Unlock the power of AI-driven video automation to supercharge your sales workflow with a scalable, personalized sales assistant built on Tavus.
Technical prerequisites and requirements
Before you start building your AI sales assistant, make sure your technical infrastructure is ready. You'll need access to your CRM—such as Salesforce or HubSpot—with API credentials for seamless data integration. You should also have access to an email and calendar platform like Gmail or Outlook, along with API or OAuth credentials for automated scheduling and communication. A Tavus account with API access is essential; you can sign up and generate API keys through the Tavus Developer Portal.
It's helpful to be familiar with workflow automation tools like Zapier or Make, as these can streamline the integration process. Basic experience with REST APIs and webhooks will help you manage data flows between systems effectively. Additionally, make sure your development and testing environments are secure and isolated to prevent data breaches. Compliance with SOC2 and GDPR is crucial, especially if your solution will handle personal data.
Phase 1: Define use cases and business value
Identify core sales assistant functions
Start by pinpointing which sales tasks you can automate to boost efficiency. AI sales assistants are especially effective in lead generation and enrichment, automatically gathering and updating lead information. They also personalize outreach by sending tailored emails, videos, or chat messages to prospects, which can significantly increase engagement rates.
Meeting and call summarization is another valuable function, capturing key points and action items from sales calls so nothing gets missed. Automated follow-up sequences can be scheduled based on engagement, ensuring timely reminders and follow-ups. On top of that, AI sales assistants can provide sales coaching and training, offering real-time feedback and guidance to your sales reps.
For each function, document the business KPIs you want to impact. Consider metrics like time saved per sales representative, the increase in qualified leads, higher engagement rates on emails and videos, and improved conversion rates and deal velocity. These metrics will help you quantify the business value of your AI sales assistant.
Map AI assistant capabilities to sales workflow
To get the most from your AI sales assistant, align its capabilities with your sales workflow. Break down your sales process into stages—prospecting, nurturing, and closing—and look for automation opportunities at each stage. For example, during prospecting, Tavus can help you create personalized video introductions for new leads, making your outreach more engaging and effective.
In the nurturing phase, you can automate follow-ups and reminders with AI-driven sequencing, ensuring no lead is overlooked. When it’s time to close deals, summarize meetings and send tailored video recaps to reinforce key messages and next steps. For more insights on simulating real-time sales conversations and coaching, check out the Sales Coach persona documentation.
Set success metrics and ROI benchmarks
Establish both technical and business KPIs to measure your AI sales assistant’s impact. Key metrics to track include time saved per sales rep, the number of qualified leads generated, engagement rates for emails and videos, and conversion rates and deal velocity. By setting a baseline for each metric before deployment, you’ll be able to measure improvements once your AI sales assistant is live.
Phase 2: Prepare technical requirements and prerequisites
Assess data sources and integration points
Take a thorough inventory of all platforms your sales team uses. This includes CRM systems like Salesforce and HubSpot, email platforms such as Gmail and Outlook, calendar tools like Google Calendar, and communication tools like Slack and Teams. Make sure you have API access for each platform to enable smooth data integration. Document the authentication requirements, such as OAuth and API keys, for secure access. Identify the specific data fields needed for your AI workflows, including lead name, email, company, and meeting transcripts.
Select AI sales assistant platform and tools
Choose the core components for your AI sales assistant. Tavus serves as your conversational video AI platform, offering predefined personas like the Sales Coach for real-time, video-based sales coaching and conversation simulation. You’ll also want to select NLP libraries for tasks like text analysis, summarization, and lead scoring, and consider third-party APIs for lead enrichment, scheduling, and analytics.
Set up development and testing environments
Set up sandbox environments for your CRM, email, and Tavus API to provide a safe testing ground. Generate Tavus API keys through the Developer Portal, and ensure secure access to production data while keeping test data isolated. Confirm compliance with SOC2 and GDPR requirements to protect personal data.
Always use test accounts and data in your sandbox environment to avoid accidental outreach or data leakage.
Phase 3: Implement core AI sales assistant workflows
Automate lead generation and enrichment
To automate lead generation and enrichment, start by integrating with your lead data sources. Connect your CRM or third-party APIs, such as LinkedIn or Clay, to fetch new leads. For example, you can use a Python script to fetch leads from your CRM:
import requests
crm_api_url = "https://api.yourcrm.com/v1/leads"
headers = {"Authorization": "Bearer <crm_api_token>"}
response = requests.get(crm_api_url, headers=headers)
leads = response.json()Next, enrich and score leads with AI by applying NLP models to extract job titles, detect intent, and score leads. You can use open-source libraries or third-party services for this. For instance, spaCy can help with job title extraction:
import spacy
nlp = spacy.load("en_core_web_sm")
for lead in leads:
doc = nlp(lead["description"])
for ent in doc.ents:
if ent.label_ == "JOB_TITLE":
lead["job_title"] = ent.textAfter enrichment, generate personalized video introductions for each lead using the Tavus API. Here’s the API endpoint:
API endpoint:POST https://tavusapi.com/v2/conversations
Example request:
curl --request POST \
--url https://tavusapi.com/v2/conversations \
--header 'Content-Type: application/json' \
--header 'x-api-key: <api_key>' \
--data '{
"persona_id": "pdced222244b"
}'Replace <api_key> with your Tavus API key. The persona ID for the Sales Coach is pdced222244b. The response will include a conversation_url for the video session. For more on video generation, see the Tavus Video Generation Quick Start.
