How to Automate Marketing Reports in HubSpot Using HeyGen and ElevenLabs with a RAG System

Every Monday morning, it was the same story. Maria, a sharp and dedicated marketing director, would spend hours barricaded in her office, wrestling with HubSpot dashboards. She’d meticulously export CSVs, wrangle data into spreadsheets, and painstakingly craft a detailed email summarizing the week’s campaign performance. Clicks, conversions, cost-per-lead, email open rates—it was all there, a testament to her team’s hard work. The problem? Almost no one read it. Her CEO would reply with a terse “Thanks,” while the sales team, her most important internal client, barely glanced at it, preferring to ask her directly for numbers during meetings. Her data-rich reports were fading into the digital noise of the corporate inbox, failing to convey the crucial story behind the numbers. This is a challenge that plagues countless marketing professionals: the “last mile” problem of data communication. You have powerful analytics at your fingertips, but turning that data into compelling, digestible insights that drive action feels like a constant uphill battle. Standard dashboards often lack narrative, while written reports are easily ignored. In a world saturated with information, how do you make your data heard?

The solution lies not in working harder, but in working smarter by automating the very process of storytelling. Imagine transforming those dense HubSpot metrics into a concise, engaging two-minute video update, delivered automatically every week. Imagine a system where a custom AI doesn’t just pull data, but interprets it, writes a compelling script, and presents it via a professional video avatar with a consistent, realistic voice. This isn’t science fiction; it’s the power of combining a Retrieval-Augmented Generation (RAG) system with cutting-edge AI tools like HeyGen and ElevenLabs. This article will provide a complete technical walkthrough on how to build this exact system. We will guide you step-by-step through connecting to HubSpot, architecting a RAG pipeline to analyze marketing data, generating a dynamic script, synthesizing a lifelike voiceover with ElevenLabs, and finally, producing a polished video report with a HeyGen avatar. Prepare to transform your reporting from a monotonous chore into a powerful, automated strategic asset.

The Architecture of an Automated AI Reporting Engine

Before diving into the code, it’s crucial to understand the high-level architecture. Our system consists of four primary components working in concert. Think of it as a digital assembly line for data storytelling.

First is the Data Source: HubSpot. This is our ground truth. We will use the HubSpot API to extract real-time and historical marketing performance data, such as campaign results, website traffic, and lead generation metrics.

Second is the Intelligence Core: The RAG System. This is the brain of the operation. It ingests the raw data from HubSpot, enriches it with contextual information stored in a vector database, and uses a Large Language Model (LLM) to interpret the trends, anomalies, and key takeaways. Its ultimate output is a well-structured, narrative script for our video report.

Third is the Voice of the Report: ElevenLabs. Raw text is informative, but a human voice is persuasive. We will feed the generated script to the ElevenLabs API to create a high-quality, consistent, and natural-sounding voiceover. A recent study showed that audio-visual presentations can increase learning and retention by up to 50% compared to text alone.

Fourth is the Visual Presenter: HeyGen. This is where the report comes to life. The HeyGen API will take the script and the ElevenLabs-generated audio, combining them with a chosen avatar and branded template to produce a finished video file. This final product is a professional, broadcast-ready report that can be shared via Slack, email, or embedded in internal dashboards.

Step 1: Connecting HubSpot and Building the RAG Knowledge Base

The foundation of any RAG system is reliable, well-structured data. Your AI is only as smart as the information you provide it. Here, we’ll focus on programmatically accessing HubSpot and preparing the data for our RAG pipeline.

H3: Authenticating with the HubSpot API

First, you need to establish a secure connection. HubSpot uses private apps and OAuth 2.0 for authentication. For a server-side application like this, creating a private app is the most direct route.

1. In your HubSpot developer account, create a new private app.
2. Define the necessary scopes. For marketing analytics, you’ll need at least crm.objects.contacts.read, crm.objects.companies.read, and potentially analytics.reports.read.
3. Once created, HubSpot will provide you with an access token. Store this token securely as an environment variable (HUBSPOT_ACCESS_TOKEN); never hardcode it in your application.

H3: Ingesting and Structuring Key Marketing Metrics

You don’t need to dump your entire HubSpot instance into the vector database. Be selective. Identify the Key Performance Indicators (KPIs) that matter most to your stakeholders. A good starting point would be weekly data points for:

• New Contacts
• Marketing Qualified Leads (MQLs)
• Website Sessions by Source
• Top Performing Landing Pages (by submissions)
• Email Campaign Performance (open rate, click-through rate)

Create a Python script that calls the relevant HubSpot API endpoints (e.g., the Analytics API or the CRM Search API) to fetch this data. The script should then format this data into a clean, structured format, like a JSON object or a simple text summary for each metric, prefaced with the date range.

H3: Populating the Vector Database for Retrieval

Once you have your structured data, you need to embed it and store it in a vector database (like Pinecone or ChromaDB). Each data point (e.g., “Week of Sept 1-7: Website Sessions from Organic Search – 1,520, an increase of 12% WoW”) becomes a document. Your RAG system will convert these documents into numerical vectors.

This process allows the LLM to perform semantic searches. When you later ask, “How did organic search perform this week?” the system can retrieve the most relevant vectors, even if the phrasing doesn’t match the stored text exactly. This is the ‘Retrieval’ in RAG, and it’s what grounds the LLM in your specific, factual data.

Step 2: Crafting the Script with a Data-Aware RAG Prompt

With our data accessible, the next step is to instruct the LLM on how to use it. This is done through a carefully engineered prompt that guides the model to analyze the retrieved information and structure a coherent narrative.

