping log | No | Column number holding the customer name in the shipping log | 2 |
| Match threshold (0-1) | No | How strict the fuzzy match should be | 0.85 |
Output Columns
| Column | Meaning |
|---|---|
| Order ID | The order ID from your orders export |
| Order Customer | The customer name from your orders export |
| Shipping Order ID | The matching order ID from the shipping log |
| Match Score | Similarity score of the best match |
| Status | Matched or Unmatched |
| Confidence | High, medium or low label derived from the match score |
User List Consolidation
Merge two user lists and flag people who appear in both systems. The template standardises names from two systems (HR, CRM, RevOps), detects which people appear in both lists, flags internal duplicates and produces a consolidated list of unique users. Results are written to a new User List Consolidation sheet.
Workflow
Standardize List A → Standardize List B → Find Duplicates List A → Fuzzy Match → Review → Consolidated Unique Users
Inputs
| Field | Required | Description | Default |
|---|---|---|---|
| List A range | Yes | The range containing the first user list | - |
| Name column in List A | No | Column number holding the name in List A | 1 |
| List B range | Yes | The range containing the second user list | - |
| Name column in List B | No | Column number holding the name in List B | 1 |
| Match threshold (0-1) | No | How strict the fuzzy match should be | 0.85 |
Output Columns
| Column | Meaning |
|---|---|
| List A Name | The name as it appears in List A |
| Standardized Name | The cleaned name used for matching |
| Match in List B |
The closest matching name from List B or
!No match found
if no value meets the threshold
|
| Match Score | Similarity score of the best match |
| Status | Matched or Unmatched |
| Confidence | High, medium or low label derived from the match score |
Wikidata Reconciliation
Match a name list against a table of Wikidata labels and return the best QID. The template standardises each name, finds the closest label in your reference table and writes the QID, label, score and review status to the Wikidata Recon sheet. Your source data is never touched.
The template matches against a local reference table, not the live Wikidata API. Export the items you need from Wikidata Query Service or a Wikibase instance first, with one QID column and one label column. That keeps each run repeatable, avoids query limits and leaves the data in your Workspace. A reference table for the domain you are working on, such as every museum in one country, matches faster and produces fewer false candidates than an export of the whole of Wikidata.
A match is a candidate, not a confirmed identity. Review the score, the source name and the label before you reuse the QID in an upload or a catalogue record. For a QID that is wrong, correct the reference table or raise the threshold and run the template again.
Workflow
Standardize → Fuzzy Match QID → Fuzzy Match Label → Review
Inputs
| Field | Required | Description | Default |
|---|---|---|---|
| Name list range | Yes | The range containing the names or labels to reconcile | - |
| Name column in the list | No | Column number holding the name in the source list | 1 |
| Wikidata table range (QID and label) | Yes | The reference range with one QID column and one label column | - |
| QID column in the Wikidata table | No | Column number holding the QID in the reference range | 1 |
| Label column in the Wikidata table | No | Column number holding the label used for matching | 2 |
| Match threshold (0-1) | No | How strict the fuzzy match should be | 0.82 |
Output Columns
| Column | Meaning |
|---|---|
| Source Name | The name as it appears in your list |
| Standardized Name | The name with diacritics removed, used for matching |
| Wikidata QID | The QID of the closest label, or !No match found |
| Wikidata Label | The label that produced the match |
| Match Score | Similarity score of the best match |
| Status | Matched or Unmatched |
| Confidence | High, medium or low label derived from the match score |
Frequently Asked Questions
Does the Wikidata template call Wikidata directly?
No. It matches against a QID and label table that you export from Wikidata Query Service or a Wikibase instance. That keeps each run repeatable, avoids query limits and leaves the data in your Workspace.
What are workflow templates?
Workflow templates are pre-built multi-step processes that chain the Standard Data Cleaning operations together.
You provide your ranges and the template runs standardisation, deduplication and fuzzy matching automatically, writing the results to a review sheet.
Are workflow templates included with Essential or Extended Pass?
Yes. Workflow templates are an Essential or Extended Pass feature.
Essential or Extended Pass includes all templates in every category, and cleaning, deduplication, standardisation and enrichment draw on the pass work balance.
Does running a template modify my source data?
Each template writes its results to a review sheet, reusing the sheet if it already exists.
The previous template results are replaced, but the source data is not modified.
What is the match threshold in a template?
The threshold is a value from 0 to 1 that controls how strict the fuzzy matching step is. A higher threshold returns fewer, more confident matches.
Each template ships with a sensible default that you can adjust before running.
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