Predictive Analytics

One of the strengths of predictive analytics is to help see beyond current activities, into future scenarios, by predicting (with a known certainty) the potential outcome of an event.

  • Will customers leave in the future?
  • Who is the best candidate to hire?
  • Are consumers likely to recommend a service or product in the future?
  • When is it likely that there will be an energy outage?

Captured as probability scores, such measures describe the likelihood that the event of interest will happen, going beyond the current facts and figures, providing an analytical crystal ball. And by knowing what is likely to happen, current decisions can be made to help drive more desired results in the future. For example, knowing that a customer is more likely to

For example, knowing that a customer is more likely to leave than stay, (say, based on decreasing purchasing patterns and increased calls into the support line), a personal call from a customer care representative or an incentive offer may help salvage the relationship. And while an experienced analyst may be able to see the emerging trend in the data, and believing that this customer is on the verge of leaving, they might have a hard time quantifying this event. How likely exactly is the customer to leave? A predictive model provides a quantitative measure to base decisions on (e.g. the model can there is an 80 percent probability that the customer will leave), without human, subjective bias.

Can Predictive Analytics Ever Truly Be Made Pervasive?

It sure can! In the end, it comes down to what we mean by “pervasive.” Can information workers in an organization consume and benefit from predictive analytics (PA)? Absolutely. In the final analysis, this is precisely what’s meant by making predictive analytics truly “pervasive.” We can:

  • Develop sophisticated predictive models using the latest machine learning techniques and ensembles
  • Help you cross-sell or upsell products to customers and meet your targets.
  • Help you benefit from predictive insights that permit you to understand a given customer interaction or behavior across different channels, recommend products that can generate the best revenue opportunities, or make time-critical adjustments to retain high-value customers.
  • Push it out to information consumers
  • Solve the challenge on the “producing” end
  • Devise creative solutions to problems, be it by bringing in new sources of data and variables, developing or selecting new algorithms and functions, applying a rigorous approach to problem-solving
  • Recast more staff members as producers of predictive analytics insights

Social Network Analysis

AMSTAT Consulting is dedicated to using data to figure out what customers are saying about you and what they are saying about your competition. We can use this newly found insight to figure out how this sentiment impacts the decisions you are making and the way your company engages. We can:

  • Determine how sentiment is impacting sales, the effectiveness or receptiveness of your marketing campaigns, the accuracy of your marketing mix (product, price, promotion, and placement), and so on
  • Answer what is ultimately a more important question: “Why are people saying what they are saying and behaving in the way they are behaving?”
  • Look at the interaction of what people are doing with their behaviors, current financial trends, actual transactions that you are seeing internally, and so on
  • Get to the core of why your customers are behaving a certain way that requires merging information types in cost-effective ways, especially during the initial exploration phase of the project
  • Enable companies to incorporate the understanding of the textual content, providing the critical competitive advantage over their peers, providing key areas of improvement and increased vigil to streamline workflows. Key areas include:
    • Opinion Mining & Sentiment Analysis
    • Brand Monitoring & Competitive Analysis
    • Lead Generation
    • Trend Analysis

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Automated Modeling

We can:

  • Use a single run to test multiple modeling methods, compare results, and select which model to deploy
  • Choose the best performing algorithm based on model performance
  • Produce accurate models quickly without specialized skills
  • Create the most sophisticated of streams
  • Compare multiple modeling approaches
  • Explore a multitude of model combinations and options
  • Rank the generated models based on the measure specified, saving the best for use in scoring or further analysis.

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Open-source Technologies

AMSTAT Consulting can:

  • Use R, Python, Spark, Hadoop and other open-source technologies to amplify the power of our analytics
  • Extend and complement these technologies for more advanced analytics while we keep control

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Let’s get started!