AI for Ecommerce Reporting: Kill the Sunday Deck

Why Sunday Decks Fail (and What Replaces Them)

The Sunday night deck is a tax on operations. Someone spends 2 - 4 hours pulling numbers from Google Ads, Shopify, Klaviyo, and a spreadsheet, formatting slides, and writing commentary that's half stale by Monday morning. By the time the team reads it, ad spend decisions are already locked in.

Scheduled AI briefs replace this with a standing automation: pull data from connected sources at a fixed time (Friday 5 PM, Saturday 6 AM, Sunday 8 PM - pick one), synthesize it into a structured brief, and deliver it to Slack or email before the team's Monday standup. The brief includes thresholds that flag anomalies, not just raw numbers. A human operator then writes the narrative and decision rules in 15 minutes, not 2 hours.

The shift is from "dashboard as source of truth" to "brief as decision input." Dashboards are for drilling. Briefs are for action.

The Core Fields: What Goes in the Monday Message

Not every metric belongs in a weekly brief. The brief should fit on one screen (or one Slack thread) and answer three questions: Did we hit plan? Where did we leak margin? What do we do Monday?

Start with these mandatory fields:

Revenue (actual vs. forecast, week-to-date and month-to-date)
ROAS by channel (paid social, email, organic, affiliate) - flag if below threshold (e.g., 2.5x for paid, 1.2x for email)
CAC and LTV by cohort (new vs. repeat) - flag if CAC exceeds 25% of first-order AOV
Inventory status (days on hand by category, stockouts, overstock alerts)
Margin (gross margin %, contribution margin by channel) - flag if below 40% gross or 15% contribution
Churn rate (email unsubscribes, repeat purchase rate) - flag if repeat rate drops >5% week-over-week
Ad spend pace (actual vs. daily budget, CPM and CPC trends) - flag if CPM up >15% or CPC up >10%
Top 3 SKUs by revenue and margin (not just revenue)
Refund rate and top refund reasons (flag if >3% of revenue)

Automation Thresholds and Decision Rules

A brief without thresholds is just a dashboard in prose. Define hard rules that trigger actions or escalations.

Example threshold matrix:

If ROAS < 2.0 for paid social: pause bottom 20% of campaigns by spend, flag for human review of creative
If CAC > 30% of first-order AOV: reduce paid spend by 10%, shift budget to email and organic
If inventory days on hand < 7 for top 3 SKUs: alert merchandising to reorder or reduce ad spend on those products
If repeat purchase rate drops >5% week-over-week: flag for retention team, check email deliverability and recent product issues
If refund rate > 3%: pull top 3 refund reasons, check if product-specific, alert QA or customer service
If margin < 40% gross: flag pricing, bundle, or discount strategy for review
If CPM up >15% or CPC up >10%: check audience saturation, pause underperforming segments, test new audiences

What Stays Human: Narrative and Trade-offs

Automation handles data synthesis and flag-raising. Humans handle narrative and trade-offs.

The Monday brief should include a 2 - 3 paragraph summary written by the operator or analyst: What happened? Why? What's the call? This is where judgment lives. Example: 'ROAS dropped to 2.1x this week due to iOS audience saturation and a 12% CPM increase. We're pausing the bottom 30% of campaigns and testing lookalike audiences. Expect a 1 - 2 week lag before ROAS recovers. In the meantime, we're shifting $2k of daily spend to email (current ROAS 3.2x) and organic (no CAC). Margin impact: neutral to positive.'

The brief should also include a decision queue: What needs approval? What's waiting on another team? What's the priority order for the week? This prevents the brief from being read and forgotten.

Connecting the Tools

A scheduled brief requires connectors to ads platforms (Google, Meta, TikTok), ecommerce platform (Shopify), email (Klaviyo, Klaviyo), and finance (Stripe, Shopify accounting). The connectors pull data on a schedule (Friday evening, Saturday morning, or Sunday evening) and load it into a single data layer.

The data layer doesn't need to be a data warehouse. A Google Sheet, Airtable, or simple SQL database works. The key is that all metrics are normalized to the same time period (week-to-date, month-to-date, same-week-last-year) and stored in one place.

Once data is unified, the brief generator (a script or low-code tool) reads from the data layer, applies thresholds, and outputs a formatted brief. The brief is then posted to Slack, emailed, or both.

Frequency and Timing

Weekly is the standard cadence for ecommerce reporting. It's frequent enough to catch problems before they compound, but infrequent enough to avoid noise.

Schedule the pull for Friday evening or Saturday morning (before the team's Monday standup). This gives the operator time to write narrative and decision rules Sunday evening if needed, but the brief is ready Monday morning without last-minute scrambling.

For high-velocity brands (>$50k daily revenue), consider a daily alert system that flags only exceptions (ROAS < threshold, inventory < threshold, refund rate > threshold). The weekly brief then focuses on trends and trade-offs, not daily noise.

Avoiding Common Pitfalls

Pitfall 1: Too many metrics. A brief with 30 metrics is a dashboard. Stick to 8 - 12 core fields. If a metric isn't actionable, cut it.

Pitfall 2: Thresholds that are too tight. If 50% of briefs trigger alerts, the alerts become noise. Set thresholds at the 75th - 90th percentile of normal variance. For a brand with 2.5x average ROAS and 10% weekly variance, the threshold is 2.0x, not 2.4x.

Pitfall 3: No narrative. A brief that's all numbers and flags is useless. The operator must write 2 - 3 paragraphs explaining what happened and why. This is the value-add.

Pitfall 4: Siloed briefs. If the ads team gets one brief and the merchandising team gets another, decisions conflict. Use a single brief that all teams read and respond to.

Questions

FAQ

How long does it take to set up a scheduled brief?

1 - 2 weeks. Week 1: define fields, thresholds, and data sources. Week 2: build connectors, test the brief generator, and run a dry run. The ongoing time per brief is 15 - 30 minutes for narrative and decision rules.

What if data sources don't have APIs or connectors?

Use a data integration tool (Zapier, Make, Stitch) to pull data from APIs and load into a central sheet or database. If a source has no API, export manually and upload to the data layer. This is slower but workable for 1 - 2 sources.

Should the brief include forecasts or just actuals?

Both. Include actual vs. forecast for revenue, ROAS, and margin. This shows whether the week is tracking to plan. Forecasts should be updated weekly based on current pace and historical seasonality.

Who writes the narrative and decision rules?

The operator or analyst who owns reporting. This is a 15 - 30 minute task, not a 2 - 4 hour task, because the data is already synthesized. Rotate the task across the team if needed to avoid burnout.

Want this on your account?

Thirty minutes. Bring the number that keeps you up.

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