Retail Starter Kit

As a retailer, understanding your customers is key to increasing sales. In this Starter Kit, get everything you need to start gaining greater insights into your customers’ behavior with several models, such as marketing response analysis, customer segmentation, sentiment analysis, and customer lifetime value. The starter kit also includes spatial analytics to visualize new store location impact as well as a model for predicting customer behaviors.

Starter Kit Features

Ad Area Distribution

Build a quick model that allows you to ensure that a company’s advertising strategy targets the optimal locations for distribution in relation to retail location by combining multiple spatial data sources.


Hull Trade Area Creation

Build a catchment or trade area based on distance or drive time by using geocoding with our Trade Area Tool.


Customer Acquisition

Understanding which channel customers use to make a buying decision can be complex. With this Starter Kit, you can blend various data from e-commerce sales data to in-store sales data, add product detail to analyze historical sales data, and understand which channel contributes the most to customer acquisition.


Customer Response Modeling

Match customer geographic and demographic data to understand your customers’ behavior. Use our Logistic Regression Tool to learn customer behavior, then score the model and predict which customers are most likely to respond to a promotion based on drive time.


Customer Sentiment

Prep, parse, and analyze survey data and output the data to tableau to visualize customer sentiment.


Lifetime Value

Build and calculate customer lifetime value for your customer base. Use sales data to predict customers that are more likely to have a lifetime value in the top 5% compared to their cohort. Finally, send the data to tableau to visualize and explore.


New Location Impact

Blend customer value data, customer location, and new store location data to analyze how each customer is more likely to respond to a targeted campaign or a new competitor. In addition, this model allows the output to create a user-friendly application that allows users to dynamically place location points on a map to see how a change in location may affect customer response.


“As a company we have moved from being intuitive to being analytical.”  

— Simon Uwins, CMO, Tesco

Our Customers

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Our Partners

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