You have an ERP for invoicing, a CRM for contacts, PDFs for spec sheets, spreadsheets for allocation, and email for everything else. Six tools, six silos — and the launch intelligence that would transform your product cycles captured nowhere.
Each layer multiplies. Each combination needs a price, an allocation, and a margin. Or a platform.
Most CE brands run six disconnected tools. Here is what changes when they become one platform.
Rep opens a PowerPoint. Flips to the comparison slide. Reads numbers aloud. No data captured about which specs the retailer focused on. After the appointment, the preference is a memory.
Interactive generation comparison on screen. Spec by spec with upgrade percentages. Every spec the retailer lingers on is captured. After 200 appointments: you know which specs sell upgrades per channel.
Production split based on last cycle’s orders. No visibility into browsing patterns during pre-order. Colour overstock discovered post-launch when it is too late to adjust.
Pre-order browsing data shows colour and storage preference weeks before production lock. Shifts detected across channels in real time. Overstock risk quantified before commitment.
Allocation based on relationship, not performance. The loudest retailer gets the most stock. No visibility into commitment velocity or sell-through history. Wave 2 timing is a calendar guess.
Commitment velocity, sell-through history, and channel performance scored per retailer. AI recommends wave 1 vs wave 2 allocation. Transparent, auditable, data-driven.
Accessory orders happen separately from device orders. No visibility into attach rates per retailer. No bundle optimisation. The highest-margin category is managed by accident, not strategy.
Attach rates tracked per device, per retailer, per channel. Bundle suggestions based on conversion data. Accessory crossover day predicted. The margin multiplier is a managed metric, not a hope.
Hero films, teardown footage, lifestyle content — all produced at significant cost. No connection between showroom engagement and portal orders. Content budget follows creative instinct.
Showroom and Remote watchtime correlated with allocation commitments. Hero film, teardown, and lifestyle content each measured per channel type. Budget follows evidence.
Violations discovered from customer complaints or competitor reports. By the time you act, the pricing signal is damaged. Enforcement is manual and inconsistent across channels.
MAP pricing locked per product per channel at every touchpoint. Violations flagged within 24 hours. AI detects which retailer types violate at which cycle stage. Enforcement timed proactively.
Each launch starts from a forecast based on last cycle’s orders and management intuition. The same conversations. The same guesses. The same overstock risk.
Each launch starts from the last one’s structured data: spec preferences, colour demand, allocation velocity, accessory patterns, content ROI, retailer health. Intelligence compounds. Risk shrinks.
The cost of a toolstack is not the licence fees. It is the intelligence you never capture.
Consider what happens at every product launch when your tools are disconnected. Your rep presents the new flagship at a trade fair. The retailer compares specs, browses colours, asks about storage tiers, and discusses allocation. On the Sales App, every toggle is a data point. On a PowerPoint, it is a memory that fades within days.
The retailer logs into the portal two weeks later. Without connection to the trade fair appointment, they start from scratch. The colour they preferred? Not carried over. The storage tier they asked about? Not pre-selected. The accessory bundle the rep discussed? Not suggested. Every friction point is a lost conversion opportunity — and a lost data point.
Meanwhile, your showroom hosts 40 retailer visits per month. Each retailer watches different content for different durations. Which hero film drives allocation commitments? Which teardown scene gets replayed? Without connecting showroom engagement to portal orders, your content budget is an act of faith rather than a measured investment.
The accessory margin — your actual profit driver — runs on a separate system. Earbuds attach at 82% for premium chains but only 51% for online retailers. Cases show the reverse pattern. Without this data in the same system as device orders, you cannot optimise bundle defaults per channel. You cannot predict the accessory crossover day. You cannot measure the margin multiplier that justifies your entire ecosystem strategy.
After three product cycles, a brand on disconnected tools has three folders of quarterly reports. A brand on a platform has structured launch intelligence: which specs sell per channel, which colours per market, which accessories per retailer type, which content converts, and how fast each account commits. The first brand forecasts. The second brand predicts. The gap compounds with every cycle.
Product quality is converging. Multiple brands ship comparable flagship devices within weeks of each other. The spec gap between top-tier competitors narrows with every generation.
The brands that win are the ones who know which colours to produce before production lock, which retailers to brief first, which accessories to bundle per channel, and which content drives allocation commitments. That knowledge comes from structured launch data — not from trade fair conversations remembered imperfectly.
FIRE gives consumer electronics brands this knowledge. Not as a one-time report, but as a compounding data asset that grows every product cycle, across every channel, with every retailer interaction.
Specs, colours, allocation, accessories, MAP — one platform, compounding every cycle.
See the PlatformTell us about your brand, your current B2B setup, and what you are looking to improve. We will show you exactly how FIRE works for your specific situation.
No generic demos. No slide decks. A real walkthrough with your products and your industry configuration.
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