Customer Experience Use Cases

Customer Segmentation

Customer-Lifecycle Prediction

Global fashion company: This company wanted to improve the effectiveness of its annual marketing plan and its execution.  It did not have tools to precisely predict customer behavior, and data problems prevented decision-makers from developing a strategy to introduce personalization features in its customer experience.

Using an advanced analytics approach, we developed a customer-lifecycle value microapp that was able to provide accurate predictions of when each customer was likely to make his/her next purchase and how many purchases a given customer would make in a specified sales period. With such a high prediction accuracy, decision makers were able to create optimized sales strategies to increase revenue.

Results: 99% average prediction accuracy achieved

E-Mail Marketing and

Cross-Sell Optimization

Global fashion company: This fashion company needed to improve its online sales but was struggling to launch a productive and targeted email campaign to communicate with customers most likely to purchase and to suggest  additional items that each had a high likelihood of purchasing.  Decision-makers did not have an understanding of the relevant commercial and sales performance drivers that were affecting their conversion rates and online sales.

A2Go developed an advanced analytic application to optimize customer-sales recommendations and extract insights from customer browsing history.  The accuracy of the predicted customer behaviors was enhanced by using external datasets relevant to commercial trends __thus providing context to customer behavior and greatly improving conversion rates.

Results: 8.4% higher conversion rate with the targeted email campaign and 15.4% increase in revenue

Customer Segmentation and Demand Forecasting

US-based B2B Rental Business: This business was struggling with unpredictable customer rental cycles, return-date variability, and "available-to-rent" quantity per site. 

Data analytics were used to classify customers into segments  based on pricing preferences and rental patterns.  It was then possible for the decision-makers to forecast sales and services and establish sales and services priorities aligned with the goal of optimizing revenue.

Result: 5% higher revenue from the same inventory

Optimization of Cross-Sell

Global Fashion Retailer: This company was dissatisfied with the revenue results of its current e-commerce platform’s recommendations for new customer purchases. Complex parameters such as discounts and low inventory on some products had to be factored into the computations and analysis.

A2Go developed a microapp that delivered optimized predictions and prescriptive actions for decision-makers in three weeks’ time. This speed was possible because the company had all of the relevant data at hand that was necessary in the analysis. When we piloted the solution in tandem with the company’s current platform solution, the results were impressive.

15% improvement in revenue