Sales History

View historical sales data in Tether

Sales History

The Sales History view shows your actual historical sales data. It’s essential for understanding past performance, validating forecasts, and identifying trends.

Accessing Sales History

Navigate to Demand Forecast → Sales History (or Sales History in the sidebar for Sales Rep users).

Sales History is available to both Admin and Sales Rep users, making it accessible for the entire team.

What is Sales History?

Sales History displays actual sales transactions that have occurred:

Data Point	Description
Units Sold	Quantity sold
Revenue	Sales value (if tracked)
By SKU	Broken down by product
By Channel	Broken down by sales channel
By Period	Daily, weekly, or monthly

Sales History View

Layout

The Sales History view uses a similar layout to the Forecast Dashboard:

• Filter Panel (left) - Filter by channel, product, etc.
• Data Table (center) - Historical sales by period
• Time Controls (top) - Date range and aggregation

Table Columns

Column Type	Content
Row Identifiers	SKU, Channel, Collection
Period Columns	Sales for each time period
Totals	Row and column sums

Viewing Historical Data

Date Range Selection

1. Click Date Range

   Open the date range picker

2. Select History Period

   Choose how far back to look:

   • Last 30 days
   • Last 90 days
   • Last 12 months
   • Custom range
3. Apply

   Data refreshes to show selected period

Aggregation Levels

Level	Best For
Daily	Recent detailed analysis
Weekly	Short-term trends
Monthly	Long-term patterns
Quarterly	Strategic overview

Grouping Options

Group historical data by:

• Channel
• Collection
• Product hierarchy
• SKU

Filtering Sales History

By Channel

View sales for specific channels:

1. Open Channel filter
2. Select channels
3. See only sales from those channels

By Product

Focus on specific products:

1. Use Collection or SKU filters
2. Select products to view
3. Data shows only selected items

By Time Period

Beyond date range, filter by:

• Day of week
• Specific months
• Comparable periods (same month last year)

Comparing to Forecasts

Side-by-Side View

To compare sales history with forecasts:

1. Go to the Forecast Dashboard
2. Enable both “Sales History” and “Forecast” metrics
3. View actual vs. predicted in the same table

Variance Analysis

Column	Description
Forecast	What was predicted
Actual	What actually sold
Variance	Difference (Actual - Forecast)
Variance %	Percentage difference

Reading Variances

Variance	Meaning	Action
Positive	Sold more than forecast	Good news, may need supply
Negative	Sold less than forecast	Review why, check inventory
Zero/Small	Forecast was accurate	Forecasting is working well

Sales Trends

Identifying Patterns

Look for:

Seasonal Patterns:

• Higher sales in certain months
• Holiday peaks
• Weather-related changes

Growth/Decline:

• Consistent month-over-month changes
• Year-over-year comparisons
• Product lifecycle stages

Channel Patterns:

• Channel-specific seasonality
• Promotional impacts by channel
• Channel growth rates

Trend Indicators

Pattern	What It Looks Like
Growth	Values increasing over time
Decline	Values decreasing over time
Seasonal	Regular peaks and valleys
Steady	Consistent values period to period

Year-over-Year Comparison

Compare current period to same period last year:

Setting Up YoY View

1. Select This Year's Period

   Choose the current period you’re analyzing

2. Add Comparison

   Enable “Compare to Prior Year” option

3. View Results

   See both years’ data side by side

YoY Metrics

Metric	Description
This Year	Current period sales
Last Year	Same period prior year
Change	Difference in units
% Change	Percentage growth/decline

Exporting Sales Data

Export Options

1. Set Filters

   Configure view with desired filters and date range

2. Click Export

   Click the Export button

3. Choose Format

   Select:

   • CSV - For data analysis
   • Excel - For formatted reports
4. Download

   File includes all visible data

Export Uses

• Detailed analysis in Excel
• Input to other planning tools
• Sharing with stakeholders
• Archive for records

Period Completion Status

Some views show period completion:

Status	Meaning
Complete	Full period, all data in
In Progress	Current period, data still coming
Estimated	Some data may be delayed

Recent periods may show incomplete data if sales are still being processed or synced.

Integration with Forecasts

Sales history feeds into forecasting:

How Forecasts Use History

1. Baseline - Historical patterns establish baseline
2. Trends - Growth/decline rates inform projections
3. Seasonality - Past seasonal patterns project forward
4. Model Training - Algorithms learn from history

Data Quality Impact

Better history data = better forecasts:

• Complete data improves accuracy
• Consistent tracking helps patterns
• Flagged anomalies prevent distortion

Best Practices

Regular Review

Check sales history regularly:

• Weekly: Recent performance
• Monthly: Trend analysis
• Quarterly: Strategic review

Investigate Anomalies

When you see unusual patterns:

• Was there a promotion?
• Were there supply issues?
• Market event?
• Document for future reference

Compare Year-over-Year

Use YoY comparisons to:

• Understand seasonal patterns
• Measure growth
• Validate forecasts

Export for Analysis

Export data for deeper analysis:

• Create charts and visualizations
• Perform statistical analysis
• Share with leadership

Troubleshooting

Missing Sales Data

Possible causes:

• Integration sync delay
• Date range doesn’t include data
• Data wasn’t imported

Solutions:

1. Check integration status
2. Expand date range
3. Verify data import completed

Data Doesn’t Match Source

Possible causes:

• Returns not processed
• Timing differences
• Aggregation method differs

Solutions:

1. Check if returns are included
2. Verify period definitions match
3. Confirm aggregation logic

Next Steps

Forecast Dashboard

Compare history to forecasts

Forecast Comparison

Compare forecast models

Filtering

Learn to filter data effectively

Integrations

Set up sales data sync