Combined figures recompute when you select campaigns above. Shopify figures are last-click UTM attributed from the order customer journey (real, native Shopify data). Across all four campaigns $1,407.65 of the $1,737.47 total sales is attributed to a campaign, the remaining $329.82 came in organic, direct or without a journey (including the $239.85 bundle). Link clicks are only known at the account total, so they show n/a for a subset.

How this period compares to the one before it of the same length.

The whole funnel follows the date picker. Sessions, add to cart and checkouts are store-wide from Shopify Analytics (all traffic sources, not only Meta); link clicks and purchases are Meta.

Inventory levels not connected yet. Wire in Shopify inventory counts to see runway, daily sell rate and auto-computed reorder dates per variant.

Country-level session breakdown is not pulled into this snapshot yet.

Total discounts Jun-Jul 2026: $1,065.09 across 23 paid orders, equal to 38.0% of gross sales ($2,802.56). Discounts are the single largest cost after ad spend. Per-code breakdown is not pulled yet.

No data yet. RFM scoring requires repeat-purchase history, which does not exist after only one month of sales.

A high CPA is expected in a cold-traffic launch; the target is under $50 at scale. The break-even ceiling rises once a repeat-purchase rate settles, because LTV lets you absorb a higher first-order cost.

COGS is the strips plus the Deep Sleep Mask on first 3-box and one-time orders; repeat 3-box ships without the mask. Card fee: 2.9% + $0.29 per order (Shopify Payments international rate). Blended margin uses the actual order mix, not a planning assumption.

Jun 2026: paid CPA is $143.61 ($3,303 spend on 23 orders). Blended ROAS 0.53, Meta ROAS 0.45. At AOV $71.94 and first-order break-even of $43.70, we are buying orders above our own margin - payback requires at least one repeat order. This is expected in a cold-traffic launch. As creative improves and the audience warms, CPA falls. Once a repeat rate is established, the blended CAC (which will include organic and direct orders) will close the gap to the $43.70 ceiling.

These are first-run numbers off a cold audience with no prior creative history. The CPA gap closes through better creative (lower CPC), warmer audiences (higher CVR) and repeat orders layering on top. CAC payback can be computed once the June 2026 cohort has had 60 days to reorder.

No data yet. Only June 2026 has real numbers. CAC trend, word-of-mouth share and referral coefficient need several months of comparable data. Revisit after August 2026 when three full months can be compared.

No data yet. Inventory value, reorder schedule and 3PL payment terms are not in this snapshot. Add stock levels and supplier terms to the intake doc to enable the cash conversion cycle view.

No data yet. Upload a 3PL invoice to the intake doc and re-run /collect-data. This section rebuilds the expected fulfillment cost from Shopify order volume and flags any lines that deviate from contract rates.

No data yet. Cohort LTV needs at least two months of repeat-purchase history. Jun 2026 is the first full month. This section opens once the June cohort has had 60+ days to reorder (August 2026).

Full path from revenue down to contribution profit. Ad spend at 190% of revenue is the defining feature of a cold-traffic launch. The gross margin on the product itself (78.5%) is strong - the only variable that needs to move to reach profitability is CPA.

Contribution profit = net revenue minus COGS, fees, refunds and ad spend. A 4% refund floor is applied as a structural buffer even when actual refunds are lower. Operating profit subtracts fixed monthly costs on top of contribution.

Payment processing fees (2.9% + $0.29 per order) are already captured in the contribution P&L above as variable costs - no double count here. UpPromote's 1.5% variable commission applies only to affiliate-driven orders and is excluded from the fixed total. Operating profit = contribution profit less this total.

No data yet. A spend-response curve needs several distinct spend levels over time. Jun 2026 gives a single data point ($3,303 spend, ROAS 0.53). The curve and scenario planner unlock after a few months of varied spend.

No data yet. The scenario planner runs on the spend-response curve above. Unlocks alongside it. Currently: $3,303 spend produced 23 orders at $143.61 CPA and -$1,996 contribution. Scale by reducing CPA, not by adding spend to the same creative.

