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Email & retention

Money left on the table (email flow coverage)

Email & SMS scores your Klaviyo account against five canonical money flows and estimates the conservative monthly revenue you're leaving on the table for each one missing.

The five flows

The five canonical money flows, with their published benchmark range as a share of email revenue: Welcome series (3-5%), Abandoned checkout (5-10%), Browse abandonment (no reliable published range, still scored), Post-purchase (2-4%), and Winback / lapsed customers (1-3%).

Reading the card

On Email & SMS (/email), the "Money left on the table" card lists each flow as live or missing. For a missing flow with a published benchmark, Vibel estimates a conservative monthly dollar gap using the low end of that published range against your own measured share of revenue that comes from email (or a conservative default when that can't be measured yet). Every dollar figure is labeled an estimate, never invented without a citable range.

Fixing a gap

Each missing flow comes with a concrete next step, for example: turn on an abandoned checkout flow with 2 to 3 emails starting about an hour after checkout is left behind.

A similar signal for dropshippers

Product testing (/testing) runs the same kind of "is this leaving money on the table" logic on ad spend instead of email, scoring every SKU as SCALE, KEEP or KILL against your real break-even ROAS. See the "Product testing: kill or scale" guide for the how-to.

Good to know

  • Needs Klaviyo connected to score coverage at all.
  • Archived flows in Klaviyo don't count as missing, they're excluded entirely from the score.
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Related terms

Break-Even ROASReturn on Ad Spend (ROAS)Share of Voice (SoV)
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What is VibelConnect your Shopify storeConnect ad platforms (Meta, Google, TikTok)Connect Google (Ads, GA4, Search Console) & ShopifyConnect Klaviyo (email & SMS)Set up your costs for true profit (COGS + operating costs)Install the web tracking pixelYour first sync: what to expectThe Vibel app mapCommand centerThe weekly report (Figures)Cohorts & LTV
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