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Rank our top 10 products by net revenue for the last 30 complete days. Look up the net revenue definition first. Show revenue and units per product, compare with the previous 30 days, and state how refunds and cancellations are treated before drawing conclusions.

Show daily funnel step counts and conversion rates for the last 30 complete days. Look up the funnel step definitions first. Highlight the steps with the largest drop-off, compare with the previous 30 days, and flag instrumentation gaps before drawing conclusions.

Show the refund rate by product and the most common return outcomes for the last 90 complete days. Look up how this account records refunds and returns first. Rank products by refund rate, state the valid-order definition and window, and flag unlinked refunds before drawing conclusions.

Measure discount reliance for the last three complete months. Show discount value as a share of gross revenue by month, then break the latest month down by discount code, product, and sales channel. Look up how this account records discounts first. State the window and included stores, and flag orders with missing discount records before drawing conclusions.

Break revenue and orders down by sales channel for the last complete quarter with monthly detail. Look up how this account classifies sales channels first. Show each channel's share and trend, compare with the previous quarter, and state the channel definitions and included stores before drawing conclusions.

Flag stockout risk using the latest inventory snapshot and the last 30 complete days of unit sales. Rank at-risk products by estimated days of cover, showing units sold, available inventory, and location where present. State the inventory source, snapshot date, and included locations, and flag products with missing inventory or sales history instead of guessing.

Rank product pairs by how often they appear on the same order in the last 90 complete days. Look up the valid-order definition first. Show order counts and attach rates for the top pairs, state the window and included stores, and flag incomplete line-item history before drawing conclusions.

Show gross margin by product for the last complete quarter. Look up how this account records product costs first. Rank products by margin, state the cost definition and window, and flag products with missing or stale costs instead of ranking them.

Check data freshness across the connected sources. Show the latest record date per source and flag feeds that are stale or missing against their expected cadence. State how freshness is measured for each source, and distinguish a delayed feed from one this account never connected.

Review support contacts for the last 30 complete days. Show ticket volume by topic and channel with resolution times, and rank the drivers worth addressing. State the topic taxonomy and window, and flag untagged tickets before drawing conclusions.

Compare acquisition performance for the last complete week against the week before. Look up the available definitions and data first. Show spend and new-customer measures by supported channel, identify coverage gaps, and distinguish attribution from causal lift.

Review the last complete week's ad creative performance using the SourceMedium data available to this account. First check whether ad-level data and creative identifiers are present. Compare spend and available conversion measures across creatives with comparable exposure. Flag small samples and missing creative metadata. Prepare a testing brief with the evidence, questions to investigate, and proposed next tests. Do not change campaigns or treat attribution as causal lift.

Check whether this SourceMedium account has partner or affiliate identifiers linked to orders and customer history. If it does, compare new-customer revenue and repeat purchase behavior by partner at equal cohort ages. State how orders are assigned to partners, the observation window, and any missing history. Prepare a partner review that distinguishes observed results from possible explanations. If the required records or joins are unavailable, explain what is missing instead of ranking partners.

Compute our customer acquisition cost overall and by supported channel for the last complete month. Look up the available spend and new-customer definitions first. Show spend, new customers, and CAC by channel, compare with the previous month, and flag spend or orders that cannot be assigned. State the new-customer definition and reporting window before drawing conclusions.

Review our marketing efficiency for the last complete month against the previous month. Compare total marketing spend with order revenue using SourceMedium definitions, show efficiency by supported platform, and separate observed changes from explanations that need investigation. State the stores, currency, and reporting window, and flag missing spend or unattributed revenue before drawing conclusions.

Compare the first-touch and last-touch channel mix for purchases in the last complete month. Look up which attribution models this account supports first. Show how channel credit shifts between the two views, state the model, window, and included channels, and flag journeys with missing touchpoints. Distinguish observed credit from causal lift.

Rank platform and campaign-type combinations by ROAS for the last 30 complete days. Look up the available spend and revenue definitions first. Show spend, attributed revenue, and ROAS with a minimum-spend threshold so small tests do not top the ranking. State the attribution method and window, and flag spend or revenue that cannot be assigned before drawing conclusions.

Check whether creator or partner codes are leaking beyond their audience in the last 60 complete days. Compare the customers using each code against the audience signal available to this account, such as survey responses or referrers. Rank suspect codes by order count and revenue, state the audience signal and window, and flag thin evidence before naming a leak.

Build a holiday readiness brief from the last complete holiday window and the prior 14-day baseline. Compare daily revenue, ad efficiency by platform, and promo reliance between the two windows. State the exact windows, stores, and currency, and flag incomplete history before recommending where to concentrate this year.

