Getting Started with Hatched

Our CEO, Donal, explains our methodology and report structure, starting with a simple Excel example, then a deeper workbook for added insight.

Article Contents:

Data Methodology Data Source Excel Report Structure Summary Data Tabular Data Notes Model Calculations Model Details Plots

Data Methodology

Hatched Analytics specialises in identifying and collecting proprietary sequential ID (order ID) data - unique identifiers that reflect the volume of orders or transactions processed through a company’s technology stack.

When an online purchase is made, a numeric or alphanumeric identifier is often generated. These identifiers typically form part of a sequence. By collecting sufficient volumes of these signals, Hatched can infer transaction/order volumes processed by the platform.

Sequential IDs may be identified across multiple locations, including:

Email receipts

URLs or clickstreams

JSON page elements

Delivered packages

Data Source

To scale this methodology, Hatched operates a cashback and rewards application. This provides access to a community of more than 20,000 gig workers who share transactional data in exchange for rewards, with full transparency on how the data is used.

This community is not a panel. Instead, these users generate the IDs that allow us to observe real order counts flowing through company platforms on a weekly, monthly, and quarterly basis. Importantly, no sampling is applied. The indices are built directly from the collected signals.

Data is sourced at scale from our community of more than 20,000 gig workers.

Excel Report Structure

This section explains the core components included in each Hatched report and how to navigate them. Reports are delivered in Excel via email, and the file structure is consistent across tickers.

You will see 7 tabs of note:

Summary

Data

Tabular Data

Notes

Model Calculations

Model Details

Plots

Estimates
Indices

Summary

This tab includes details the data feed’s metadata, including:

Launch date

Delivery Frequency

Data Frequency

Transparency scores for indices & KPI alignment

Data

This tab is a structured view that all charts within the excel are built from. It is a presentation layer, with inputs coming from the Tabular Data.

At the top, there is a KPI prediction section (if applicable), showcasing estimates and their performance historically, and the model used. These are point-in-time snapshots.

Below, there are transaction indices for weeks, months, and quarters. If multiple indices exist (e.g., brand/geo breakdown), they are includued here.

Data tab for our FIGS data feed showing the historical performance of our Number of Order predictions, as well as the indices these are built on.

Tabular Data

This tab contains the underlying data used by the Data tab. In this table you will see:

The period duration and end date.

Full set of weekly/monthly/quarterly index values.

The cumulative totals of these indices.

Comments where applicable.

The release date of each index value.

The YoY change.

Index Health.

Notes

This tab provides narrative context and rationale around model changes, anomalies, and segments excluded (e.g., a period ignored). When a model switch occurs (e.g., Model 1A → 1B), Notes explain why.

Model Calculations

This tab is a transparent history of the estimation math used for KPI predictions. It shows the full model trail across time (e.g., where 1A vs 1B was applied) and how the estimate is constructed period by period.

Model Details

This tab show the formal model specification and diagnostics for each KPI estimate including parameters, residuals/fit context, and a clear record of which model version was applied when.

Plots

Estimates: Reported KPI (orange line), Hatched estimate (blue line), YoY comps (orange/blue bars), and error context.

Indices: Weekly, monthly, and (where available) mid-month/quarterly index charts; multiple panels appear if the report has several indices (e.g., brand or region).