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Retailer sell-through reporting

Track sell-through across every retail partner. Consolidate syndicated data and EDI feeds into a weekly report with base vs incremental and year-over-year comparisons.

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The prompt

I want to track sell-through performance across our retail partners from syndicated data and retailer feeds. Can you build me a flow that pulls consumption actuals by retailer and product, calculates sell-through rates and base vs. incremental performance, and outputs a weekly report with current vs. prior year comparisons?

Just copy and paste the prompt into a new Parabola flow to get started.

What Parabola builds

A workflow with seven steps you can edit:

1. Pull each retailer source. Syndicated feeds like SPINS and IRI, retailer EDI files, portal exports from Target, Walmart, Ulta. The flow ingests each.

2. Standardize the SKU and the retailer. Retailer SKU codes map to your internal SKU. Each retailer name maps to one canonical record. The downstream math joins cleanly.

3. Pull the sell-in side. POs from NetSuite or your wholesale system. Sell-in is the denominator the sell-through number depends on.

4. Calculate sell-through. Units sold through to consumers divided by units sold in to the retailer, per SKU, per retailer, per week.

5. Split base vs incremental. Promo lift gets isolated using the promo calendar. Base trend stays clean, incremental gets attributed to the campaign.

6. Layer in year-over-year. Same week prior year as the comparison anchor. Account for new launches and discontinued SKUs so the comparison is fair.

7. Output the report. Weekly roll-up, retailer-level detail, SKU-level dig, optional Slack alert when sell-through drops below threshold at any major account.

Why teams stop doing this manually

Wholesale data lives in fifteen places. SPINS sends a weekly file. IRI sends a different one. Target's portal exports a CSV with retailer-specific SKU codes. Walmart EDI lands at a different cadence. Ulta sends spreadsheets that change column order between cycles. The wholesale planner is supposed to make one report out of all of this every Monday.

The math is straightforward once the data is clean. Sell-in divided by sell-out. Base versus incremental. Year-over-year. The math is not the problem. The problem is the data plumbing, every single week, before the math can even start.

The cost of getting this wrong is operational. A retailer reports a stockout and the planner does not see it until the next week's roll-up. A promotional lift gets misattributed and the brand pulls the wrong lever next quarter. The team builds the report at the cost of doing anything else with the data.

The work is repeatable and rule-based. Pull, standardize, join, calculate. That is exactly the kind of work that lives in a flow.

How it works

Step 1. Paste the prompt.

Open Parabola, paste the prompt in section 2, and let it ask follow-up questions about your retailer mix, your syndicated providers, and the comparison cuts your team uses.

Step 2. Connect your data.

SPINS, IRI, retailer EDI feeds, portal exports, plus NetSuite or your wholesale system for the sell-in side. Plus the SKU map and the promo calendar.

Step 3. Run it weekly.

Monday morning is the default. The flow refreshes against the latest retailer files and outputs the report. Wholesale planning reviews and acts.

Related prompts

FAQ

Can the flow handle retailers with different reporting cadences?

Yes. Each retailer pipeline has its own schedule. The roll-up reads the latest available data per retailer and tags any retailer where the file is stale.

How does the flow handle new product launches with no prior-year comparison?

New SKUs get tagged and reported against the launch baseline rather than year-over-year. The flow keeps them out of the year-over-year average so the comparison stays clean.

What about retailer-specific promotional calendars?

Each retailer has its own promo calendar input. The base vs incremental calculation runs per retailer. The roll-up shows a brand-level view layered over the retailer-specific cuts.

Can the flow alert on stockouts at a specific retailer?

Yes. Configurable threshold. The flow posts a Slack alert when sell-through drops below the threshold at any major account, with the retailer and SKU named.

How is this different from the dashboards inside SPINS or IRI?

Provider dashboards show consumption data. This flow ties consumption to your sell-in, your promo calendar, and your internal SKU structure. The output is the report the planning team can act on, not the raw feed.
Stop rebuilding the sell-through report every Monday.
Paste the prompt, point it at your retailer feeds and sell-in source, and let the report refresh on its own.
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