Sales Performance (standard sales dashboard for URS)

The Sales Performance Dashboard is a general template used across Daasity for omnichannel sales reporting, and all source-specific sales performance dashboard templates.

Overview

The Sales Performance Dashboard is a general template used across Daasity for omnichannel sales reporting. It provides a high-level view of your sales performance and is the basis for many source-specific dashboards (e.g. POS retail data, DTC eCommerce, Amazon). This dashboard helps business users answer fundamental questions: “How are my sales trending? Which products or locations drive revenue? Where should I focus to improve performance?” It accommodates different data sources by highlighting whichever metrics are available for that source, while keeping a consistent layout and methodology.

Key Use Cases:

• Evaluate overall sales trends over time (daily, weekly, or monthly) and year-over-year (YoY) growth.

• Identify top-selling products and top-performing markets or channels.

• Monitor key performance indicators (KPIs) like revenue, units sold, and, when available, distribution and velocity metrics to diagnose growth drivers.

Dashboard Layout and Features

*(Include a screenshot of the Sales Performance Dashboard’s top section, showing the KPI summary and trend chart, for reference.)

• KPI Summary Bar: At the top, the dashboard highlights a set of KPIs for the selected time period. Typical KPIs include Total Sales (revenue), Units Sold, and growth rates vs prior year. For retail datasets with syndicated metrics, this section may also show distribution and velocity metrics. For example, % ACV Distribution (the percentage of total market sales coming from stores carrying your product) and Velocity (sales per distribution point) are key drivers when availableen.wikipedia.orgmicrosites.nielseniq.com. Velocity is often expressed as dollars per TDP (Total Distribution Points), meaning sales per 1% of market ACV – a core indicator of how well your product sells when it’s on shelfmicrosites.nielseniq.com. If the data source doesn’t support certain metrics, the dashboard will automatically omit or replace them with the closest available equivalents. (See the Metrics Dictionary for detailed definitions of each KPI.)

• Sales Trend Chart: Beneath the KPIs, a time-series chart plots sales over time (by week, day, or month) with comparisons to the prior year. This helps you visualize seasonality and growth. A year-over-year line or annotations may be included to quickly show YoY % change each period. Use this chart to spot trends (e.g. peaks during promotions or holidays) and to ensure current performance is tracking against last year’s benchmarks.

• Product Breakdown Table: The next section is a ranking table of products (e.g. by Brand, Category, or SKU, depending on context). It lists each product’s key metrics – typically the same ones shown in the KPI bar (sales, units, etc., plus any distribution or velocity metrics) – for the selected period. It also includes comparison columns like % change vs last period or YoY. By default, this table is sorted by revenue, showing you at a glance which products contribute most to sales. The consistent inclusion of KPIs across the top and in this table means you can easily scan how each product performed on each metric. For example, you might see that Product A has higher sales than Product B, but if Product A also has much higher distribution, then Product B might actually have a stronger velocity (sales per point of distribution) once distribution is accounted formicrosites.nielseniq.com. This table helps identify your star products and those that underperform relative to their distribution.

• Location/Channel Breakdown Table: A similar table provides a breakdown by location or channel. In a retail POS context, this might show metrics by Region or Retailer; in an omnichannel DTC context, it might be by Sales Channel or Country. The columns mirror the KPI metrics (sales, units, etc., with growth rates), so you can see where your business is strongest. For instance, you may find one region is contributing the majority of sales or that a particular retailer has a higher share of sales than others – insights that can inform distribution strategy. If viewing syndicated retail data, these location breakdowns can highlight distribution gaps (e.g., a low % ACV in a certain region indicating distribution opportunity).

• Time Period Detail Table: Many Sales dashboards include a detailed table by time period (e.g. by week for the last 52 weeks). Each row represents a week (or day/month) with the key metrics, so you can inspect exact values and period-over-period changes. This is useful for power users who want the granular data or to export for further analysis. For example, after a big marketing campaign, you could look at the specific week to quantify the sales lift.

• Product Detail (Drill-down) Table: In some cases, a more detailed SKU-level table is included (especially if the main product breakdown is at a higher level like brand). This Product Detail section might list individual SKU or UPC performance along with attributes like size, flavor, etc. It ensures that for any product category roll-ups, you can drill down to the lowest level to identify which specific items are driving trends. (If your dashboard’s primary breakdown is already SKU-level, this section might be omitted as it would be redundant.)

Source-Specific Notes: This dashboard template is designed to be source-agnostic. For each data source (Shopify, Amazon, NielsenIQ/IRI syndicated data, etc.), the structure remains the same while the metrics adjust to what’s available. For example, a DTC platform may not have an ACV distribution metric, so its dashboard would stick to sales, orders, AOV, etc., whereas a NielsenIQ/Spins retail dashboard would include distribution (% ACV) and velocity. No matter the source, the top KPIs are also used as default columns in the tables below, creating a familiar experience as you navigate between different channel dashboards. This modular approach makes the documentation easier to maintain – we document each metric once in the metrics reference, and each dashboard page like this one can simply refer to those definitions. (For detailed definitions of metrics like ACV, velocity, etc., see the Understanding Your Data section or Metrics Dictionary. For source-specific metric availability, refer to the documentation for that integration.)

Tips for Using the Sales Dashboard

• Identify Drivers of Growth: Compare the YoY% in the trend chart with changes in distribution and velocity. For instance, if sales are up 20% YoY, check if %ACV Distribution grew (meaning you are in more stores) or if velocity (sales per store) grew – or both. Industry research shows that distribution is often the single largest driver of market share differences (accounting for over 50% of variation), so a big part of growth could be getting onto more shelves. Velocity improvements (more sales per store) indicate strong consumer demand or successful marketing at the store level. Understanding which factor is driving your growth will inform whether you need to focus on sales fundamentals (velocity) or distribution expansion.

• Spot High Performers and Underperformers: Use the product ranking table to see which products are outperforming or lagging. For example, a product with high sales but low growth might be reaching saturation, whereas a product with lower sales but high velocity could have huge upside if you increase its distribution. Look at the Distribution column: if a product has, say, only 30% available distribution but a high dollar velocity, it means it sells very well where it’s available – a clear sign to push for broader distribution. Conversely, if a product has high distribution but low velocity, resources might be better spent on improving its marketing or considering a SKU rationalization.

• Compare Regions/Channels: The location breakdown helps identify strategic focus areas. If one region shows much lower sales or distribution, it could be an untapped opportunity or an execution issue. If you have syndicated data, you might find that your market share in one retailer is lower despite similar distribution – indicating stronger competition or pricing differences in that retailer. These insights can guide sales and trade marketing teams where to prioritize efforts.

• Leverage Time Detail for Seasonality: By examining the week-by-week table, you can pick out seasonal peaks (for example, a lift in November/December for holiday season, or summer spikes if you sell seasonal products). Use this to plan inventory and promotions. If certain weeks underperformed expectations, cross-reference if those align with distribution changes or out-of-stock issues (e.g., a sudden drop in one week might indicate a supply disruption or a lapping of a one-time promotion last year).

This Sales Performance Dashboard is your go-to starting point for retail analytics. Once you understand the overall picture here, you can drill into more specialized dashboards (like syndicated data dashboards for competitive analysis, such as Brand Performance, Pricing Analysis or our suite of Promotional Analysis dashboards across all of your sales channels) for deeper analysis. Remember, the framework here is consistent: KPIs up top, trend chart, and diagnostic tables. Mastering this template will make it easy to navigate any source-specific performance dashboard Daasity provides.