Relevant for:

  • Consumer Goods
  • Retail

InfomatiX Platform:

IX Automation and Optimization

IX Big Data Mashup

Business topics:
  • Consumer insights
  • Sales forecasting
  • Market segmentation

Analytical Tools
  • TIBCO Spotfire
  • RapidMiner

  • Hadoop
  • Predictive Analytics

Simplified BI ecosystem supporting brand decisions

The Challenge

Companies operating in the CPG and Retail industries are facing with harsh competition and struggling with customer retention. Consumers have so many options today with so little difference between the products, they usually switch brands quite often and brand loyalty is hard to reach. Differentiation is more important than ever before.

However there are huge amount of data from many various sources waiting to be analyzed and several tools offered on the market to utilize this information, the wide possibilities of choices are blocking sometimes. An inconsistent usage of different kind of tools can result in duplicated data storage and unreliable calculations.

Relevant picture on the target consumers enables smart decision making and products suit consumers’ needs the best. That is why, predict customer behavior is a consistent issue as it can ensure competitive advantage. The challenge is that predictive analytics often requires utilization of large amounts of data from multiple sources which is hard to process and visualize.

Understand consumers on a deep granularity level is crucial to succeed but challenging at the same time. Marketers must improve efforts to utilize existing data to better understand the needs of each target audience and tailor marketing campaigns appropriately.

The 3-level ecosystem

The simplified infrastructure consists of 3 levels to cover the functionalities of a full BI ecosystem. The seamless data preparation and predictive workflows are designed to be transparent with consistent calculations and without unnecessary replications. The analysts utilize self-serve predictive capabilities of the advanced analytics tools, as well as self-discovery opportunities of the visualization tools in order to ensure that the brand related actionable insights are captured by end users and decision makers as early as possible.

The 3 levels are the following:



The Consumer information sources – the big data platform to ensure seamless data flow

The leveraged big data infrastructure stores and processes large data sets while also saves time. The seamless mashup meaningful data sources like Google Analytics, Twitter, Facebook, YouTube, internal DW  is inevitable for omni-channel marketing analytics.

Predictive Analytics – advanced analytics for consistent data explorations and forecasts

The advanced analytics layer not only provides data preparation for visualization (cleansing, enrichment), but the best predictive analytics platforms ensure calculation transparency and data credibility for decision makers with their self-serve workflow planning capabilities and built-in operators. The advanced analytical models also enable clear predictions and forecasts when designing and optimizing the customer journeys.

Data Visualization – self-serve analytics to focus on actionable insights 

Empower analysts to instantly visualize customer journey data from predictive analytics models and allows self-serve analytics for business users. The visualization is constructed to tell a clear story from data, the trends behind the KPI related to customer retention, and how to minimize the effects of drainers and utilize the learnings from drivers. This way, the decision-makers can focus on what matters most, the actionable insights.

The Values

Highly effective marketing activities: the solution allows insight-driven decision making.

  • Rapid responses to consumer demands
  • Increase in marketing conversion rate with cleverly planned and adopted marketing campaigns
  • Discovery of new revenue opportunities

Saved time: Fast reponds to business questions are the result of all connected tools. The created BI ecosystem settles an appropriate format of processing huge amount of data quickly.

  • Reduced time from insight to action and monetize on gained opportunities

 Reduced costs and complexity: the integrated solution helps connect different layers of processes and prevent data duplication.

  • Decrease infrastructural cost
  • Capitalize on data through actionable insights
  • Reduce marketing spending associated with channel-mix optimization

The simplified BI ecosystem helps to capture meaningful data, predict customer behavior and optimize marketing/sales based on real insights with analytics capabilities results in huge advantage on today’s highly competitive consumer markets.