LTV:CAC below 1.0 means each customer returns less than one acquisition dollar on the first order alone. Reaching 1.0 on contribution needs either a lower CPA or more repeat orders per customer. These numbers update as the cohort reorders.

M1 (first repeat window) opens once a cohort has had 30+ days: 1-box 4-week subscribers reorder first, the 3-box 12-week cycle later. Cancelled subscribers count as churn from the cohort. Heatmap cells fill in green as data matures.

A 0% rate is expected before any customer has had 30+ days to reorder. The meaningful read on product strength comes once the first subscription windows close and we count who reordered versus who cancelled.

No data yet. June 2026 is the first sales month, so no repeat cohort history exists. These curves populate automatically from actual reorder data once the first subscription windows close (expected Aug 2026 onwards). No projected curve is drawn in the meantime.

Every Sunday you export all subscriptions from the Kaching Subscriptions app and upload it here. The dot turns orange after 8 days and red after 11 days, so you always know when the recurring numbers need a refresh. Thresholds: green 0-7 days, orange 8-10, red 11 or more.

MRR sums each active subscriber's monthly-equivalent revenue (a 3-box billed every 12 weeks counts as a third of $89.97 per month; a 1-box is billed every 4 weeks). Early read: the longer, bigger cadence retains better, possibly because users feel they have enough time to see results.

Gross monthly churn rate = churned MRR / starting MRR. A high first-month rate here is driven entirely by the 1-box cadence.

The 3-box plan charges less often (every 12 weeks vs every 4) but bills a larger amount per delivery, so it generates steadier MRR per subscriber than the 1-box plan.

Cancellations concentrate entirely in the 1-box 4-week cadence, which may feel too frequent for some customers, while the 3-box 12-week plan has held at zero churn.

Rage clicks and quick backs are the most meaningful signals here: zero of both means visitors are not immediately frustrated or bouncing on arrival. Dead clicks are worth watching. Friction counts on a rolling 3-day window are too small to read as a trend. Upgrade to Clarity Premium for persistent data, scroll depth heatmaps and per-page recommendations.

Read the funnel to find the biggest leak. Add-to-cart is usually the weakest step for cold paid traffic: the lever is getting more visitors to engage with the product page enough to add. Checkout abandonment is the secondary lever once add-to-cart improves.

Not available on this plan. Web vitals (LCP, CLS, FID) measure how fast and stable the page feels, and they affect Google ad quality scores and Meta landing page experience ratings. Run a Lighthouse audit or connect Google Search Console to get LCP, CLS and FID for the product page. Target: LCP under 2.5s, CLS under 0.1, FID under 100ms.

The current Clarity plan gives friction signals (rage clicks, dead clicks, quick backs) and the rolling 3-day session window. Upgrade to Clarity Premium to unlock persistent data, scroll heatmaps, click maps and per-page CVR by device. These are the inputs needed to run systematic PDP conversion tests.

Video engagement metrics (thumbstop rate, thruplay rate) are not returned by the Meta API when ads run as static image formats or when the fields are missing from the pull. Until they populate, the efficiency signal comes from CTR and ROAS on meaningful spend.

"Above BE" means the ad is profitable at current margins (ROAS above break-even). Watch for the largest spenders sitting below break-even: they consume a disproportionate share of budget relative to the revenue they return. To add thumbstop and thruplay rates, add video_play_actions and video_thruplay_watched_actions to the ad-level insights call in /collect-data.

No decay curve drawn yet. Real frequency is not pulled at the ad level. Add frequency to the ad-level breakdown call in /collect-data and this fills with per-ad CTR-vs-frequency curves. No illustrative trend is shown in the meantime.

Ranked by Meta ROAS on spend above $50 (the floor for a meaningful read). The volume leader is shown even when it sits near break-even, since total spend and order count matter for scaling decisions. The angles above break-even are the efficiency winners to scale.

Verdict symbols: checkmark confirmed (actual ≥ expected) · warning partial (within 20%) · x refuted (>20% below) · clock pending. A verdict is called once an ad accumulates 50+ link clicks or 14 days of run time, whichever comes first.

