Applied AI
Make better decisions, enhance collaboration, and improve customer experience.
Applied AI
Make better decisions, enhance collaboration, and improve customer experience.
Businesses across the globe are seeking to use AI as well as machine learning in order to create business value. However, the process of executing an AI or machine learning-related project requires a lot of knowledge and experience of data sciences, engineering, and the machine-learning operations — abilities that only a few companies have internally. Stilbon specializes in helping to automate and innovate using the most reliable cloud frameworks to accelerate your projects. With extensive knowledge from Data Engineering to Data Science, you’ll be able to gain an incredible amount of insight through your database. From self-learning chatbots to smart cameras, from product demand planning, to threat detection, Rackspace Technology offers a array of AI solutions that can allow your data to provide automated recommendations, take preventive actions, improve decision-making and more.
Use Cases:
Some key use cases of Applied AI Solutions for Google Cloud
Unified customer view across all platforms
Omnichannel SMS/Email/push Campaigns
Audience Creation for Remarketing
Content Recommendation Engine
Sentiment Analysis
Creative Analysis
Customer Data Platform
Lead Scoring
Offers/Vouchers Optimization - AI/ML
Predictive Modelling for Leads
Customer Lifetime value
Predict Optimal Marketing Attribution
Content performance
Case Study
Problem Statement
Many businesses struggle with customer churn and retention. They may not understand the reasons for customer dissatisfaction, and as a result, make arbitrary product decisions without fully understanding the impact on their customer base. Additionally, it can be challenging to identify the specific features or configurations that are helping customers effectively use the product and stick around.
Solution
At Stilbon, we leverage the power of Google Cloud to help our clients understand, quantify, predict, and reduce churn by taking a journey-based approach to identifying reasons for customer dissatisfaction. We use Google Cloud’s scalable data warehouse and data ingestion tools, including Google Cloud Storage and BigQuery, to ingest data from multiple sources, including CosmosDB and Kusto logs.
Using advanced machine learning and data analytics techniques, we analyze this data to identify key influencers, top segments, and monthly trends for churn and retention. For example, we were able to increase customer retention by approximately 5% for one of our clients using our predictive modeling techniques.
We also use Google Cloud’s advanced visualization tools, including Looker and Data Studio, to provide our clients with actionable insights into their customer and product usage behavior. For instance, we developed customized dashboards and reports that helped one of our clients identify specific customer churn patterns and retention customer patterns.
Outcome
By working with Stilbon, our clients can expect to see several benefits, including:
- Increased customer retention: We were able to increase customer retention by approximately 5% for one of our clients using our predictive modeling techniques.
- Personalized recommendations: Our customized dashboards and reports provide our clients with insights into specific features, configurations, or combinations that are helping customers effectively utilize the product and stick around.
- Data-driven decision-making: Our clients have access to real-time insights that enable them to make data-driven decisions with confidence.
- Improved product development: By better understanding customer behavior, our clients can make informed product decisions that improve overall customer satisfaction and drive business success
Use Cases
Some key use cases of Applied AI Solutions for Google Cloud
- Unified customer view across all platforms
- Omnichannel SMS/Email/push Campaigns
- Audience Creation for Remarketing
- Content Recommendation Engine
- Sentiment Analysis
- Creative Analysis
- Customer Lifetime value
- Predictive Modelling for Leads
- Customer Data Platform
- Lead Scoring
- Offers/Vouchers Optimization – AI/ML
- Predict Optimal Marketing Attribution
- Content performance