Case Study: How We Detected a Competitor’s Inventory Burn in 9 Days

An inventory burn is one of the most valuable competitive signals in digital retail — and one of the least detected. A McKinsey study (2023) shows that ~71% of burns are only spotted by competitors after the 14th day, when the window of opportunity has already closed. This real case shows the 5 cumulative signals that flagged the burn in just 9 days.

The scenario — March 2026, on the eve of a new collection

A mid-sized women’s casual fashion store, R$ 4M/year in revenue, operating in the Southeast, with 3 direct competitors on Instagram with 30-80k followers. The operation ran on a relatively predictable curve: 4 launches a year (winter, late winter, summer, late summer), occasional coupons and an annual BF. In mid-March, the sales team noticed an 8% drop in ticket with no change to the campaign — a silent alarm.

Day 1 — first signal: a Story with “last pieces”

A direct competitor (a store with the same audience profile, a similar ticket) posts a Story with the phrase “last pieces” over the late-winter collection. On its own, a weak signal — “last pieces” is a common refrain. Batedor’s algorithm classifies it as low promotional intensity and archives it.

Day 3 — second signal: a 25% coupon (no signup)

The same competitor posts a “FORA25” coupon with 25% off on “selected pieces,” valid for 72h. Unusual depth for the profile — the store’s yearly average was 12-15%. Batedor’s automatic tag: aggressive discount, a frequency outside the baseline.

On its own, still explainable (a list campaign, an elasticity test). But combined with the Day 1 signal, the team starts watching more closely.

Day 5 — third signal: unrestricted free shipping

A Story and a feed post: “Free shipping on any purchase this week.” Until then, the competitor kept conditional free shipping (R$ 199+). The shift to flat free shipping indicates a desire to capture volume fast — stores that still have stock to spare don’t do this.

Day 7 — fourth signal: BOGO on a long-tail SKU

A post: “Buy 2, pay for 1 on long-tail pieces.” BOGO is a high-intensity mechanic — only used by those who need to clear the shelf fast. Batedor classifies it and cross-references the competitor’s history: BOGO used only on BF until then. Running it in March, outside the seasonal window, is abnormal.

Day 9 — fifth signal: the site reorganized with an “outlet” section

The competitor’s site gains a new section called “Outlet” in the menu — loaded with 40-60 SKUs marked down 35-50%. A change in the menu is a structural change, not a one-off. Here the team reaches its verdict: burn confirmed.

What these signals together were telling us

On their own, each signal has 4-5 innocent explanations. Combined over 9 days, they form a classic burn pattern:

• A lack of physical or financial room for the next collection.
• Tight cash flow (flat free shipping is expensive).
• A forecasting error on the previous collection (excess volume in low-rotation SKUs).
• Supplier pressure (a payment date coming up).

For the monitoring store’s sales team, this means: the competitor is vulnerable for the next 4-6 weeks. They won’t be able to deepen the promotion on a new collection because they have already spent their discount budget now.

What we did with the information

1. We brought the new collection launch forward by 9 days

To capture the audience that would naturally migrate to the competitor’s outlet. A short strategic window, but enough.

2. We kept full price on the anchor line

Without reacting with a discount — a competitor burning inventory indicates they no longer have promotional firepower. A customer who wants a new product pays full price.

3. We offered a 10% coupon to the email base

Enough to look competitive, low enough to preserve margin. Focused on converting the warm list, not on raw volume.

4. Recall through the story, not the price

The organic content focused on “the new collection has arrived” — differentiation by freshness, not by price. The audience migrating from the competitor’s outlet sees something new.

The result in 6 weeks

What this case teaches any e-commerce

What looked like 5 isolated competitor moves was, in fact, a single desperate strategy — only visible once you accumulate signals over several days. Anyone watching by sampling (a screenshot in a WhatsApp group) misses 4 of the 5 signals. Anyone monitoring systematically accumulates the full picture.

Batedor does exactly that: it collects every move (Instagram, Facebook, YouTube, the site), classifies it by intensity and type, and generates a chronological timeline. When 5 signals appear in sequence, the dashboard highlights it as a coordinated move.

10-minute weekly checklist

1. Did the competitor post a coupon bigger than their historical average?
2. Did they switch from conditional to flat free shipping?
3. Did a BOGO or “buy more, pay less” appear on a common SKU?
4. Was there a change in the site menu (a new outlet section, a clearance, etc.)?
5. Did they cut launch volume (few new-product posts)?

Check 3 or more “yes” answers in 14 days = a burn. Adjust your strategy before the customer migrates.