📂 TUESDAY – Single-Stock Deep Dive: “Volume vs. Price Growth Decoder”

Revenue growth can lie.

A company growing sales 6% because prices rose 8% while units fell 2% is telling a very different story from one growing 6% because customer demand actually increased.

Home Depot reports today, with Lowe’s following Wednesday, making the distinction especially useful as investors evaluate housing-linked demand. Home Depot has confirmed its Q2 earnings release for August 18.

Today’s Intel Drop separates real demand growth from inflation-assisted revenue.

💡PROMPT TEXT:

(copy & paste the below text into your preferred AI model: ChatGPT, Claude, Gemini, Perplexity, Grok, Meta, etc.)

You are conducting an institutional-grade “Volume vs. Price Growth Decoder” on one publicly traded company as of August 18, 2026.

USER PROVIDES:

TICKER:
OPTIONAL THESIS:

GOAL:

Determine how much of the company’s recent revenue growth came from:

1. Higher prices
2. Higher unit volume
3. Product or customer mix
4. Acquisitions
5. Currency
6. New locations or capacity

Use the latest:

- 10-K
- 10-Q
- Earnings releases
- Earnings transcripts
- Investor presentations
- Industry data
- Competitor commentary
- Pricing disclosures

STEP 1 — DECOMPOSE REVENUE GROWTH

For the last 8 quarters, determine where possible:

Revenue Growth =
Price + Volume + Mix + Acquisitions + FX + Other

Do not invent figures where the company does not disclose them.

If exact decomposition is unavailable:

- Estimate ranges using credible evidence
- Clearly label the result as an estimate
- Explain the source of uncertainty

STEP 2 — ANALYZE VOLUME QUALITY

Evaluate:

- Units sold
- Transactions
- Customer count
- Traffic
- Same-store volume
- Seat capacity
- Occupancy
- Subscriber count
- Usage
- Shipment volume

Use whichever metrics fit the business model.

Classify volume:

- Accelerating
- Stable
- Slowly declining
- Rapidly declining

STEP 3 — ANALYZE PRICING QUALITY

Determine:

- Magnitude of recent price increases
- Whether prices are sticking
- Promotional activity
- Discount intensity
- Customer elasticity
- Competitive reactions
- Mix effects disguising pricing changes

Classify pricing power:

- Strong
- Moderate
- Weakening
- Lost

STEP 4 — DETECT REVENUE ILLUSIONS

Look specifically for:

- Revenue rising while units fall
- EPS rising primarily from buybacks
- Gross margin rising because low-margin volume disappeared
- Average ticket increasing because low-income customers left
- Nominal growth masking real contraction
- Acquisition growth masking organic weakness
- FX creating misleading comparisons

Flag each clearly.

STEP 5 — ANALYZE CUSTOMER SEGMENTATION

Where possible determine behavior among:

- Lower-income customers
- Middle-income customers
- Higher-income customers
- Commercial customers
- Small-business customers
- Enterprise customers

Identify which cohort is driving marginal growth or weakness.

STEP 6 — BUILD THE PRICE / VOLUME TABLE

Include:

- Quarter
- Reported Revenue Growth
- Estimated Price Contribution
- Estimated Volume Contribution
- Mix
- Other Effects
- Margin Direction
- Demand Quality
- Confidence Level

STEP 7 — BUILD THE FORWARD MODEL

Construct three scenarios for the next four quarters:

A. Pricing holds + volume stabilizes
B. Pricing normalizes + volume improves
C. Pricing weakens + volume remains soft

For each estimate directionally:

- Revenue
- Gross margin
- EPS implications
- Free cash flow
- Valuation implications

Avoid false precision.

STEP 8 — FINAL SCORECARD

Assign:

- Real Demand Strength: 1–10
- Pricing Power: 1–10
- Revenue Quality: 1–10
- Volume Trend: 1–10
- Earnings Sustainability: 1–10

Then conclude:

1. Is reported growth primarily price-driven or volume-driven?
2. Is that mix improving or deteriorating?
3. What does consensus appear to misunderstand?
4. What metric matters most next quarter?
5. What would invalidate the thesis?

Separate facts, estimates, and inference.

Output in a clean table + 3–5 sentence explanation why this matters right now.

END PROMPT

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