Improving Event Follow-ups with AI: A Matillion Case Study

Improving Event Follow-ups with AI: A Matillion Case Study

Companies spend big on marketing. Gartner reports that organizations typically put 6.8% of their revenue into marketing efforts, with 39.1% of that going to marketing programs. A significant chunk of this spend goes to events - trade shows, conferences, and the like. With so much money on the line, getting the most out of these events is critical.

At Matillion, we recently took on the challenge of making our event follow-ups more effective. We used our own data productivity platform to create an AI-powered solution that's giving our sales and marketing teams better results. This blog post walks you through our journey, from the initial idea at Summit to how we're now using this system to get more value from our event investments.

From Idea to Implementation

Imagine being at a busy tech conference, your booth filled with interested attendees, and you're trying to capture meaningful data from each conversation. This was our situation at the recent Summit.

As we scanned badges and wrote notes on our conversations, we had an idea: What if we could use this unstructured, free-text data in an AI pipeline built with our own Matillion platform? Our goal was to categorize booth conversations, generate statistics on attendee interests, and provide our sales team with useful insights.

Creating the AI Pipeline

Within two days of the event, our data engineering team, led by our Chief AI and Data Science Officer, Julian Wiffen, turned this idea into reality. They built a data pipeline that could:

1. Take in unstructured booth scanner data
2. Use AI to categorize conversations
3. Create statistics on customer interests
4. Send insights back to our Salesforce system via reverse ETL

Quick Benefits

We saw positive results quickly. Our Sales Development Representatives (SDRs) received tailored talking points based on the top five conversation topics identified by our AI analysis. This improved our follow-up training sessions and helped create more personalized outreach strategies.

Expanding the Idea: AI-Generated Company Insights

We then took this a step further. Julian suggested using our AI pipeline to search Google for the latest news and information about our potential customers. This extra layer of AI-generated insights allowed us to create even more relevant and timely follow-ups.

Personalized Follow-up Emails

By combining the event interaction data with these AI-generated company insights, we created highly personalized follow-up emails. These emails mentioned the specific conversations from our booth and included relevant insights about the recipient's company in the context of building data pipelines with Matillion.

The Importance of Human Oversight

While AI played a key role in this process, human oversight was crucial. Our product marketing team carefully reviewed the AI-categorized topics, adjusting the prompts in the AI pipeline as needed. Before sending any emails, we conducted a thorough quality check to ensure accuracy and relevance.

This "human in the loop" approach is vital. We don't want AI to operate unchecked – instead, we use its capabilities while maintaining control and ensuring quality.

Implementing This Approach in Your Organization

To implement a similar approach in your organization, consider these key steps:

1. Identify your data sources (e.g., booth scanner data, CRM information)
2. Set up an AI pipeline to process and analyze this data
3. Integrate the insights with your existing systems (like Salesforce)
4. Create templates for personalized follow-ups
5. Establish a review process to ensure quality and relevance

The benefits can be seen across multiple teams:

• Sales teams get data-driven talking points
• Marketing teams can create more targeted campaigns
• Customer success teams gain deeper insights into client interests

While we've focused on event follow-ups, this approach can be adapted for various industries and use cases. The key is to start with a clear objective and use AI to enhance, not replace, your human expertise.

Conclusion

By using AI through our own Matillion platform, we've improved our event follow-up process. We're now able to offer more value to our prospects, provide our sales team with better insights, and ultimately have more meaningful conversations.

We encourage you to explore how AI-powered data productivity can improve your organization's approach to customer engagement. To learn more about Matillion's AI capabilities and how they can benefit your business, visit our website or contact our team.

To see more AI use cases, check out more AI fundamental videos here