Email Drafting Assistant Build vs Buy

For B2B sales teams, the decision to build a custom AI email drafting assistant or buy an existing solution depends on several factors: internal technical resources, budget, specific customization needs, and data privacy requirements. Most teams will find buying an off-the-shelf product more efficient due to faster deployment and lower maintenance, unless their needs are highly specialized or they possess significant AI development capabilities.

The email drafting assistant market has grown significantly. These tools promise to reduce the time SDRs and AEs spend on email composition, improve message quality, and increase response rates. However, not all solutions are created equal, and the “build vs buy” question is critical.

This article explores the considerations for both approaches, helping you determine the best path for your sales organization. We will look at factors like cost, time, customization, and data security.

Understanding the “Build” Option

Building an email drafting assistant from scratch means your team develops the AI models, integrates them with your existing systems, and maintains the entire infrastructure. This path offers maximum control and customization.

When Building Makes Sense

Building is typically considered when:

• Highly Proprietary Data: Your sales process relies on unique data sets that cannot be shared with third-party vendors. This could include highly sensitive customer information or internal product knowledge that gives you a competitive edge.
• Deep System Integration: You require an assistant that integrates deeply with highly specialized internal tools or legacy systems that off-the-shelf solutions do not support.
• Unique Workflow Requirements: Your sales workflow is so distinct that no existing product can adapt to it. This might involve specific approval processes or content generation rules.
• Strong Internal AI Talent: You have a dedicated team of AI engineers, data scientists, and developers with experience in natural language processing (NLP) and machine learning (ML) model deployment.
• Long-Term Strategic Investment: The email drafting assistant is part of a broader, long-term AI strategy where custom development aligns with core business objectives and future innovation.

Costs and Time of Building

Building is not cheap or fast. The costs extend beyond initial development.

Initial Development:

• Personnel: Salaries for AI engineers, data scientists, software developers, project managers, and QA testers. This can easily run into hundreds of thousands of dollars annually per person.
• Infrastructure: Cloud computing resources, data storage, GPU access for model training.
• Data Acquisition/Preparation: Time and resources to clean, label, and prepare your proprietary sales data for model training.
• Model Training: Significant computational resources and time to train and fine-tune large language models (LLMs) or smaller, specialized models.

Ongoing Maintenance:

• Updates and Patches: Keeping up with new AI research, security vulnerabilities, and platform updates.
• Model Retraining: Periodically retraining models with new data to maintain performance and accuracy.
• Bug Fixes: Addressing issues that arise during use.
• Feature Development: Adding new functionalities as your needs evolve.

Building a custom email drafting assistant is a commitment to ongoing resource allocation, not a one-time project.

A typical build project could take 6-18 months for an initial viable product, with continuous development thereafter. Consider the opportunity cost of diverting your engineering resources from other critical projects.

Understanding the “Buy” Option

Buying an email drafting assistant means subscribing to a vendor’s software-as-a-service (SaaS) solution. This is often the faster and more cost-effective route for many organizations.

When Buying Makes Sense

Buying is generally preferred when:

• Rapid Deployment: You need a solution quickly to address immediate pain points in email composition.
• Limited Internal Resources: Your team lacks the specialized AI engineering talent or bandwidth to build and maintain a custom solution.
• Standard Use Cases: Your email drafting needs align with common sales scenarios, such as prospecting, follow-ups, or meeting scheduling.
• Predictable Costs: You prefer a subscription-based model with clear, recurring costs rather than unpredictable development expenses.
• Vendor Expertise: You want to leverage the vendor’s specialized knowledge, ongoing R&D, and support.

Costs and Time of Buying

Buying typically involves a subscription fee, which can vary based on features, user count, and usage volume.

Initial Costs:

• Subscription Fees: Monthly or annual fees per user or per usage tier.
• Implementation/Setup: Some vendors charge for initial setup, training, or integration services.
• Data Migration (if applicable): Costs associated with migrating existing templates or data.

