Business Challenges:
A Company having Ecommerce operations in USA was facing severe challenges by using trivial CRM
Campaigns using Salesforce and other Thrid party tools.
Ecommerce company has slew of challenges around managing the Customer churns, focusing on features
that could engage customers and increase the Customer LTV.
After trying several adhoc campaign management tools, Ecommerce client adapted Ezapp Solution AI
Campaign Management to improve the App downloads and mazimize the Business Revenue.
Solution:
Ezapp provided the AI forecasting of sales growth and optimization of the Ads revenue by predicting
the Leads sales. Client
was able to increase subscriptions and App downloads.
Ezapp built the AI Campaign Management that allowed the Client to optimize their spending on the
omni channel and maximize revenue
on Marketing dollars spending. Client manage several campaigns across Google PPC, Facebook, Ads
Publishing Network. AI Platform performed allocation
of budget across various channels to optimize the app downloads, increase sales revenue, decrease
the churn outs. Deep Learning models allows Client
to find the relevant product faster from the chat window.
Machine Learning models leverage past purchase behavior of existing customers to provide
personalized recommendations for
each visitor.
Results :
-
2 Out of 10 Products Recommended by Recommender System are purchased by the visitor. This increased
the revenue by 45% and
overall monthly revenue by 25%
-
Optimize the Ads Revenue Spent by Best Channels to increase the Revenue Sales leveraging
Re-Inforcement Learning models.
-
Optimized the Allocation of Dollar spent by leveraging Markov Chaining Model.
-
Reduced Customer Churn outs by leveraging the Random Forest model.
-
Increase the App downloads by leveraging the Logistic Regression Classifier and identified the
Coefficients that were related to Response variable.
- Delivered the Customer Engagement Model and Customer Life Time Value (LTV) by leveraging the
Linear Regression Model and provided the Predictions for the
3-month Sales Predictions for the Sales Channel.