According to Deloitte studies, less than 20% of companies around the world are using analytics tools to identify future opportunities. At SEREVISO we leverage the predictive analytics and adaptive analytics tools to extract future trends and predictions for our partners so they could be ahead of the competitors.

In short, predictive analytics tools means using a series of algorithms and features to analyze data and identify what is most likely to happen with the business operations based on its past. We take the raw data and help you look beyond what you already know.

predictive analysis

Businesses can implement predictive analytics tools in any of their departments to reduce risks, reform operations and maximize revenue. Here are a few examples:

Marketing Department

  • Lead Scoring: correlate the actions of the existing customers with future marketing efforts
  • Refine Segmentation: nurture future customized campaigns by understanding specific targets
  • Content Distribution: identify the type of content that resonates the most with customers, distribute similar content to the leads
  • Upselling and Cross-selling: anticipate future needs and selling opportunities
  • Campaign Channels: extract insights about the most appropriate channels

Financial Department

  • Shrinking Expenses: identify where underperformance is likely to occur, help companies take actions before it happens
  • Improve the financial planning process: make better business decisions
  • Market Fluctuations: incorporate external data and internal data to enable scenario modeling


  • Result-oriented Sales: deduce which individuals are more interested in buying
  • Conversions: increase conversion rate through better targeting
  • Time-saving: focus on the relevant prospects

Predictive Analytics Methodology

Analyze the business

  • Business objectives
  • Success criteria

Understanding business data

  • Collect data
  • Explore data
  • Check data quality

Prepare data

  • Data selection
  • Data cleanse
  • Data formatting


  • Deploy the model
  • Score the results
  • Monitor and optimize

Model evaluation

  • Select the model
  • Validate the model

Data modeling

  • Select modeling methods
  • Build the suitable model

Are you ready for new opportunities?

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