Find the Broken P: Diagnosing a Stalled DoorDash Market Launch

Marketing Academy · Field Work●Marketing Fundamentals

All projects·From: The 4 Ps (and the extra 3)

MiniAudit· 25 minutes

DoorDash

Objective: Given a snapshot of launch metrics for a new DoorDash market, walk the 7 Ps diagnostic funnel in the lesson's prescribed order (Product, Price, Place, Promotion, People, Process, Physical Evidence) to identify which single P is actually broken, instead of defaulting to 'more promotion.'

You're a launch marketer at DoorDash. A mid-size metro opened eight weeks ago and order volume is 40% below plan. The regional GM wants to double the ad budget. You have one data snapshot before that budget gets approved.

Apply the diagnostic order from the lesson (Product first, Promotion near the end) to a metrics table, and stop at the first P that fails its healthy/unhealthy test.

Before you start

What you'll need

Free path (everything below is enough to finish)

Google Sheets

FreeBuild the P-by-P scorecard

Free, sortable, easy to share with the GM

The process

1 step

Step 01 of 01

Diagnosing underperformance by walking the 7 Ps in a fixed order before increasing ad spend

The lesson's diagnostic flowchart checks Product, then Price, then Place, then Promotion, then People, then Process, before landing on Physical Evidence, stopping at the first 'No.'

Restaurant selection matches other markets, price parity holds, and the app is live in 94% of target zip codes, but only 22% of a pre-launch awareness survey has heard of DoorDash launching locally. Which P is broken?

Google Sheets— Open the launch metrics snapshot, score each P healthy/unhealthy in the order given.

Procedure

List all 7 Ps as rows, in the lesson's diagnostic order
Score Product: restaurant count and category mix vs. 2 comparable launches
Score Price: delivery fee and menu markup vs. competitor benchmark in that metro
Score Place: percentage of target zip codes with active coverage
Score Promotion: pre-launch and week-8 unaided awareness survey results
Stop scoring at the first 'unhealthy' row and flag that as the fix

Sample output

P-by-P scorecard, DoorDash [Metro] launch, week 8

Product: HEALTHY, 340 restaurants live, matches comparable-market average
Price: HEALTHY, delivery fee within $0.50 of local competitor
Place: HEALTHY, 94% zip code coverage vs. 90% target
Promotion: UNHEALTHY, 22% unaided awareness vs. 65% target at week 8

Diagnosis: Promotion is the first broken P. Do not add more restaurants or change price, fix awareness first.

Healthy

Diagnosis stops at the first unhealthy P and that becomes the sole recommendation.

Unhealthy

Recommending a budget increase before scoring Product, Price, and Place.

What this means

Because Product, Price, and Place all score healthy, Promotion is the legitimate bottleneck here, this is one of the few cases where more promotion actually is the right call, because it is not masking a deeper problem.

So what do I do about it?

Symptom	Action	Effort
GM wants to double ad budget without a diagnosis	Run the P-by-P scorecard before approving new spend	30 min

YouYou can do this yourself, no engineering access required.

Final deliverable

A one-page P-by-P scorecard with a single recommended fix, not a list of five things to try.

See a reference example

Sample output

Zomato is often held up as the counterexample: when its Tier-2 city expansion underperformed in 2019, delivery times (Process) turned out to be the broken P, not Promotion, average delivery time was 61 minutes against a 35 minute target. Zomato fixed dispatch routing before spending a rupee on new ads, and order volume recovered within a quarter.

Success criteria

You're done when you can:

Scores all Ps in the lesson's diagnostic order, not a random order
Correctly identifies Promotion (not Product/Price/Place) as the broken P from the given data
Recommendation matches the single broken P, not a bundle of fixes