Ongoing Costs:

• Subscription Renewals: The primary ongoing cost.
• Premium Support: Optional tiers for enhanced support.
• Add-ons/Upgrades: Costs for new features or modules as they become available.

Deployment for a bought solution can range from a few days to a few weeks, depending on the complexity of integration and team training.

Vendor Evaluation for Bought Solutions

When buying, thorough vendor evaluation is crucial. Use an RFP checklist for evaluating AI sales vendors to guide your process.

Key questions to ask potential vendors:

• Data Security and Privacy: How is your data handled? Where is it stored? What compliance certifications do you have (e.g., SOC 2, GDPR, CCPA)?
• Integration Capabilities: Does it integrate with your CRM, sales engagement platforms, and other tools? Look for robust APIs.
• Customization: Can you customize templates, tone, and brand voice? Can it learn from your specific sales collateral?
• Performance Metrics: How do they measure success? What are typical improvements in open rates, reply rates, or time saved?
• Support and Training: What level of support is provided? Is training included?
• Roadmap: What are their plans for future features and improvements?

Hybrid Approaches

Sometimes, a purely build or buy strategy is too rigid. A hybrid approach combines elements of both.

Examples of Hybrid Models

• Buy Core, Build Integrations: Purchase an off-the-shelf email drafting assistant and build custom connectors to your unique internal systems. This is common if your CRM is highly customized.
• Buy Core, Build Customization Layer: Use a vendor’s platform for the core AI capabilities, but build a custom front-end or a layer that applies your specific business rules or data sources before feeding into the vendor’s API.
• Buy Foundation, Build Specialized Modules: Acquire a general-purpose AI writing tool and then build specialized modules on top of it for very niche sales scenarios.

This approach requires a balance of internal development capabilities and a willingness to work within a vendor’s ecosystem.

Key Decision Factors: A Comparison

To help make an informed choice, here is a comparison of key factors:

Impact on Sales Team Productivity

Regardless of whether you build or buy, the goal is to improve sales team productivity. An effective email drafting assistant should:

• Reduce Time Spent: SDRs and AEs spend less time crafting emails from scratch.
• Improve Quality: Emails are more consistent, on-brand, and grammatically correct.
• Increase Effectiveness: Higher open rates, reply rates, and ultimately, more qualified meetings.

Consider how the solution will fit into your existing sales tech stack. For example, will it integrate with your sales engagement platform, or your CRM? A tool that requires your team to jump between multiple systems will negate many of its benefits.

The real ROI of a sales AI tool is measured by its impact on pipeline generation and revenue, not just time saved.

When evaluating potential solutions, consider how they will impact your team’s existing workflows. A solution that requires significant behavioral changes might face adoption challenges. This is similar to evaluating a battlecard generator build vs buy decision, where integration with existing knowledge bases is key.

Data Hygiene and AI Readiness

Before implementing any AI tool, whether built or bought, your data hygiene must be in order. An email drafting assistant relies on quality data to learn and generate effective content. If your CRM data is messy or incomplete, the AI’s output will suffer. This is a critical prerequisite, as discussed in CRM data hygiene: the prerequisite nobody wants to do before AI.

An AI readiness assessment can help identify gaps in your data, processes, and technical infrastructure before you commit to a build or buy decision. This assessment ensures your organization is prepared to maximize the value of an AI tool.

Conclusion

For most B2B sales organizations, buying an email drafting assistant is the more pragmatic choice. It offers faster deployment, lower initial costs, and leverages vendor expertise, allowing your sales team to quickly benefit from AI-powered email generation.

Building a custom solution is a significant undertaking, justified only by highly unique requirements, proprietary data, and robust internal AI capabilities. If you are considering building, ensure you have a clear understanding of the long-term commitment and resources required.

A hybrid approach can offer a middle ground, combining the speed of off-the-shelf solutions with targeted customization. The best decision aligns with your organization’s strategic goals, available resources, and specific operational needs.