Monthly assisted conversations
Count pre-purchase threads, not website sessions.
Estimate the monthly value of automating pre-purchase conversations. Enter assisted volume, automation level, reply time, team cost, conversion rate, expected lift, and average order value.
Unlike traffic-based calculators, it starts with actual shopping conversations. It does not connect to your accounts, and results are planning estimates rather than guaranteed sales or audited ROI.
An assisted conversation supports a purchase decision: product differences, size, fit, compatibility, materials, availability, delivery, or option selection.
Count threads, not messages. Include relevant website chat, Instagram, and WhatsApp conversations, but remove cross-platform duplicates.
Exclude unanswered outbound messages, post-purchase complaints, unrelated support, and conversations without shopping assistance.
Count pre-purchase threads, not website sessions.
Estimate the percentage completed to the intended outcome.
Include understanding, product research, and response time.
Use loaded employee cost, outsourced rate, or owner-time value.
Enter the percentage of assisted conversations producing an order.
Estimate the relative improvement from better assistance.
Enter revenue per completed assisted order.
Use a 30-to-90-day average so exceptional campaigns do not distort the result.
Monthly assisted conversations × AI automation level
Automated conversations × Minutes per manual reply ÷ 60
Hours saved × Team cost per hour
Automated conversations × Assisted conversion rate × Expected lift × Average order value
Team cost saved + Revenue influenced
Conversion lift is relative. A 3% assisted conversion rate with a 10% lift produces an incremental rate of 0.3 percentage points—not a new rate of 13%.
Consider 1,200 assisted conversations, 70% automation, four minutes per reply, $25 hourly team cost, a 3% conversion rate, 10% relative lift, and $80 AOV.
Automated assisted conversations
Manual time saved
Team cost value
Modeled revenue influenced
Monthly opportunity
The $1,400 may represent capacity rather than reduced payroll. The $201.60 is modeled incremental revenue. Neither is confirmed profit.
Site-wide conversion includes visitors who never use the assistant. Assisted shoppers asked a question or requested guidance and may already have stronger intent.
Measure comparable assisted conversations that produce an order and keep the definition consistent. Higher conversion among chat users does not prove the assistant caused it; controlled tests provide stronger evidence.
Manual reply time, its team cost, and revenue influenced by the conversion-lift assumption.
AOV uplift, upsells, cross-sells, returns, software fees, implementation, maintenance, human takeover, and product-data management.
The calculator cannot know which orders would have occurred without assistance. Model AOV changes in a separate scenario instead of double-counting.
Orders completed after a shopping-assistant interaction.
Revenue counted under the attribution window and rules chosen by the business.
Additional revenue that probably would not have occurred without the assistant.
Revenue influenced is an incremental scenario based on your lift—not all assisted revenue.
Lower automation, assisted conversion, lift, and AOV.
Your most likely workflow and historical performance.
A stronger result that remains operationally possible.
Prefer your history or pilot results over vendor claims. If a small adjustment reverses the conclusion, test that assumption before expanding.
The calculator does not include platform or operating costs. Subtract the complete cost of the solution before calculating net value.
Estimated monthly opportunity − Platform, implementation, and operating costs
Net value ÷ Total shopping assistant investment × 100
Do not count released time, reduced payroll, and new work value separately when they overlap. Review Dealism pricing.
Record a baseline, then track assisted and AI-completed conversations, recommendation clicks, carts, checkouts, purchases, AOV, escalations, returns, and costs.
Use one attribution window. For stronger evidence, use an A/B test or holdout group and monitor recommendation quality and escalation.
Customer conversation automation can handle predictable steps. An AI Customer Agent can clarify needs, answer product questions, and guide shoppers toward an option or human teammate.
Start with one high-volume, low-risk shopping question, define success and human takeover, and expand only after replacing assumptions with measured results.
Yes. Run multiple scenarios without connecting an ecommerce store or customer account.
No. Use the conversion rate for comparable assisted shopping conversations whenever available.
No separate AOV lift is applied. Run another scenario with an adjusted order value to test that assumption.
No. Incremental revenue is only the amount that probably would not have occurred without assistance.
Yes. Include shopping-related conversations, use one counting rule, and remove duplicates across channels.
Replace assumptions with measured results, subtract all platform and operating costs, and compare net value with total investment over the same period.
Dealism replies the second they message, sounds completely human, and quietly closes deals in the background.
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