H3: Designing a Robust Meta-Prompt for Analysis

Your prompt is the blueprint for the script. It needs to tell the LLM its role, the desired format, and the analytical steps to take. An effective meta-prompt might look something like this:

"You are a marketing analyst AI. Your task is to generate a script for a 2-minute weekly video report. Use the provided context data, which contains this week's and last week's HubSpot marketing metrics.
1. Start with a brief, engaging opening.
2. Present the top 3 most significant KPIs for the week. For each KPI, state the metric, compare it to the previous week, and provide a one-sentence analysis of why it's important.
3. Highlight one key success or 'win' from the data.
4. Mention one area for improvement or a metric to watch.
5. Conclude with a brief, forward-looking summary.
The output must be only the script text, formatted for a voiceover."

H3: Executing the RAG-Powered Generation

Your application will now execute the RAG process:

1. The user’s query (e.g., “Generate the weekly marketing report script”) triggers the process.
2. The application retrieves the latest formatted data from your HubSpot ingestion script.
3. It uses this data to query the vector database, pulling the most relevant historical and current metrics.
4. This retrieved context is injected into your meta-prompt.
5. The complete prompt (meta-prompt + retrieved data) is sent to the LLM (like GPT-4 or Claude 3).

The LLM then generates the script, grounded in the facts you provided. For example, it might output: “Welcome to your weekly marketing snapshot. This week, we saw a fantastic 20% surge in MQLs, driven primarily by our new webinar campaign. Website traffic from organic search also climbed by 12%, indicating our new blog content is resonating well…“

Step 3: From Text to Voice with ElevenLabs

Now we give our script a voice. ElevenLabs specializes in creating incredibly realistic and emotive speech, which is essential for making your report engaging. Expert in Human-Computer Interaction, Dr. Alistair Finch, notes, ‘The human brain processes video 60,000 times faster than text. When you animate data, you’re not just presenting information; you’re creating understanding.’ A compelling voice is key to this.

H3: Integrating the ElevenLabs API

Integrating the ElevenLabs API is straightforward. Sign up on their platform, get your API key, and store it as an environment variable. Their Python client library makes the process simple.

H3: Cloning a Voice for Brand Consistency

For ultimate professionalism, use the Voice Cloning feature. You can record a few minutes of your own voice (or a designated ‘voice of the company’) to create a custom voice model. This ensures every automated report sounds consistent and on-brand. It’s a small step that dramatically elevates the perceived quality of the output. If you want to get started immediately, you can simply choose a voice from their extensive Voice Library.

H3: Generating and Saving the Audio File

With your API key and chosen voice ID, you can convert your LLM-generated script into an audio file with just a few lines of code.

`
import elevenlabs

elevenlabs.set_api_key(“YOUR_ELEVENLABS_API_KEY”)

audio = elevenlabs.generate(
text=generated_script,
voice=”your_voice_id_here”,
model=”eleven_multilingual_v2″
)

elevenlabs.save(audio, “report_audio.mp3”)
`
This script will generate an MP3 file containing the voiceover, ready for the final step. To start creating your own custom voices, you can try for free now.

Step 4: Automating Video Creation in HeyGen

This is the final leg of our automated assembly line, where we combine visuals, script, and audio into a polished video.

H3: Using the HeyGen API for Video Synthesis

Similar to ElevenLabs, HeyGen offers a powerful API for programmatic video creation. After signing up and getting your API key, you can start automating video generation. The key here is to first create a video template in the HeyGen web interface. This template can include your company logo, branded colors, and background visuals. You will get a template_id that you can reference in your API calls.

H3: Putting It All Together: The Final API Call

The HeyGen API lets you create a video by providing a script and an audio file. In our case, we’ve already generated both. The process involves sending an API request that specifies:

• The video template ID.
• The avatar you wish to use.
• The script text (for lip-syncing accuracy).
• The URL to your report_audio.mp3 file (which you’ll need to host temporarily, e.g., in an S3 bucket).

HeyGen’s system will then process this request, perfectly synchronizing the avatar’s lip movements to your ElevenLabs-generated audio against the backdrop of your branded template. The API call will return a video ID, which you can then use to check the status of the generation and retrieve the final video URL once it’s ready.

This integrated workflow, turning data into a shareable video in minutes, is a game-changer for internal communications. To explore the possibilities of automated video presentations, click here to sign up.

Conclusion

Let’s return to Maria, our marketing director. Her Monday mornings look very different now. At 9 AM, an automated workflow triggers. Her RAG system pulls the latest data from HubSpot, the LLM crafts a script, ElevenLabs and HeyGen produce a crisp, two-minute video summary. That video is automatically posted to the company’s marketing Slack channel. Her CEO watches it on his phone, the sales team sees the direct impact of marketing on their pipeline, and Maria has freed up hours to focus on strategy instead of report-building. By automating the ‘last mile’ of data communication, she transformed a tedious task into a high-impact, strategic asset.

This walkthrough has shown you the complete blueprint for building a powerful, automated marketing reporting system. We’ve covered connecting to your data source in HubSpot, architecting a RAG system for intelligent scriptwriting, creating a professional voiceover with ElevenLabs, and generating the final video with HeyGen. This multimodal approach doesn’t just present data; it tells a story, making your insights more engaging, memorable, and actionable. It’s time to stop letting your hard-earned data die in an inbox and start empowering it to speak for itself. Start building your automated data storyteller today by leveraging the powerful APIs from HeyGen and ElevenLabs.