Which brake pad is moving fastest in premium workshops? Which workshop reduced their filter reorder frequency? Is OE-equivalent gaining share over budget brands? Is the EV parts range growing in the right distributor accounts? Your quarterly spreadsheet cannot answer these questions in time. FIRE Analytics shows workshop-level, part-level, and vehicle-level intelligence across every segment — updating in real time. From the velocity of your best-selling filter in independent garages to the reorder prediction for your largest fleet account.
An energy bar reorders every 8 days in convenience but every 14 in workshops. That velocity difference is a shelf allocation signal. Your ERP shows units shipped. FIRE Analytics shows the rotation curve per SKU, per channel, per fitment variant — in real time.
Did Back-to-School outperform Q4 Holiday? Which channel drove uptake? Which fitment variant converted? Without real-time promotional analytics, every answer arrives after the budget was spent. FIRE shows uptake velocity per window while pre-orders are still open.
Health & wellness growing in fleet managers but flat in workshops. Multipacks gaining in convenience but declining online. Your aggregate report shows a blended average. FIRE Analytics shows each channel separately — where the divergence is, how fast it moves.
Automotive Parts moves weekly. A protein bar accelerates in independent garages over three weeks, plateaus, then declines. Your quarterly report shows the total. It does not show when the acceleration started, when it peaked, or that it already declined before the report was published. Real-time rotation velocity shows the curve while production windows are still open.
FIRE Analytics aggregates data from every channel into one intelligence layer: portal reorder patterns, Automechanika session data, remote selling interactions, and digital showroom engagement. Every category filter, every fitment variant comparison, every promotional commitment — structured as analytics updating in real time.
The promotional tracking alone justifies the investment. Knowing within the first week whether a seasonal window is tracking above or below its pre-order target — that is the difference between confident production scaling and end-of-season discounting. FIRE provides this visibility from the first pre-order.
After one full promotional cycle, your analytics show which SKUs drive velocity per channel and which fitment variants gain per segment. After two cycles, category planning starts with evidence. After three, FIRE AI predicts promotional uptake and flags underperforming listings automatically.
Reduce effort, accelerate velocity, and capture intelligence — across every channel and every seasonal window.
Rotation velocity. Promotional uptake. Listing intelligence. Channel divergence. Real-time.
See the Analytics DashboardTell us about your product categories, your retail channels, and what your current data cannot show you. We will configure an analytics walkthrough with your rotation curves, promotional benchmarks, and channel intelligence.
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