DATA TRANSFORMATION PILOT
Prioritize, structure, and enrich product data.
AI product data enrichment offers a powerful way to accelerate one of the hardest tasks in digital commerce. But many AI enrichment pilots are doomed from the start. There's no argument about whether the data needs help; the question is what really works to drive business outcomes?
The Data Transformation Pilot answers that question at an entry-level cost and gives you real evidence to drive your enrichment program. We find the categories where the upside is largest, transform the data properly, and show you the impact it has on search and conversion.
What You Get
Ascend Diagnostics
Prioritize performance gaps with our proprietary dashboard. Free access forever.
6-Week Timeline
Fixed scope, fixed price, fixed end date. You know what you're getting and when.
Data Model/Schema
We define the structure and rules. You don't have to build it yourself; it's part of the work.
Product Data Enrichment
Production-ready enriched data, not a report. AI-boosted with human QA, deployed and measured.
Ascend Diagnostics Dashboard
Before we transform a single record, Ascend Diagnostics analyzes your commerce data to identify the categories where enrichment will have the highest impact. Once your transformed data goes live, it tracks performance in real-time; showing you the before and after so you can see exactly what the work delivered.
Priority Engine
Ingests your data to surface high-impact opportunities
Before & After Tracking
Measures performance lift as enriched data hits the website
Free Access Forever
You keep the dashboard to monitor results indefinitely
Why smart enrichment beats fast enrichment
Most AI enrichment tools optimize for one thing: filling in blank fields as quickly as possible. The result? You get data faster and cheaper, but you still need to QA it, rework it, and figure out if it actually matters. That's where the real cost lives.
We start differently. We identify where enrichment drives business outcomes, build the structure to support accuracy, and handle the QA as part of the engagement. The data you get is production-ready from day one. This means faster time to your channels, better search performance, and real evidence that the work paid off.
| Dimension | AI Enrichment Tool (Standalone or PIM feature) | Pivotree AI Data Transformation Pilot |
|---|---|---|
| Starting Point | "Enrich everything we can" | "What should we enrich and why?" |
| Data Model | You build it, use what you have, or skip it | We define it with you |
| Output | Auto-enriched records | AI-enriched + human QA = high-confidence data |
| QA Process |
Manual review of every record |
Baked in and done for you |
| Rework Cycles | Multiple rounds (time sink) |
Minimized through upfront work |
|
Launch Readiness |
"Good enough to ship?" | Ready to deploy with confidence |
| Ongoing Measurement | Usually missing | Ascend Diagnostics, free forever |
| Total Cost of Ownership | Enrichment cost + hidden QA labour | Fixed scope, fixed price, predicatable |
How it works
Prioritize the problem
We find the categories and SKUs where the upside is largest using your own commerce data. You see the reasoning behind it before anything gets touched.
Transform the data
Taxonomy, schema, classification, and targeted enrichment. We actually change the records, not just recommend changes.
Measure the result
We capture how those categories are performing before the work starts. Once the transformed data is in use, that benchmark is what the comparison runs against.
This is the right call when...
- You know the product data is holding you back and you can't point at the specific part doing the most damage.
- A full catalog enhancement program has been floated internally and died for lack of evidence.
- You need a number and an end date before anyone will approve anything.
- There's a channel launch, an acquisition, or a replatform coming, and a couple of categories have to be right before it lands.
- You've paid for a data project before and got a report on the problem instead of a fix.
Data Transformation Pilot FAQs
No. An assessment reports on the problem. This engagement changes the data. You end up with transformed records in your environment, not a document about what to do next.
It depends on your environment. It might be your team, it might be us, it might be a third party already working in the system. Because the measurement step depends on the data actually being live, we settle on who's deploying it before the engagement starts.
Then you know that, and you know it after one contained engagement instead of at the end of a full program. The benchmark is captured before the work starts precisely so the answer is allowed to come back negative.
No. We work on whatever you're on, and if you're not on anything yet, the taxonomy and schema work here will tell you what shape your data needs to be in before you choose.
It depends what the data shows. Some customers scope the next set of categories, some move to a standing program, and some take what they've got and run with it. There are no obligation attached to the pilot.