Streamline the feature engineering process and improve predictive model quality
Make feature engineering more efficient and effective with predefined features and data.
Pressured to perform, many organizations turn to data science and machine learning to understand and predict consumer behavior. But predictive modeling success ultimately hinges on selecting features that are most likely to affect the desired outcome – a time-consuming and error-prone process.
Mobilewalla offers an innovative alternative: a "Feature Mart" with more than 200 sophisticated, highly predictive features that can be used to model a variety of outcomes. These features are predefined across nine key categories and can be applied across industries and use cases. Mobilewalla also provides the data behind the features to train and validate models, and the data science services to augment your internal teams and improve your outcomes.
Effective Feature Engineering
Feature engineering is a manual, resource-intensive process that requires ample data, careful analysis, expert judgment, and some degree of luck. This complexity creates ample room for error.
Mobilewalla helps data scientists streamline the feature discovery process and improve predictive modeling results at two levels:
Data enrichment – The addition of high-quality third-party data to an internal database. We fill in consumer intelligence gaps to create a richer picture of customer characteristics and empower more precise feature selection.
Feature discovery and selection–Mobilewalla's library of predefined features effectively allows data scientists to outsource aspects of feature discovery and selection.
Tech Brief: Streamline Feature Engineering for Better Predictive Modeling Results
This tech brief for data scientists explores the underlying challenges of feature selection and explains how to overcome them through data enrichment and pre-defined features.
Average daily distance
Most seen location
Mobile app usage
Paid app usage
Types of apps used
Affinity for types of apps
Average household phone price
Average household phone age
Social relationship size
Work relationship size
Social phone price
Level of device usage
Time of device usage
With Mobilewalla features you can:
Increase the breadth, depth, and scale of your training data
Reduce human judgment and error while still allowing for expert refinement for feature discovery and selection
Decrease time and resources spent on exploratory data analysis
Improve the predictiveness of machine learning models
More Mobilewalla Offerings
Use third-party data to understand your customers – and your competitors' customers – more deeply.