Solutions
Take advantage of new data technology strategically. Sparkbeyond, an AI-powered Data Analytics platform,
quickly transforms your data into valuable assets, creating business insights for the fast-changing times.
In order to get the right answer,
one must first ask the right question.
In order to get the right answer,
one must first ask the right question.
Case ①
Churn Management
─ Challenges
Most customers leave the service without giving feedback on the reason for termination. From a company’s perspective, it is more efficient to spend money on retaining existing customers, rather than re-acquiring them after exiting.
Many companies find it difficult to detect large customer churn before a noticeable drop in sales.
─ AI Opportunity
AI can pinpoint who is currently out of the box by discovering new patterns in past customer activity. AI-powered problem-solving technology can connect complex data to find millions of deviations from hundreds of data sets and thousands of fields.
After subdividing customers in the risk group, AI can be used as a strategic measure to preserve customers.
Case ②
Location Optimization
─ Challenges
Optimizing branch location has a significant impact on business opportunities. Accurate data analysis is essential for strategic location planning.
The cost of branch expansion is substantial, and having AI-based, branch-specific insights is essential to gaining consumer visibility.
─ AI Opportunity
AI connects complex external data sources to help you find specific areas where potential profitability and campaigns are highly effective. AI-powered problem-solving technology can discover millions of profitability factors that are intuitively difficult to understand through hundreds of location data sets and thousands of fields.
AI-based location information optimizes sales teams’ sales activities, makes them more personalized, and helps with marketing-related programs and in-store product selection.
Case ③
Sales process Optimization
─ Challenges
The multi-channel sales team is trying to find key customer engagement points. Today’s business environment is constantly changing, and it is becoming increasingly difficult to predict.
As the company’s need for optimizing KPIs, efficiency and maximizing sales increases, it is difficult to evaluate the sales pipeline.
─ AI Opportunity
By discovering new patterns with AI’s data analysis, you can pinpoint what is the most impactful variable for your company’s KPI. AI analyzes operational management performance, supply chain, logistics, and field operations data, and determines new factors affecting performance.
AI can increase demand forecasting accuracy by analyzing vast amounts of data.
Enable rapid decision making – “Why Sparkbeyond?”
Delivering more than $ 1 billion of business impact to more than 20 industries.
Enable rapid decision making
“Why Sparkbeyond?”
Delivering more than
$ 1 billion of business impact
to more than 20 industries.
Current VS SparkBeyond Approach to Analytics
Key Features
01. Feature Engineering
It automatically generates millions of hypotheses in a few minutes on the AI platform and extracts highly interactive features based on target values to provide insight.
02. Context Datasets
Complementing insufficient data by adding multiple data sets between various external data sources and events to the pipeline and generate a variety of insights.
03. Insights Studio
It supports decision making with stronger insights by segmenting/combining influential hypotheses in business.
Use cases by industries
CPG
● “Where to play” – POC churn, TT store sales potential, etc.
● “How to win” – assortment, range, etc.
● Demand forecasting
Retail
● Location optimization
● Assortment
● Pricing
● Promotions
● Demand forecasting (inventory mgmt.)
Insurance
● Cross-sell & up-sell
● Automated underwriting & pricing
● Churn management
● Claims fraud & streering
Finance
● Market targeting / Life-events
● Credit risk scoring
● Fraud detection
● Portfolio optimization
Telco / Media
● Life-time value (subscription, Churn, Cross sell & up-sell)
● Latency prediction
● Content distribution optimization
Energy,
Materials & Manufacturing
● Demand forecasting / output prediction (Completion optimization)
● Out of order production
● Fuel utilization optimization
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