Marketing Analytics

Understand the customer. How likely a customer is to purchase, how much a customer will spend, and a relationship with the business.  Big Data technologies and data science can fundamentally increase the impact of marketing. Whether you run traditional business to cutting edge technology, data science in marketing will ensure improved marketing ROI. 



From Fundamental to Advanced

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Customer Insights

A 360 degree view of customers, detailed market characterizations, improved marketing ROI.

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Price Sensitivity

Understand how customers value products or services, improve profitability, and forecast market penetration based on pricing strategies.

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Competitive Pricing Analysis

Make informed strategic pricing decisions, understand market position, and uncover competitors' pricing strategy.

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Customer Behavior Analysis

Understand customers and their behaviors to improve lifetime value, loyalty, floor layouts, web design, and target marketing.   

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Social Network Analysis

Send each person the right message at the right time and improve social media marketing return on investment by defining the relationships between the people and entities within a social network.

Human Capital Analytics

Keeping organizations competitive, productive, and efficient ultimately depends on employees. Hiring, retaining, and maintaining a talented workforce is perhaps the most important responsibility of an organization. Human Capital Analytics improves hiring, retaining, and encouraging talent development to ensure organizations succeed.  



From Fundamental to Advanced

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Compensation Analysis

Improve retention, increase productivity, and update compensation strategy.  

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Smart Hiring

Understand employee success, prioritize interviews, and ground hiring decisions in context.

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Talent Development

Protect human capital investment and ensure employee success by tracking, reviewing, and analyzing employee development.

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Human Resource Targeting

Find the right talent for even the most difficult to staff positions.  

Motion Analytics

Whether its the movement of ships, vehicles, financial transactions, email, or user activity, motion analytics provides your organization a simple, yet sophisticated way to track the movements of your data and automatically detect behaviors and flag anomalies.  Using historical data and machine learning techniques, Analyze develops custom algorithms that address your organization's needs. These algorithms learn and adapt to changes in your data to ensure that each behavior signature remains relevant.

Our Expertise

Understanding the behavior of moving data has a wide range of applications from nuclear physics and astronomy to counterterrorism and consumer applications. Predicting the location and behavior of data and drawing meaningful conclusions from their motion is conceptually and mathematically challenging. Many theoretical approaches have been developed over the years, and understanding which techniques are best applied to a particular problem is more art than science. For example, consider a set of ships moving on the surface of the ocean. Embedded in the movements of these ships is a whole host of information about the behaviors and intentions of their owners, captains and crews. Why does one vessel take a seemingly inefficient route between two places in perfectly good weather? Does it want to avoid being seen by other ships? Why do two fishing vessels from different countries rendezvous on the open ocean? Are they illegally exchanging their catch, or engaged in human trafficking? Why does a cruise ship's movements closely follow the wind and ocean currents? Is it adrift and in distress?

The techniques used to analyze objects in motion depend on the information sought. Analyze data scientists bring a range of mathematical and algorithmic approaches to motion analytics, including:

Graph Theoretical and Network Techniques

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Sometimes motion data is best understood as a collection of route and destinations (edges and vertices). Graph theory is a rich mathematical discipline with established solutions to many common problems such as connectedness, path finding, distances and probabilistic prediction. Interconnectedness in human relationships (sometimes called social network analysis, but not just applied to applications like Facebook and Twitter) can also be explored effectively through graph theoretical techniques.

Geometric and Pattern Matching Techniques

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Sometimes motion is expressed in regular, predictable or distinctive mathematical or geometric patterns. A fishing trawler might leave port, cast  its nets in a particular manner, retrieve them at a later time and return to its home port whereas a ferry may travel back and forth between two destinations in a straight line, never deviating from its pattern. When drawn out in time series or other projections, these ships create unique geometric patterns. Shape and object recognition techniques, series pattern detection and genetic algorithms help us understand, organize and classify this kind of motion.

Machine Learning Techniques

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Machine learning techniques help make sense of complex, unorganized and seemingly random data sets. Clustering identifies data elements that share a common set of features or properties. Correlation tells us whether some features of data (for example, the size or class of ship) help us predict other features (such as its speed or location). Dimensionality reduction helps us reduce the data search space to focus on only those pieces of information that matter. The most powerful techniques, prediction techniques, tell us what an object in motion should do based on past behavior as well as whether it is behaving outside the norm.



Text Analytics

Knowledge Management taken to the next level using advanced data science. Using text analysis algorithms including named entity extraction and ontological classification, your organization can leverage the digital knowledge created by your employees over the last decades to ensure it stays productive and cutting edge. 

