Automation

Airtable Review-Form Contact and Retailer Automation

Links review submissions to the right Contact and Retailer by email and creates a flagged Contact when no match exists without dropping submissions.

  • Airtable workflow automation
  • Airtable review form automation
  • Airtable contact matching
  • Airtable retailer matching
  • review submission automation
  • email address record matching
Airtable Review-Form Contact and Retailer Automation — case study visual

Overview

The project at a glance

A multi-location consumer retail operation relies on customer feedback to keep its locations and product lines performing. Reviews arrive through a web-based form, and each submission had to be linked to the correct customer record and the correct retail location. With multiple stores, a growing customer base, and a steady flow of form submissions, that linking work had become a manual bottleneck.

The core problem was matching: each review needed to be connected to the right Contact and the right Retailer — the company's term for a store location — so that feedback could be routed and acted on correctly. The existing process depended on staff looking up submissions and assigning them by hand, and any submission that could not be confidently matched risked being lost.

Octacer was asked to automate the intake and matching workflow end to end. The delivered system reads each incoming review submission, matches it to the correct Contact and Retailer by email address, creates a flagged Contact when no match exists, and never drops a submission from the pipeline.

What the engagement had to achieve

  1. Automatically link each review submission to the correct Contact and Retailer
  2. Match records by email address without manual lookup
  3. Create a flagged Contact when no existing match can be found
  4. Ensure no submission is lost, even when matching fails

The story

From manual lookup to automated routing

What was at risk

The Challenge

The review intake process began with a web form, but what happened after submission was manual. Someone had to open each submission, determine which customer it belonged to, determine which retail location it referred to, and update the records accordingly. The effort scaled with submission volume, and the risk of error or delay grew with the workload.

Failure mode 01 Manual matching at scale

Every review submission had to be matched to a Contact record and a Retailer record by hand. Staff had to interpret the submission, search for the customer, search for the location, and then attach the review to both. As submission volume grew, the lookup work consumed more time and attention. The matching itself was the fragile part. A submission that did not obviously correspond to an existing customer had to be assessed individually, and the process relied on whoever happened to be doing the lookup. The company had no consistent rule for what to do when a match could not be found.

Failure mode 02 Submissions at risk of being dropped

A review that could not be matched to an existing Contact or Retailer had no clear path forward. The default outcome of an unmatchable submission was that it stalled in the workflow — and a stalled submission could be lost entirely. For a feedback process meant to capture customer sentiment, losing submissions was not an acceptable outcome. The company needed a workflow that would never let a review disappear from the pipeline, regardless of whether a match existed.

How we responded

The Solution

Octacer's approach was to make the matching rule deterministic and the failure path explicit. Instead of relying on human judgment at each step, the system would apply one consistent rule: match by email address. When a match exists, link the submission to the right Contact and Retailer automatically. When no match exists, create a flagged Contact so the submission is preserved and can be resolved without being lost. This design separated the two things the company actually needed: automatic routing for the majority of submissions that could be matched, and reliable capture for the minority that could not. Neither outcome depended on manual intervention.

Decision 01 One deterministic matching rule

Email address became the single matching key for both Contact and Retailer records. The system reads the email from each incoming submission and checks it against existing Contact and Retailer records. This removed the ambiguity of human lookup and gave every submission a consistent, repeatable outcome. The rule is simple by design. A deterministic email match either succeeds or it does not, and the system behaves accordingly. There is no fuzzy matching, no interpretation, and no judgment call that could vary between handlers.

“Match on email — the only consistent identity.”

Decision 02 A flagged fallback that preserves submissions

For submissions that do not match an existing Contact, the system creates a new Contact record with a flag indicating that it was created from an unmatched review. The submission is linked to that flagged Contact and continues through the pipeline instead of stalling or disappearing. This design guarantees that no review is ever dropped. Every submission either links to a verified record or creates a clearly identifiable placeholder that can be reviewed and resolved later. The flag makes the unresolved state visible rather than silent.

“Never drop what can't be matched — preserve it. A preserved submission can be resolved; a lost one cannot.”

Deliverables

What we built

The concrete capabilities designed, built, and shipped in this engagement.

Automated review-form intake

The system watches the web form for new review submissions and ingests each one automatically. When a submission arrives, it enters the matching workflow without any manual step, so form volume no longer determines the effort required to process reviews.

  • Submissions enter the pipeline the moment they are submitted
  • No manual export, download, or data entry between the form and the records
  • The intake step is the entry point for every review

Email-based Contact and Retailer matching

Each submission is matched against existing Contact and Retailer records using the email address from the review form. When a match is found, the submission is linked to both the correct customer record and the correct store location automatically.

  • One consistent matching rule applied to every submission
  • Correct routing without human lookup or interpretation
  • Reviews land against the right customer and the right location

Flagged Contact creation for unmatched submissions

When no existing Contact matches the submission's email address, the system creates a new Contact record marked with a flag that identifies it as originating from an unmatched review. The submission is preserved and linked, rather than left unresolved or dropped.

  • No match still results in a complete, linked submission
  • The flag makes unmatched records easy to identify and resolve
  • The pipeline never loses a review, regardless of match outcome

End-to-end submission preservation

The workflow is built so that every submission has a destination. Matched submissions route to their correct records; unmatched submissions create a flagged Contact and route through the same pipeline. There is no state in which a submission exists but has no record to link to.

  • Every submission ends up linked to a Contact and a Retailer
  • No manual fallback required to keep the pipeline complete
  • The workflow enforces capture as an invariant, not an option

Technology

The stack

The tools behind the build, and the role each one played.

Platform

Airtable

the underlying system holding Contact and Retailer records, receiving linked review submissions, and hosting the automation that performs matching and flagging.

Airtable Automation

the workflow engine that triggers on new form submissions, performs the email-based lookup, creates flagged Contacts when needed, and links each submission to the correct records.

Outcome

What changed

The review intake workflow no longer depends on manual lookup. Each submission is matched and routed automatically, and the matching rule produces a consistent outcome every time.

Submission capture

guaranteed

every submission is linked to a Contact and Retailer, either by match or through the flagged fallback.

Matching effort

eliminated

email-based matching replaces manual lookup for every incoming review.

Unmatched submissions

preserved

submissions without an existing Contact create a flagged record instead of being dropped.

Beyond the launch

Lasting improvements

The changes that keep paying off after the engagement ended.

  1. Review routing is now consistent and rule-based rather than dependent on individual judgment
  2. Unmatched submissions are visible and resolvable through their flag rather than silently stalled
  3. The workflow scales with form volume without requiring proportional manual effort

Ready to build something like this?

Let's discuss how we can deliver a similar outcome for your team — scoped to your stack, your data, and your workflow.