Solve problems quickly with pre-built flows

Below are a few ways in which we've seen companies be successful.
With end-to-end data tooling, use cases are endless.

How sales teams convert more leads

SaaS
Optimization
Marketing
CRM
Enrich
  • Import data from your CRM and build conversion pipeline analytics
  • Enrich sales lead data with APIs like Clearbit and Apollo
  • Build a data model to predict Customer LTV
  • Setup an automation intended to increase conversion rates by offering a discount to high LTV customers via an automated email marketing campaign
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1
Import
2
Chart
3
Automate

How revenue teams reduce passive churn

SaaS
Optimization
RevOps
Billing
Churn
  • Import data subscription billing provider such as Stripe, Braintree, Chargebee
  • Set up smart retries for failed payments, alert customers through professional emails that their credit card is failing
  • Send opt-in emails asking your customer to update their credit card information
  • Fetch updated credit card information directly from Visa and Mastercard for expired cards and update payment
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How risk teams manage fraud

Risk
Prediction
Fraud
Payments
  • Integrate your payments stack and filter for users making large transactions
  • Verify their business with MidDesk, enrich their user profile
  • Predict a risk score using MidDesk and historical payments data
  • Process predictions into 3 categories - auto-decline, manual review, and auto-clear and send matching email.
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1
Collect
2
Score
3
Alert
1
Model
2
Forecast
3
Automate retention campaigns

How market teams manage competitor pricing

Marketplaces
Web Scraping
Automation
Pricing
  • Design a web scraping bot using webscraper.io or equivalent
  • Import and store web scraping results via webhook
  • Build data models to normalize scraping results and store for comparison
  • Build statistical alerts to notify via email when a segment of competitor product has deviated from the norm
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How product teams retain users

Event Tracking
Churn
Retention
CRM
  • Integrate your event tracking software such as Google Analytics, Segment, Snowplow, PostHog
  • Chart product analytics and build product activity metrics to understand usage
  • Build a churn prediction model to run weekly and identify churn before it happens
  • Automate discounts, CSAT¬†surveys, or manual outreach to understand why user activity or behavior changed
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1
Convert
2
Engage
3
Retain
4
Predict

Want to pilot?

We're looking to explore these use cases and others with companies solving interesting problems.
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