Automating customer onboarding with Numbers Station
A media consulting firm was having challenges onboarding new customers as their business started to grow. The data team used Numbers Station to automate customer data onboarding processes. For every new customer, data analysts at the media company were able to clean and map the data to their internal schema 20x faster compared to their previous manual approach.
A media consulting firm providing services for marketing and advertising strategy was having issues onboarding new customers as their business grew rapidly. The challenge they were facing was caused by inconsistent data schemas from different customers, requiring their data team to build bespoke pipelines to map customers' data schemas to their internal schema. Their approach was not scaling fast enough and also prone to errors and data quality issues. They were looking for an automated solution to onboard their customers faster and create trust with their customers by delivering high quality data.
Accelerate customer onboarding by automating data wrangling workloads and build customer trust with better data quality.
The data from new customers required a significant amount of manual work and customization. This is because customers’ marketing data came from a variety of systems like ad platforms, web analytics tools, and more. This data often had inconsistent schemas, and contained errors or missing values. This required writing custom regex and rule-based logic to clean and normalize the data for each new customer. Ultimately, this manual solution was prone to errors and not scalable as the volume of customers to onboard started to grow.
Using Numbers Station’s Data Transformation Assistant, the data team was able to automatically generate cleaning logic from natural language instructions, and use AI for more advanced transformations like categorizing campaigns based on their descriptions. Using Numbers Station’s dbt integration, the data team then deployed all customer onboarding pipelines in their warehouse with automatic monthly updates for all their customers.
The data team was able to drastically reduce the time they spent onboarding new customers, from 2 weeks of work to four hours per customer on average. This allowed the media company to acquire more customers faster, and spend time on providing strategic insights rather than writing complex cleaning and normalization logic.
More marketing analytics use cases
Use AI to categorize campaign metadata (e.g. name, description). Build accurate customer engagement reports to understand which strategies work best with your customers.
Enrich your internal marketing data with third party data (e.g. demographics, firmographics, etc) to get a complete understanding of your prospects and their preferences.
Understand how the community reacts to your social media media campaigns by analyzing common topics, trends and sentiments in social media data (e.g. tweets).