CraigsIP — 2 Year Customerr

When Quarterly Reports Tell You What Already Happened, You Need Earlier Signals

How an Award-Winning Equity Analyst Replaced 4 Hours of Manual Checking with Scheduled Weekly Data on A2 Milk

CraigsIP is a New Zealand-based equity research firm. Their Senior Research Analyst — a multiple-time INFINZ "Analyst of the Year" award winner — covers The a2 Milk Company, a consumer goods stock sensitive to retail pricing and demand shifts.

The challenge: company financial results are reported quarterly. By then, the move is often already in the price.

The analyst needed leading indicators — retail signals that show up before the income statement confirms them.

The Manual Approach: 4 Hours of Checking, Still Incomplete

Before working with us, the analyst was manually checking Amazon and Walmart listings for A2 Milk products. Every week, hours spent clicking through SKUs, noting prices, trying to spot changes.

Time sink 4 hours/week of senior analyst time — time that should go to research, not data collection.
Coverage drift Inconsistent SKU/variant coverage week to week.
No change history Hard to know when a price moved and by how much.
Hard-to-capture volume signal Amazon's "bought X times in past month" requires consistent daily snapshots.
This is what we call hidden labor. A senior analyst doing manual data collection because no tool gave them daily capture, variation-level tracking, and analysis-ready formatting.

What Changed: Real Data Early, Without a Long Setup Cycle

We showed them real data from their actual target products early — without a long setup cycle. That proof changed everything.

What We Provide

Every week, the analyst receives a consolidated report built from daily Amazon and Walmart data for A2 Milk and competitor SKUs.

FieldWhy It Matters
DateTrack changes over time
RetailerAmazon vs Walmart comparison
Product / SKUSpecific variation tracked
Price (promo)What consumers actually pay
Price (regular)Baseline for promotional analysis
Purchases in Past MonthDirectional demand proxy
Customer RatingQuality/sentiment indicator
Number of RatingsReview velocity signal
Product Weight (oz)Normalize across pack sizes
Price per ozTrue price comparison across variations

This structure lets the analyst see pricing pressure, promotional intensity, and demand signals — all before quarterly results.

The Complexity: Variations and Normalization

Infant formula isn't a single product. A2 Milk alone has multiple variations:

And competitors like Bubs have even more:

Each variation has its own price, its own volume, its own trajectory. Without normalizing by weight, a small pack and a large pack can look like different pricing when it's just pack size.

We track 28 SKUs across Amazon and Walmart, capturing daily snapshots that roll up into the weekly report.

The Scale

MetricValue
SKUs tracked (in-scope)28
Retailers2 (Amazon, Walmart)
Collection frequencyDaily → Weekly report
Fields per SKU/day10

This isn't massive scale — it's precise scale. The value isn't volume of data; it's the right data, consistently captured, formatted for analysis.

What the Data Enables: Signals Before Earnings

Promotional activity When Amazon runs a price cut on A2 Milk, the analyst sees it in the next report — not weeks later.
Volume trend signals Amazon's "bought X times" provides an early directional demand signal — often before quarterly revenue reflects it.
Competitive positioning Comparing A2 Milk pricing against Bubs shows relative positioning and whether competitors are gaining shelf presence.
This is alternative data for equity research: retail signals that inform financial analysis before earnings confirm them.

Two Years Later: From Manual Checks to Scheduled Weekly Reports

Before
After
"See price cuts and promotions earlier than waiting for quarterly results."

Fewer surprises at earnings. 4 hours per week of senior analyst time redirected to actual research. That last point matters: this is a multiple-time Analyst of the Year. Every hour spent on manual data collection is an hour not spent on award-winning analysis.

Who This Helps

CraigsIP's story resonates with equity research teams and alternative data users:

See What This Looks Like for Your Coverage Universe
We'll track your actual target products on your actual retail platforms. You'll see real data within 48 hours.
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