The boss opens their phone at 8 a.m. and sees yesterday's GMV, order count, average order value and repurchase rate; operations review campaign ROI, coupon redemption rate and distribution contribution every day. From traffic entry to conversion, from user segmentation to product contribution, every metric across the chain is clear at a glance — grounding every decision.
Real-time big screens + multi-dimensional reports + anomaly alerts — so every business move is grounded in data
GMV / orders / UV / conversion rate / live online count refresh at second level — hang it on a big screen in the big-promotion war room
Visit → browse → add-to-cart → order → pay → repurchase — diagnose the conversion rate of each step in the six-layer funnel separately
Sales rankings / add-to-cart rankings / favorites rankings / slow-mover detection — grounding merchandising and restock decisions
RFM segmentation, repurchase cycle, churn warnings and new-vs-existing customer ratio — member asset health at a glance
Each campaign's ROI, coupon redemption rate, distribution contribution and campaign AOV comparison — grounding review and improvement
A 30% YoY drop in GMV, an order surge, or a refund rate over 10% auto-pushes a notification — catch problems the moment they happen
Sales trend, last 7 days ($K)
The big-promotion war room hangs a 4K screen refreshing GMV in real time, and the operations director sees the same data the moment they open their phone; the boss checks the live leaderboard on the road, with the performance rhythm fully in hand. Everyone sees the same data — no more "what I see is different from what they see".
People per stage and step conversion
Is GMV falling short because of too little traffic or too little conversion? The funnel chart clearly breaks down the conversion rate of each of the six layers: how many drop from visit→browse, browse→add-to-cart, add-to-cart→order… find exactly which layer is the bottleneck and optimize it specifically.
Inactive for 30 days → step in early to win back
Three-dimensional segmentation by recency (R), frequency (F) and monetary value (M) automatically classifies members into 8 quadrants such as "high-value / high-growth / high-retention / general customers". Different quadrants get different marketing strategies, spending resources where they count.
Before the 9 a.m. morning meeting each day, open the mobile data cards: yesterday's GMV, order count, AOV, new members and refund rate — grasp the business rhythm in 5 seconds.
Do a campaign review after a big promotion: impressions, coupon-claim rate, redemption rate, campaign GMV and ROI — find the highest-ROI play to double down on next time.
Check the slow-mover report weekly; SKUs with fewer than 5 add-to-carts in 30 days are auto-listed, and operations decide to discount-clear or delist.
The RFM report shows a list of "high-retention customers" who haven't repurchased in 90 days, auto-triggering a combined retention-coupon + SMS campaign.
Data feeds back into business decisions, flowing to the product, marketing and member modules
Order data is the most fundamental source of GMV / AOV / refund rate
RFM segmentation results feed back into member tag / tier operations strategies
Campaign ROI data guides product selection and intensity for the next campaign
Monthly financial report data cross-validates with business data — reconciliation with zero discrepancy
Sign up to experience the full data analytics capabilities for free, or book a consultant demo