More leads
More qualified traffic and prospecting: more people enter for the same investment.
E-commerce treats sales as if it were just checkout and ignores the commercial side: 70% of carts are abandoned and almost no one recovers them, the pre-sales WhatsApp goes unanswered and high-ticket sales disappear, and the client who bought once is never provoked to repurchase. It's a leaking bucket: you fill it with paid traffic and sales leak at three points at the same time.
Typical e-commerce numbers. Adjust with yours.
Everything starts from your real revenue per client, the LTV. Four numbers you already have:
A structured sales engine moves three levers at the same time. Since they act on the same account, the effect does not add up: it multiplies.
More qualified traffic and prospecting: more people enter for the same investment.
Response in minutes, follow-up that doesn't fail, and AI answering after hours.
Relationship and base reactivation: the same client buying again.
The size of each step depends on where you are starting from: those who already use a good CRM with AI have less to gain (20% per lever) than those who don't use any CRM yet (30%). That is why the calculator asks for your current situation, and it is the only place where an estimate is entered.
In the MMV Method, e-commerce gains a commercial layer on top of the store: abandoned cart, pre-sales questions, and repurchase become structured funnels in Kommo, not lost events. The store stops depending only on automatic checkout and starts recovering sales with service and follow-up. You measure LTV and repurchase rate, not just monthly revenue.
Abandoned cart, high-ticket pre-sales, and after-sales/repurchase funnels, with each client tagged by product purchased and return potential.
Connects the platform (Shopify, Nuvemshop, WooCommerce) to Kommo, triggers cart recovery via WhatsApp/email, and creates the repurchase funnel at the right moment of the product cycle.
AI agent responds to product, shipping, and payment questions 24/7 on WhatsApp, recovers those who abandoned the cart, and closes the consultative sale that checkout alone would lose.
Builds the platform integration with Kommo, recovery and repurchase automations, and LTV and recurrence reports that the store didn't have.
Reactivation of the inactive client base and repurchase campaigns by consumption window (those who bought X days ago are due to buy again), selling to those who already trust is the cheapest.
Product content and ads leading, besides checkout, to WhatsApp service for questions and high-ticket, capturing the sale that the cold cart would let escape.
Tracks product of interest, objection (price, shipping, deadline), and stage (abandoned cart vs. comparing), to prioritize those close to buying.
AI responds in seconds to pre-sales questions and recovers the cart before it cools down; for high-ticket, consultative service closes what checkout wouldn't. Structured repurchase follow-up reactivates the client in the right window and transforms one-time purchase into recurrence, raising LTV without new acquisition cost.
Captures bottom-of-funnel searches ("[product] worth it", "[product] price", "best [category] for [use]") with comparison and product review pages, and answers purchase questions in direct format to be cited by ChatGPT and AI Overviews when the consumer decides what to buy.
Frequently Asked Questions, E-commerce
N8N detects abandonment and Kommo triggers a short and useful sequence, reminder, response to probable objection (shipping, deadline), and, if necessary, human or AI service via WhatsApp. It's not bombardment: it's structured cadence that recovers a good part of 70% of lost carts, with the right message at the right time.
The platform takes care of checkout; it doesn't sell. CRM adds the missing commercial layer: recovers cart, serves high-ticket pre-sales, and triggers repurchase in the right window. It's the difference between billing only with those who buy alone and capturing the three sales that leak today, abandonment, questions, and recurrence, raising the LTV of each client.