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Shoptin vs usage-based checkout consent for Shopify

Both approaches solve the same core job: region-aware checkout email and SMS consent vs Shopify's default. The difference is price. Shoptin is flat fee ($400/mo or $333/mo billed $4,000/yr) with unlimited consents vs usage-based per-contact pricing (~$2 per incremental contact).

Side-by-side summary

Usage-based app details below reflect common public positioning in the Shopify App Store category. Shoptin details reflect shoptin.io pricing and product pages.

Capability Shoptin Usage-based apps
Primary focus Email + SMS marketing consent Email + SMS marketing consent
Pricing model Flat fee: $400/mo or $333/mo annual ($4,000/yr) Usage-based (~$2 per incremental contact, per public pricing)
Checkout consent optimization Yes Yes
Region-aware consent Yes Yes
Klaviyo integration Yes — direct sync Yes
A/B test vs Shopify default Yes — built in Yes
SMS at checkout Yes Yes
Install time ~5 minutes, no code Varies by setup
AI / dataset scale Not marketed on shoptin.io AI trained on 45M+ consent events (public claim)

When Shoptin is the better fit

  • You optimize email and SMS subscribers at checkout and sync to Klaviyo and other marketing tools.
  • You want predictable flat pricing instead of per-contact usage fees during peak seasons.
  • You need region-aware consent, A/B testing vs Shopify default, and a 5-minute no-code install.

When usage-based apps may fit better

  • Usage-based pricing aligns with your volume and budget model.
  • AI-driven optimization across a large consent dataset is a priority for your team.
  • You need WhatsApp consent at checkout (some usage-based apps market this; Shoptin does not).

Shoptin merchants see 20% more subscribers on average across all merchants, 40% higher LTV from opt-in subscribers vs non-subscribers, and go live in 5 minutes—metrics published on shoptin.io.

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Measure your missing LTV

Use this prompt with Shopify Sidekick to see how much LTV you're leaking today.

Please retrieve each of the following metrics and summarize in a table: 1. average monthly web orders over the last 12 months 2. first time purchase rate (use this: FROM sales SHOW orders, orders_first_time SINCE -12m UNTIL today) 3. LTV of customers that are NOT SUBSCRIBED to email marketing (filter out customers that have spent more than 1000 since they are b2b) 4. LTV of customers that are SUBSCRIBED to email marketing (filter out customers that have spent more than 1000 since they are b2b) 5. for all orders that were a customer's first purchase in the last 60 days, how many are in each bucket of email subscription status NOT SUBSCRIBED, SUBSCRIBED, UNSUBSCRIBED Using these metrics, tell me roughly how much LTV i am leaving on the table each month via customers that dont subscribed to email marketing (not subscribed).