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Sales Analysis · See the Truth Behind the Numbers

Is rising revenue real growth or just seasonality? Which products are quietly falling behind? What share do your top customers contribute? Which sales rep has the highest average order value? SBK's sales analysis module answers these questions clearly with charts.

6
core analysis dimensions
20+
preset reports
T+1
data refresh timeliness
Capabilities

Six Dimensions to See Through Sales Performance

Not just "how much you sold" but "who you sold to, what you sold, and how you sold it"

📈 Revenue Trends

Multi-granularity trend lines by day / week / month / quarter / year, with YoY and MoM at a glance

🥇 Best-Seller Rankings

Rank by amount / quantity / gross margin to find the truly profitable hits

👥 Customer Contribution

Top customers' contribution share, identifying "high-value customers" and the risk of over-dependence on big accounts

💼 Sales-Rep Performance

Multi-dimensional comparison of reps by revenue / average order value / deals closed / gross margin

🌍 Regional Distribution

Tally revenue by province and region, with a map heatmap intuitively highlighting key markets

📝 Custom Dashboards

Turn key metrics into a sales dashboard, visible to everyone on the team at morning stand-up

ims.shangbangke.com/analysis/sales/trendTrends
AN
Sales Trend Analysis
YoYExport
$3.86MYTD
+18.2%YoY Growth
+5.4%MoM
$542KRolling Avg

Monthly Sales ($K)

420Jan
480Feb
610Mar
550Apr
740May

Sales Trends: Strip Out Seasonality to See Real Growth

Many companies celebrate a 20% monthly sales jump, but the same period last year may have grown 25%. SBK puts YoY, MoM and trailing-12-month trends on one chart, so you can see clearly whether it's a market-wide rise or your own capability improving.

  • Multi-granularity time series: day / week / month / quarter / year
  • YoY and MoM overlaid to strip out seasonality
  • Trailing-12-month average line to see the long-term trend
  • Forecast lines (linear / seasonally adjusted) to support decisions
ims.shangbangke.com/analysis/sales/customerContribution
CU
Customer Pareto
RFMExport
CustomerSalesShareCumul.
Jinpeng Logistics$860K22.3%22%
Ruida Machinery$620K16.1%38%
Henghui Electronics$480K12.4%51%
Yunqi Tech$360K9.3%60%

Top-Customer Cumulative (Pareto)

Top 4
60% of sales
Top 12
82% of sales
Other 86
18% of sales

Customer Contribution: Identify Big Spenders and Hidden Risks

The "80/20 rule" almost always holds for customers — 20% contribute 80% of sales. But who those 20% are, whether their contribution share is changing, and whether you're over-dependent on one or two big accounts are key to sales decisions.

  • Top customers' amount share + Pareto cumulative curve
  • Customer-level RFM segmentation: recency / frequency / monetary
  • Big-account contribution-change alerts (quarter-on-quarter drop > 20%)
  • Dormant-customer detection (no order in 90 days) linked to CRM follow-up prompts
Use Cases

Decisions Now Backed by Data

Monthly Performance Reviews

The sales director opens the dashboard: amounts / gross margin / rankings / anomalies all on one screen — review meetings get far more efficient.

Identify Slow Movers to Delist

Read the bottom of the best-seller list in reverse — SKUs with sales below threshold for 3 straight months start clearance or delisting.

Dedicated Big-Account Care

Top 20 customers get dedicated reps, CRM auto-tags them "VIP", and after-sales response levels are raised.

Sales Incentive Schemes

Reps with high AOV + gross margin get higher commissions; those relying on volume but low margin go back to training.

Related Features

Data Sources for Sales Analysis

Make Sales Decisions on a Solid Basis

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