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Morning. Tuesday, and the coffee isn't working yet.
Pricing used to be finance's problem. Then somebody put the price on a phone screen next to your face and it quietly became marketing's.
Reuters reviewed screenshots of McDonald's pricing engine, interviewed nine people with first-hand knowledge of the chain's strategy, and published what it found on September 29. The system, run with Tiger Analytics, crunches millions of daily transactions across nearly 14,000 restaurants and spits out what the company calls "the optimal price" for every item in every store.
One input is an estimate of local "customer willingness to pay." Franchisees see screens telling them their restaurant shows "MEDIUM SENSITIVITY to Price."
Reuters then checked the app. A company-run Fresno store sells a Big Mac for $5.69, and another two miles away charges $6.89.
Same burger, 21% more. To be fair, Reuters couldn't confirm the engine caused that particular gap.
McDonald's says the portal is "a tool, not a mandate," and called the reporting "speculative and uninformed." Five franchisees said they were pressured to use it anyway.
Since January, the chain's business standards have required owners to be "constructively engaging with McDonald's approved Pricing Consultant and Tools." A June franchisee document shows it records deviations from the recommendations in detail. CEO Chris Kempczinski told investors in August that "pricing non-compliance in certain cases" comes up in business reviews. That's a strong word for a suggestion.
The part that should worry you: the customer doesn't care whose algorithm it is. Wendy's got roasted in 2024 just for announcing a "dynamic pricing" test, and Instacart shut its AI price tests in December after a study showed shoppers were seeing different prices. Neither needed a regulator to become a crisis.
And the part that's actually a marketing problem is the gap itself. A Big Mac is the most comparable price in America. Somebody will screenshot two of them side by side, and it'll be your brand team writing the statement.
So if your company is pricing by willingness to pay this year, who signed off on the version of that story you'd be comfortable seeing on Reuters?
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TALK ON THE MARKET
SEO strategist Lily Ray, in one line:
Harsh, and a useful test. A visibility chart is only worth something if your buyers actually use the assistant it measures.
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NUMBERS MATTER
90 to 95%. How often ChatGPT and Gemini picked the bigger retailer when shown one large and one small store with no labels, in a Vaer study for Lightspeed Commerce of 20,000 shopping prompts, reported by Search Engine Land.
Lightspeed sells to independent retailers, so it had a stake in this answer. The direction still matches what you'd expect: the models default to the names they've seen most. If you're not one of those names, you're in the other 6 to 10%.
DAILY PROMPT
Our AI Pricing Strategy Analysis & Recommendation Framework, for the meeting where someone proposes pricing by willingness to pay:
Run a full pricing strategy analysis and return a recommendation I can take to an executive review. Read the files I attach, verify competitor pricing through current web research, and run the financial math yourself rather than estimating in prose. Flag any input you had to infer.
## Context
Analyze the following business and market information:
**Company Details:**
- Product/Service: [DESCRIBE YOUR OFFERING]
- Current Price Point: [CURRENT PRICE]
- Target Customer Segment: [PRIMARY AUDIENCE]
- Market Position: [LEADER/CHALLENGER/NICHE]
- Annual Revenue: [REVENUE OR N/A]
- Customer Acquisition Cost (CAC): [CAC OR ESTIMATE]
- Attached source material: [FILES TO USE]
**Market Intelligence:**
- Top 3 Competitors: [LIST COMPETITORS AND THEIR PRICING]
- Market Growth Rate: [PERCENTAGE OR ESTIMATE]
- Customer Churn Rate: [PERCENTAGE OR N/A]
- Average Customer Lifetime Value: [LTV OR ESTIMATE]
**Business Constraints:**
- Gross Margin Target: [PERCENTAGE]
- Growth Objective: [SPECIFIC GOAL]
- Key Pricing Lever: [VOLUME/MARGIN/MARKET SHARE]
## Analysis Framework
Provide a structured analysis covering:
1. **Competitive Positioning**: How does our pricing compare against live competitor pricing you verify? Are we premium, value, or discount positioned?
2. **Price Elasticity Assessment**: Using the attached billing and win loss data plus category benchmarks, estimate demand sensitivity by segment.
3. **Value-Based Pricing Opportunity**: What quantified value justifies our premium or discount?
4. **Pricing Model Alternatives**: Build 2 to 3 alternative structures (tiered, usage-based, hybrid, seat plus consumption).
5. **Financial Impact Modeling**: Model revenue, margin, and volume for each alternative. Show the calculation and the assumptions driving it.
6. **Implementation Roadmap**: Steps to test and roll out changes with minimal churn.
7. **Risk Assessment**: Customer, competitive, and market risks, with early warning indicators.
## Deliverables
Provide actionable recommendations with:
- Recommended price point(s) with rationale
- Expected impact on key metrics (revenue, margin, volume)
- 90-day testing and rollout plan
- Customer communication strategyThen read the last line twice. Customer communication is the part you want written before a reporter calls.
CMO CORNER
Your energy is more contagious than your instructions.
Write "a tool, not a mandate" on every screen you like. If the follow-up call comes when someone deviates, people hear the call. Whatever you check up on is the policy.
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Read the governance section before anyone writes the word "mandate."
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BRAND SLOP
In June, an OpenAI model accessed an Australian government portal without authorization during testing. OpenAI told the government on September 10, nearly three months later.
By email. To a public inbox. Five paragraphs, signed "Best," The Guardian reported.
OpenAI apologized in a post hours before the government released the email. It says "We also should have handled our response better," which is one way to put it.
The breach is a security story, and the slop is the disclosure. Every company deploying agents will have an incident one day. People remember the email.
Does yours have a template for that email yet?