How it can help your organization

  • Mitigate risks of retiring workforce and employee turnover
  • Leverage analytics to grow operational capability
  • Ensure leadership and employees alike have access to the most current and relevant information
  • Decrease learning curves and improve employee transition

How it works

Extraction, Translation, and Loading make your existing archives, emails, reports, and other digital media to accessible and searchable.

Natural Language Processing algorithms append metadata that provide additional search and pre-processing to speed up search capability.

Foreign language processing ensures your entire organization, regardless of nationality, leverages the same digital knowledge

Named Entity Extraction uses metadata to identify actor(s), regions(s), function(s), etc. beyond search engine like indexing

Link Analysis connects documents, texts, and subjects that provide real digital knowledge to employees and users. 

Ontological Classification algorithms classify your digital knowledge in the way that makes the most sense for your organization such as actor(s), region(s), and function(s). 

Application Programming Interfaces (APIs), Resource Description Framework (RDF) databases, and desktop tools load, process, extract, link, and classify streaming data to keep your organization cutting edge

History and Challenges

 Digital Knowledge Analytics algorithms were originally designed to build a next-generation intelligence collection and analysis grid to support ongoing intelligence services.  In building these algorithms it quickly became apparent that extracting meaningful intelligence from open source and unstructured collections presented several challenges including unique lexicon(s) and set(s) of actors and frequent interleaving of human readable text and computer-represented data, such as source code.  Working through these and other challenges one by one it quickly became apparent how useful these tools could become for any organization. Analyze developed a simple approach to tailor these algorithms to businesses and government organizations archives and historic documents to help address a growing need to mitigate knowledge and experience loss that occurs from a retiring workforce and employee turnover. 


Speak with a data scientist 

Data Management

Terra and petabytes of data present unique data management challenges. While it has become relatively inexpensive to buy flash and hard drive space it remains difficult to understand how to structure hardware, where to store information, and how frequently to index and precompute data. 

Our Expertise

With more than 25 years combined experience in distributed computing and parallel processing, Analyze data and computer scientists help organizations match the appropriate hardware and software with their long and short term strategy and needs. Analyze brings extensive experience implementing solutions like the following within the Fortune 100 and the largest government agencies. 


Data management determines data value

The basic principle of money management used in purchasing a home or opening a savings account apply to data management: management determines quantity and access. Not all data is created equal and it is important to have immediate access to data needed now while data that will only be valuable in the future can be collected and stored. Analyze helps organizations decide which data to store where and how to ensure access to it when it matures and becomes most valuable. 


Choosing which data to keep

Analyze provides recommendations on which data will provide organizations the most lift and which data is not worth the investment. 


Choosing where to keep data

The decision on where to keep data is influenced by cost and capability. There are many different database solutions optimized for different types of data, and there are as many hardware and cloud solutions to compare. Analyze helps organizations understand the pros and cons to each solution.  


Determining when data is valuable

In the same way that the value of weather forecasts depends on the date observed, the value of data depends on the timing of the analytics. 


Ensuring access to the right data

Analyze helps organizations implement the right named entity recognition and ontological classification tools to ensure employees can leverage organizations' intellect and experience. These tools go beyond indexing and search to provide the most relevant and comprehensive reach into previous reports, social network posts, emails, contracts, articles, and other data available. 


Under the Hood: the process powering our data science


Existing data is collected and new data is captured on the web, on the road or over the ocean. 


Data is organized into a format permitting visualization and analysis beyond the limits of traditional database platforms. A custom platform (e.g. hadoop, cassandra, NOSQL, etc.) will be assembled to best fit clients' needs.


Leveraging the most trusted and reliable open source infrastructure, we use Phosphorus, our proprietary platform, to visualize your data to support data capture, organization,  analysis, and ultimately provide the justification you need to act.


Whether your organization needs basic business intelligence (count, mean, regression, and log) or the most advanced data analytics, we provide the analysis that you need. Our advanced capabilities span from graph theoretical and network techniques to machine learning and geometric pattern matching techniques and beyond. 

Read more about the The Technical Stuff



With experience working for the most advanced government agencies to the Fortune 100, we understand that the analytics must support decision making for business objectives and organizational missions. We team with industry experts to ensure you receive data driven recommendations that meet your mission or objective. We will then help you design the best method to implement these recommendations within your organization, from setting new or configuring your existing hardware, installing new software, or writing new algorithm and software code tailored to your organization.