Revolutionary Strategies for Customer Journey and Data Collection in Marketing

– Creation of a video library for a SaaS company led to more productive calls, targeted demos, and higher close rates.
– Implementation of a clean data strategy for customer support resulted in an 80% reduction in ticket volume and provided valuable insights for product teams.
– Data collection during sign-ups allowed for personalized marketing campaigns, forecasting, and website updates to improve customer journeys.Implement a comprehensive data collection strategy to improve marketing campaigns, customer support, and product development.Amazing things started happening when I stopped guessing. My ideas were radical at the time and usually ahead of their time. There were three monumental shifts that defined my outlook on what a customer journey could be.

1. Video Library for a SaaS company.
Problem: We sold to small businesses, and they were often too busy to schedule a demo or have time to spare during work hours.
Solution: I asked people how they learned, talked about it, saw it, or used it. This led to the creation of an exhaustive video library with fully detailed demos of the different parts of the product and how to use them.
Results: More productive calls and targeted demos, higher close rates.
Bonuses: Knew which videos were most popular, was able to have real conversations about business use cases from the first calls.
Trend: This was in 2014, we’re only now getting to the trend of not gating content, but it still has a ways to go.

2. Implemented a clean data strategy for self-help in customer support internally, then for other companies.
Problem: Support docs for tech products look like API docs. For consumers, it’s easy to get lost and frustrated, which leads to tickets that come in with “It doesn’t work” or “Your shit sucks!”
Solution: Map the existing docs of common issues to a form to collect clean data while categorizing and providing overall insights. This allowed for custom responses upon submission, categorization, and data-led product Q&A and R&D.
Results: 80% reduction in ticket volume, data to share with product teams to close the loop on issues and future hurdles.
Trends: This was in 2017, most brands still don’t do this, and most support tickets aren’t categorized. Most support docs don’t allow for quick step-by-step forms – I see this as the only way forward for a lot of platforms. Still waiting for people to catch on.

3. Data collection during sign-ups to design marketing strategies.
Problem: We didn’t know why people were subscribing or why those subscribing were purchasing, or why those that subscribed didn’t purchase.
Solution: Just ask during a point of intention, then map those attributes to sales to determine what matters most for people and what matters most for revenue.
Results: Email campaigns that speak directly to why people are interested in products, ad campaigns that highlight the features that are top revenue drivers and allow for custom retargeting, forecasting based on data combinations, and

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