💎 Unconventional data sources. 3 gems to learn from

Hey there,

Welcome back to another edition of Bootstrapped Growth. 👋

Data is everywhere. The richest insights usually come from unexpected sources. Clever businesses make the most of alternative data to grow in a way that standard tracking and analytics can’t offer.

Table of Contents

• 🚀 Strategy

• ⭐️ Extra Tips

• 🛠️ Resources

Thanks for reading. Let’s jump in!

🚀 3 Examples Of Insights From Unconventional Data Sources

1) Layer External Data Onto Your Core Metrics

Airbnb's pricing optimization is built on analysis of local event calendars, weather patterns, and geo-tagged posts on social media platforms. They discovered that posts about events and weather patterns predicted booking spikes 2-3 weeks in advance. Airbnb increased host revenue by 23% using dynamic pricing recommendations. These were based on correlations of such external signals with booking demand on their platform.

Takeaway ➡️ Mine social media, event calendars, and external APIs for demand prediction signals. Layer social medial sentiment and third-party event data onto key metrics to optimize pricing and inventory.

2) Use Third-Party People Staffing Data As Signals For Business Growth

HubSpot's lead scoring system uses LinkedIn job posting data and company hiring patterns to identify high-intent prospects. Businesses in growth phases tend to post multiple jobs and have active career pages. Using this signal improved the Hubspot sales teams’ close rate by 31%.

Takeaway ➡️ Track hiring patterns, job postings and team expansion signals as leading indicators of customer growth and buying intent.

3) Track Customers’ Third-Party Tool Usage Patterns

Shopify’s analysis of app store download patterns and third-party tool integrations feeds into its merchant success prediction. They found that merchants who install specific combinations of apps (e.g. email marketing, inventory management and analytics) show 4 times higher long-term retention.

Takeaway ➡️ Monitor customers' third-party tool usage and integration patterns. These behaviors predict expansion or churn better than just revenue metrics.

⭐️ Tap into more data source categories

1. Search abandonment analysis. Track what users search for but cannot find. This reveals customer needs and can be used to shape your product roadmap.

2. Mine customer service data. Analyze support tickets for help requests (versus simple bug reports) to influence support content and your product roadmap.

🛠 Useful Resources

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