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  6. 109. Sales Talk Generation AI Design

109. Sales Talk Generation AI Design

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last updated:Feb 12, 2026

アンドワン 本社、東京支社、川崎営業所
アンドワン 本社、東京支社、川崎営業所
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Sales wins not through "phrasing" but through "order." We generate talks tailored to the product, industry, and situation using AI, standardizing the quality of proposals.

The reasons for losing B2B sales are often not due to price or product, but rather due to "insufficient design of communication." Proposals that do not match the client's situation, lack of comparative criteria, weak handling of objections, and ambiguity in next actions can accumulate, causing negotiations to stall at "under consideration." On the other hand, top salespeople adjust the "order of conversation," "ways of comparison," and "assertiveness" according to the situation, even with the same product. In this service, we will design a system that generates sales talks (hearing questions, proposal outlines, comparative explanations, objection handling, closing) using AI, tailored to the product, application, target roles (purchasing/design/field/management), and consideration phases. This is not just about generating text; we will establish a "winning pattern" that can be replicated by anyone. ■ Offered Content (3 Points) 1. Design of winning talk patterns (frameworks by phase and role) 2. AI generation design (input items, output format, rationale/restrictions) 3. Operational design (improvement through field feedback, log auditing) *First, please tell us about your "main products" and "common reasons for losing sales (points where you lose in comparisons)." We will translate this into a talk pattern.

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109. Sales Talk Generation AI Design

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  • Related Link - https://andoneweb.co.jp/
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basic information

■Concerns like these - The quality of sales proposals varies by representative - Technical explanations are lengthy and fail to convey value - Explanations are weak in competitive comparisons, leading to price competition - Unable to take the next action in the initial business meeting - Top sales techniques are becoming personalized ■Provided Content (Details) - 1) Design of sales talk "templates" (a template is needed before generation) - 2) Input design for AI generation (granularity that can be input by the field) - 3) Output format (fixed in a usable form) - 4) Guardrails (preventing accidents with generative AI) - 5) Operations (improving based on wins and losses in the field) ■Deliverables - Sales talk templates (phase-specific × role-specific templates) - Generative AI specifications (input items, output formats, prohibitions, rationale presentation) - Comparison axis templates (measuring stick to win in competitive comparisons) - Objection handling collection (price, delivery, compatibility, quality, track record) - Closing collection (how to take the next action) - Operational rules (reviews, logs, improvement cycles) - KPI design (conversion rate, next appointment rate, estimate submission rate, contract rate)

Price information

■3 million to 18 million yen (varies based on scope, collaboration, and operation) - Light (type design + basic generation specifications + template collection): 3 to 6 million yen - Standard (role/phase branching, objection handling, operational design, verification): 6 to 11 million yen - Extended (CRM integration, log learning operation, automatic document/email generation): 11 to 18 million yen *Estimate required

Delivery Time

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※Shortest 4 to 6 weeks / Standard 2 to 3 months

Applications/Examples of results

■Purpose - Standardization of sales talks (elimination of individual dependence) - Improvement of win rates through competitive comparisons (presentation of comparison axes) - Strengthening of objection handling (avoidance of price competition) - Acquisition of next actions (improvement of appointment and estimate submission rates) - Acceleration of new employee training (reproducible models) ■Examples of Achievements - Many price objections → Improved win rates by organizing comparison axes and responses - Long technical explanations → Promoted understanding with a 30-second summary and structured order - Initial meetings stagnate → Improved next action rates with a closing approach ■Approach 1. Current situation analysis: Sales logs, reasons for lost deals, interviews with top salespeople 2. Model design: Create winning templates by phase and role 3. Generation design: Confirm input → output → usage scenarios 4. Testing: Generate talks in real sales cases and validate on-site 5. Operation: Tag successes/failures for monthly improvements 6. Deployment: Expand to new employee training, standard materials, and email templates

catalog(20)

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1. Introduction of FAQ × AI Chat

1. Introduction of FAQ × AI Chat

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2. Introduction of AI chat linked to the product database

2. Introduction of AI chat linked to the product database

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3. Introduction of AI for Pre-Estimate Hearing

3. Introduction of AI for Pre-Estimate Hearing

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4. Introduction of multilingual AI chat.

4. Introduction of multilingual AI chat.

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5. Construction of a Technical Data Search AI Portal

5. Construction of a Technical Data Search AI Portal

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6. Veteran Inheritance System

6. Veteran Inheritance System

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7. Building an In-house Knowledge AI (RAG)

7. Building an In-house Knowledge AI (RAG)

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8. Inquiry Automatic Classification AI Design

8. Inquiry Automatic Classification AI Design

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9. Lead Evaluation AI (Temperature Estimation) Design

9. Lead Evaluation AI (Temperature Estimation) Design

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10. Sales Talk Generation AI Design

10. Sales Talk Generation AI Design

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11. Proposal Draft Generation AI Design

11. Proposal Draft Generation AI Design

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12. Specification Summary AI (Internal) Design

12. Specification Summary AI (Internal) Design

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13. Drawing/Image Description AI (Assistance) Design

13. Drawing/Image Description AI (Assistance) Design

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14. AI-Compatible FAQ Structured Design

14. AI-Compatible FAQ Structured Design

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15. AI Response Guardrail Design

15. AI Response Guardrail Design

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16. AI Chat Log Analysis Design

16. AI Chat Log Analysis Design

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17. Establishing rules for AI content creation

17. Establishing rules for AI content creation

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18. AI Implementation PoC Design (Web)

18. AI Implementation PoC Design (Web)

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19. AI × Inquiry Flow Design

19. AI × Inquiry Flow Design

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21. Formulation of AI Utilization Policy

21. Formulation of AI Utilization Policy

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アンドワン

アンドワン 本社、東京支社、川崎営業所

IT/Telecommunications

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A site that is just cheap ultimately increases costs and risks." We propose web development that maximizes business results while thoroughly addressing essential requirements. Are you creating a website like this? - It seems that the websites of competitors look better, but you don't know why. - Every update incurs additional costs, and before you know it, expenses have ballooned beyond expectations. - While the appearance is nice, it ignores laws and industry-specific rules, leading to complaint risks... - You want to attract customers and inquiries, but the production company only talks about design. - As a result of choosing a production that is simply cheap, you are overwhelmed with trouble handling and can't focus on your core business. Point 1. Avoid troubles with a design that has no "gaps or omissions." 2. Minimize operational costs with a design that assumes in-house updates. 3. Planning power that pursues business results. "Is the initial cost a bit high?" But in the long run, it's safe and cost-effective. We have prepared a plan to truly deliver results "correctly.

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