Statistical significance testing compares two variants on the same metric (purchase rate) and asks: is this difference real or just luck? You need at least 50 link clicks per variant to call a test at 95% confidence with a realistic lift of 20-30%. Below that threshold, most comparisons cannot be called yet.

An ad is considered fatiguing when frequency exceeds 3.5 (the same person has seen it 3 to 4 times). At that point CTR and ROAS typically drop 15-25%. The fix is always the same: refresh the creative before frequency peaks, not after.

No days-until-fatigue chart drawn yet. It populates once frequency is pulled per ad, so the timeline is built from each ad's real frequency trajectory rather than an assumed curve.

Scaling depends on finding winners faster than the current ads fatigue. This tracks how many hypotheses entered the pipeline and how many have been called. While hypotheses are still pending and no verdicts have been issued, the system is in the learning phase and the volume to call tests is still building.

The live flows have been firing since the first orders. Recipient counts below are estimated from order and checkout volume, not measured. Actual send counts and performance metrics are not yet pulled from Klaviyo.

What each live flow is designed to do in the customer journey, from first touch to repeat.

Broadcasts are a reach play, not a revenue engine at this scale. Flows carry the owned-channel revenue. Once list sizes are pulled, broadcast potential can be estimated: at 35% open rate and 1.8% CTR (DTC average), each send to 1,000 subscribers generates roughly 3-5 orders. First send should align with whichever ad angle is currently working in paid.

The target ROAS is a blended figure across all channels, not paid alone. At target scale most orders come from email and repeat, so the paid channel buys a minority of new customers while email and organic deliver the rest. The break-even threshold for the paid channel alone is the account break-even ROAS defined in metrics-definitions.md.

The gap to target reflects early scale, not model failure. At target order volume the unit economics produce positive contribution; at low order volume fixed ad costs dominate every unit and produce a loss. The path is scale plus creative efficiency, not a change to the offer.

No scenario projections shown yet. Reliable Jul scenarios need each ad's ROAS to be stable (enough spend per ad to trust the number), which the first weeks of a new account do not yet provide. Rather than present a modelled revenue figure as if it were real, this section stays empty and the formula-driven goal-seek below carries the forward view. Scenarios populate automatically once ad-level ROAS settles.

The goal-seek uses 71.2% gross margin (revenue minus COGS, card fees, and 4% refund floor). Break-even ROAS is 1.56 as defined in metrics-definitions.md. The formula is: Revenue = (Contribution + Spend) / 0.712, ROAS = Revenue / Spend.

No cash forecast drawn yet. It needs four inputs, none of which are connected: (1) opening cash balance, (2) Shopify payout schedule (typically a 2-3 day rolling cycle), (3) inventory reorder PO dates and amounts, (4) monthly fixed cost config. Add these to /collect-data or config and the projected closing-cash-by-week chart populates automatically. No placeholder curve is shown in the meantime.

No data yet. The brand input and output metrics need repeat purchase and multi-month CAC history, which the current data does not provide yet.

No data yet. Brand-spend mix and cohort repurchase charts need history that does not exist yet.

No data yet. The moat scorecard needs verified inputs across the five pillars, not available in this snapshot yet.

No data yet. Cash flow, distribution, supply chain and brand status need verified inputs not wired in yet.

No data yet. The constraint ladder needs marginal ROAS, cash and repeat figures over time, which do not exist yet.

No data yet. The weekly narrative brief is generated by /weekly-brief once enough weeks of reconciled performance data exist. No brief has been produced yet.

No data yet. The generation pipeline is not wired into this dashboard yet, so queue, approval and virality counts are not available.

No data yet. No generations are tracked here yet.

No data yet. No generations are tracked here yet.

No data yet. The brand asset library is not indexed into this dashboard yet.

No data yet. Shopify last-click UTM carries the ad on each order, but per-ad revenue has not been tallied for this snapshot yet.

No data yet. Per-page sessions and CVR need each ad tied to its landing page with session-level analytics, which is not pulled into this snapshot yet.

No data yet. The ad-to-conversion funnel needs per-step session data (impression to click to landing to checkout), which is not pulled into this snapshot yet.

No data yet. This dashboard runs on a manual weekly snapshot, not a live per-source sync log yet.