If you encounter authentication errors, double-check your API key and permissions. Also, make sure your persona ID matches the one provided by Tavus for the Sales Coach.
Deploy conversational outreach and follow-up
To automate personalized outreach, use Tavus to send video messages as part of your email or messaging campaigns. Integrate with your email provider’s API to include Tavus video links in your outreach. For example:
email_body = f"""
Hi {lead['first_name']},
Check out this personalized video: {conversation_url}
Looking forward to connecting!
"""
# Send using your email provider's APISet up sequencing logic by using workflow automation tools like Zapier or Make to trigger follow-ups based on engagement events, such as when a video is watched or an email is opened. For instance, when a lead watches a video, you can trigger a follow-up email or a Slack notification.
Track engagement and trigger next actions by leveraging Tavus webhooks. These webhooks notify you when a video is watched or a conversation is completed. Subscribe to these events and build logic to trigger downstream actions, like updating CRM statuses or scheduling follow-ups. For setup details, refer to the Tavus Webhooks Guide.
To avoid common pitfalls, ensure your webhook endpoint is publicly accessible and can handle POST requests. Always validate webhook payloads for authenticity to prevent spoofing.
Integrate AI-driven meeting and call summaries
Start by capturing meeting recordings and transcripts. Connect to platforms like Zoom or Google Meet via their APIs to access call recordings and transcripts. For Zoom, use the Zoom API to fetch recordings. For Google Meet, use Google Workspace APIs to access meeting data.
Next, generate summaries and action items by applying NLP models to process transcripts, extract key points, and identify next steps. Here’s an example using OpenAI:
import openai
summary = openai.Completion.create(
engine="text-davinci-003",
prompt=f"Summarize the following meeting transcript:\n{transcript}",
max_tokens=150
)Optionally, you can update CRM records with the summary and action items.
Finally, send post-meeting personalized video recaps using the Tavus API. Automate this process with Tavus webhooks and your CRM’s API, and include the summary and next steps in the video script for maximum impact.
If you run into issues, make sure your meeting platform APIs are authorized to access recordings. If transcripts are missing, check your recording settings and permissions.
Phase 4: Connect and orchestrate with existing sales stack
CRM and communication platform integration
Sync AI assistant actions with your CRM by using the CRM’s API to create or update deals and log activities triggered by the AI assistant. For example, when a lead watches a Tavus video, update their engagement score in the CRM.
Integrate with communication tools by connecting to Slack or Teams APIs to send real-time notifications, such as new lead alerts or meeting summaries.
When implementing these integrations, always authenticate API calls and handle rate limits gracefully. Use retry logic for failed requests to avoid losing important updates.
Be mindful not to overload communication channels with too many notifications, as this can cause alert fatigue. Set up rules to filter and prioritize messages.
Workflow automation and orchestration
Automate multi-step workflows by using Zapier or Make to orchestrate actions across different platforms. For example, when a new lead is added in your CRM, you can trigger Tavus video generation and send an email with the video link.
Use Tavus webhooks for real-time triggers by subscribing to Tavus events, such as video generated or conversation completed, to trigger downstream actions in your workflows. For more details, see Tavus Webhooks and Automation.
Security, compliance, and access controls
Implement OAuth or API key management for all integrations. Regularly audit permissions and review data flows to maintain security. Ensure all workflows comply with SOC2 and GDPR requirements.
From a technical standpoint, rotate API keys regularly and monitor for unauthorized access. Set up alerts for any suspicious activity.
Phase 5: Optimize, monitor, and scale
Monitor performance and user adoption
Set up dashboards to track usage metrics, such as the number of videos generated, engagement rates (video watched, email opened), and conversion rates. Use the Tavus Analytics API to monitor video performance and user engagement. For more information, see the Tavus Analytics API.
Iterate on AI models and personalization logic
Continuously retrain your lead scoring and messaging models as you gather more data. Use Tavus analytics to A/B test video scripts, thumbnails, and delivery timing. Collect feedback from sales reps to refine workflows and adjust personalization strategies based on what drives higher engagement.
Scale and extend functionality
Expand your AI assistant by adding new outreach channels, such as SMS, WhatsApp, or LinkedIn, by integrating their APIs. Explore advanced conversational AI, like Tavus AI humans, for live video chat or Q&A. Extend your AI assistant to support additional use cases, including onboarding, renewals, or customer success.
Phase 6: Implementation patterns and best practices
Modular architecture and API-first design
Structure your AI sales assistant as loosely coupled services, such as lead generation, outreach, video, and analytics. Define clear API boundaries for each service to make scaling and maintenance easier.
Human-in-the-loop and manual override
Add approval steps for AI-generated outreach and video content. Give sales reps the ability to review and edit content before it’s sent to prospects, ensuring quality and relevance.
Continuous testing and compliance
Automate integration and workflow testing to catch issues early. Regularly audit data flows and permissions to maintain security and compliance.
Appendix: Tavus integration quick links
- Tavus API Reference
- Video Generation Quick Start
- Webhooks and Automation
- Analytics and Engagement Tracking
- Tavus Support
Start implementing these phases to deploy your AI sales assistant, integrate Tavus’s conversational video AI, and drive measurable improvements in sales engagement and productivity. Experiment with new use cases, monitor your metrics, and iterate to maximize your results.