Find the highest-leverage ways to raise average order value over the next 30 days. Break current AOV into its drivers using the last 90 complete days, compare against the prior period, and rank levers by expected impact while protecting conversion rate. State the AOV definition and window, and flag segments too small to trust.

Rank landing pages by purchase conversion rate for the last 30 complete days. Look up how this account attributes sessions and purchases first. Show sessions and conversion per page with a minimum-traffic threshold, state the window, and report only what the rows prove without guessing why visitors behave as they do.

Compare revenue and acquisition efficiency by region for the last complete quarter. Look up how this account classifies regions first. Show each region's revenue, spend, and efficiency with trend, state the window, and flag unclassified records before drawing conclusions.

Find the search terms consuming spend without conversions in the last 30 complete days. Look up whether this account has search-term records first. Rank wasteful terms by spend with a minimum-spend threshold, state the match types and window, and if search-term records are unavailable, explain what is missing instead of guessing.

Compare repeat purchase behavior across first-purchase cohorts using the SourceMedium definitions available to this account. Compare cohorts at the same age, state the observation window, and flag incomplete history. Show the evidence behind the comparison.

Split our revenue into subscription and one-time orders for the last six complete months. Look up how this account flags subscription orders first. Show the monthly split and trend, state the subscription definition and reporting window, and flag orders that cannot be classified before drawing conclusions.

Rank products by how often they appear on customers' second orders in the last complete quarter. Look up the valid-order definition first. Show the top products with order counts, state the observation window and included stores, and flag incomplete history before drawing conclusions.

Investigate unattributed orders in the last complete month. Measure the unattributed share, inspect UTM coverage and tracking completeness, and identify the patterns behind the gaps. State the attribution method and window, distinguish missing data from untracked journeys, and recommend what to fix first. Do not guess at causes the data cannot show.

Split customers and revenue into new and repeat for the last six complete months. Look up the new-customer definition first. Show the monthly split and trend for both customer counts and revenue, state the definition and window, and flag history gaps before drawing conclusions.

Rank products by how often they appear on first orders in the last complete quarter. Look up the valid-order definition first. Show the top products with order counts, state the observation window and included stores, and flag incomplete history before drawing conclusions.

Compare customer lifetime value by acquisition channel for first purchases in the last 12 complete months. Look up the LTV and new-customer definitions first. Show LTV at equal cohort ages, state the window and maturity, and flag immature cohorts before ranking channels.

Find which first-order traits predict repeat purchases for first orders in the last 12 complete months. Compare repeat rates by channel, discount use, and product type at equal cohort ages. State the repeat definition and window, and flag thin cohorts before drawing conclusions.

Shortlist lapsed customers worth winning back. Segment customers with no order in the last 90 complete days by past value and order count, and rank segments by expected return. State the lapse definition and window, and flag customers with unresolved support or refund history before targeting them.

Prepare a trading review for the last complete week. Compare revenue, orders, and acquisition costs with the previous week. Use SourceMedium definitions, state the stores and timezone, and flag missing data before drawing conclusions.

Prepare a daily trading pulse for yesterday. Compare revenue, orders, and ad spend against the prior same weekday and the trailing seven-day average. Confirm data freshness first, flag anomalies with their size, and close with the two or three items worth raising at today's standup. Do not diagnose causes the data cannot show.

Review the last complete month against the month before. Compare revenue, orders, marketing spend, and efficiency using SourceMedium definitions. State the stores, currency, and window, flag missing spend or unattributed revenue, and close with the open questions that matter for next month.

Prepare a quarterly business review for the last complete quarter with monthly detail. Cover revenue trend, acquisition efficiency, and repeat behavior using SourceMedium definitions. State the window and included stores, separate observed changes from explanations that need investigation, and close with three priorities for next quarter.

Run the daily sale check for yesterday. Compare revenue, orders, promo reliance, and ad efficiency against the pre-sale baseline and the sale targets. Confirm data freshness first, flag channels overspending, codes spiking, and products nearing stockout, and close with today's adjustments. State the baseline window and targets before recommending changes.

Draft the monthly investor update from the last complete month and the trailing three-month trend. Lead with revenue, growth, and efficiency, then name the month's wins and misses with the evidence behind each. State the window and definitions, avoid attributing outcomes the data cannot prove, and close with asks and next month's focus.

Run the post-mortem on the last complete sale window against the prior 14-day baseline and the sale targets. Compare revenue, efficiency, promo reliance, and new-customer mix. State the windows and targets, separate observed results from explanations that need investigation, and close with lessons for the next sale.

Draft next quarter's plan from the trailing two quarters. Set revenue, efficiency, and retention baselines by month, propose targets by channel, and name the bets that close the gap. State the windows and definitions, avoid presenting projections as commitments, and close with open questions for the planning review.