Best Practices & Use Cases
- Best
Practices for Report Building
Leverage Suggested Templates first:Instead of building a complex setup entirely from scratch, load a pre-built template that matches your department and tweak its filtersBy
.Be Specific with AI Prompts:When using natural language input, state both your metric and time constraint explicitly (e.g.,"Show store metrics for last week") to get highly accurate auto-configurations.Group Data First SequenceAlways use the Organize RowsHierarchically:ByArrangepanelrowtogroupings fromadd thebroadestfieldscategoryyou want to group your data by; these will become your primary first columns.Pick Specific Metrics Use the Select Table Data panel to define the exact quantitative metrics you want to evaluate. Always Apply Filters Most reports require you to use Filter By to narrow the data down by a specific date range or condition to ensure relevance. Preview Before Finalizing Always click Generate Report to preview the configuration and data before completing the task. Save for Automation Click Save Report if you intend to reuse the exact layout or schedule it going forward.
General
|
Description |
| Use the |
Every report should be constructed using the three main panels: Organize Rows By, Select Table Data, and |
Report Use Cases & Configuration Best Practices
Sales Performance
|
Report |
What it tells you |
Organize Rows By |
Select Table Data |
Filter By |
|
Weekly Sales & Basket Trend |
How sales and average order value are moving day to day |
Sales Date |
Total Sales (After Tax), Total Bills, Average Order Value |
Sales Date = Last 7 Days |
|
City-Wise Sales Performance |
Which cities generate the most |
Store City |
Total Sales (After Tax), Total Customers, Total Bills |
Sales Date = This Year |
|
Category-Wise Sales Contribution |
Which product categories drive sales and volume |
Product Category |
Total Sales (After Tax), Total Units Sold, Unique Items Purchased |
Sales Date = This Year |
|
Month-over-Month Sales Growth |
Whether sales are trending up or down month to month |
Sales Month |
Total Sales (After Tax), Sales Growth % (vs Previous Month) |
Sales Date = This Year |
|
Units & Value Per Customer Trend |
How basket size (UPT) and customer value (VPC) are trending |
Sales Month |
Units Per Transaction (UPT), Value Per Customer (VPC), Average Order Value |
Sales Date = This Year |
|
First-Time vs Repeat Visit Trend |
What share of footfall is new vs returning, by month |
Sales Month |
First-Time Visits, Repeat Visits, Total Visits |
Sales Date = This Year |
|
Store-Wise Returns Report |
Which stores have unusually high return volumes |
Store Name, Receipt Number |
Item Price, Quantity |
Quantity < 0; Sales Date = This Year |
Customer Insights
|
Report |
What it tells you |
Organize Rows By |
Select Table Data |
Filter By |
|
New vs Repeat Customers by Store (Monthly) |
Acquisition vs retention performance, store by store |
Store Name, Sales Month |
New Customers (Monthly), Repeat Customers (Monthly), Repeat Customer % (Monthly) |
Sales Date = This Year |
|
Top Spenders Leaderboard |
Your highest-value customers, for VIP treatment |
Customer Name, Mobile Number |
Total Sales (After Tax), Total Visits, Average Order Value |
Sales Date = This Year; sort by Total Sales, descending |
|
Dormant Customer Win-Back List |
Customers who haven't shopped in a while — good for a win-back campaign |
Customer Name, Mobile Number, Home Store, Last Purchase Date |
Total Visits, Total Sales (After Tax) |
Last Purchase Date before [your cutoff, e.g. 6 months ago] |
|
Customer Recency by Tier |
How recently each loyalty tier's customers have shopped |
Loyalty Tier, Customer Name, Mobile Number |
Days Since Last Visit, Total Visits |
Sales Date = This Year |
|
Customer Base by Location |
Where your customers are concentrated geographically |
Customer City, Customer State |
Total Customers |
Sales Date = This Year |
Loyalty Program
|
Report |
What it tells you |
Organize Rows By |
Select Table Data |
Filter By |
|
Tier-Wise Loyalty Balance & Enrolment |
Points balance and new enrolments, by tier |
Loyalty Tier |
Loyalty Points Balance, New Enrolments |
Enrolment Date = This Year |
|
Loyalty Redemption Rate by Store (Monthly) |
How actively each store's customers earn vs redeem points |
Store Name, Transaction Month |
Points Issued, Points Redeemed, Points Value Issued, Points Value Redeemed |
Transaction Date = This Year |
|
Tier Upgrade Report |
Which customers moved up a tier, and when |
Loyalty Tier, Customer Name, Mobile Number, Tier Upgrade Date |
(none needed) |
Tier Upgrade Date = This Year |
|
Points Activity by Type |
Points issued, redeemed, and reversed, broken down by type |
Transaction Type |
Points Issued, Points Redeemed, Points Reversed (Issued), Points Reversed (Redeemed) |
Transaction Date = This Month |
Campaigns & Communication
|
Report |
What it tells you |
Organize Rows By |
Select Table Data |
Filter By |
|
Campaign ROI by Channel |
Which channels (SMS/Email/WhatsApp) deliver the best return |
Channel |
Campaign Spend, Attributed Sales, ROAS, Attributed Customers |
Campaign Date = This Month |
|
Top Campaigns by Attributed Sales |
Which campaigns drove the most revenue |
Campaign Name |
Attributed Sales, Attributed Customers |
Campaign Date = This Year; sort by Attributed Sales, descending |
|
Store-Wise Campaign Attribution |
Which stores benefit most from your campaigns |
Attributed Store, Campaign Name |
Attributed Sales, Attributed Customers |
Campaign Date = This Year |
|
Click-Through Performance by Campaign |
Engagement (sent/delivered/read/clicked) across campaigns |
Campaign Name, Channel |
Sent, Delivered, Read, Clicked |
Campaign Date = This Year |
Advanced (if Customer Segmentation is enabled on your account)
|
Report |
What it tells you |
Organize Rows By |
Select Table Data |
Filter By |
|
Segment-Wise Customer List |
Your customers grouped by RFM segment (e.g. Champions, Loyal, At Risk) |
Customer Segment, Customer ID, Customer Name, Mobile Number |
Loyalty Points Balance |
(none needed) |
|
At-Risk High-Value Customers |
High-value customers your segmentation model flags as at risk of churning |
Customer ID, Customer Name, Mobile Number |
Total Sales (After Tax), |
Customer Segment = [your "at risk" segment label]; Sales Date = This Year |