We offer a range of services designed for innovative businesses. The common focus is on providing a competitive advantage through innovative technology and advanced practices. These are discussed in detail on this page. Visit our blog for a more free wheeling discussion on various related (and less related) topics.
Web Development Services [top]
Our web development focus is on rapid development of highly dynamic sites using the Ruby on Rails language and web development framework and the Extreme Programming agile development methodology.
Ruby on Rails allows for the rapid development of model-view-controller (MVC) patterned data driven web applications.
We develop exclusively using the Extreme Programming (XP) methodology to enable the development of applications with maximum user value, minimum defects, and shortest time to live delivery in an environment with dynamic and undocumented business requirements. We achieve this with careful adherence to a highly tested and proven process that is rapidly gaining acceptance among innovative software development groups.
We program in pairs. This ensures constant code review, constant discussion about design and architecture, knowledge sharing and cross training.
We use Test Driven Development (TDD). Before we write code, we develop tests to prove it works. Our code is developed from the ground up with a fully functional testing framework. As complexity increases we remain confident that everything continues to work, and can refactor and enhance products with confidence. We test to avoid errors, rather than testing after the fact to find them.
We develop iteratively. Every week we strive to have a live version of whatever we are working on. The choice to go live remains a business decision based on the ability of existing functionality to adequately meet objectives. There should never be a technical reason not to go live during the development process. We implement the most important features first, and complete an iteration each week. We work from a simple list of user stories and features, working closely with the business to develop a continuous feedback loop. At the end of any iteration, there are only less important things that remain to do. But these remaining things are maleable; they can be reordered, added to or reduced as the business learns and the business environment changes.
Onsite Analytic Consulting [top]
Morgan Stanley, Wells Fargo Bank, Intuit and eToys have benefited from our profitability focused approach to customer relationship analysis.
Lawrence Sinclair, is our chief analytic consultant and data mining practitioner. Call him at +1(415)407-1475 to set up a free consultation. Learn about our process for providing a free demonstration of our predictive models using your own data applied to your own specific needs. This process is outlined below.
Our analytic techniques involve the use of decision trees, neural networks, and logistic, multinomial, and simultaneous system regressions. We carefully consider our clients' specific priorities and business circumstances. We incorporate insights from other best practices. We transfer knowledge. Typically, we are able to achieve a 50% to 100% improvement in marketing effectiveness and overall customer profitability compared to the best efforts of analysts who do not use our approach and our tools.
We use advanced data mining, machine based learning and statistical analysis techniques to discover new actionable factors driving customer behavior and marketing opportunities. We define a hollistic view of the customer that presents our clients' business objectives within a framework that considers all angles: customer acquisition, customer support and service, cross-sell, up-sell, and customer retention. We show how these factors work together and must be carefully balanced to maximize customer lifetime value. We study the behavior of customers through various channels ranging from the web to telephone to identify opportunities to reduce costs and to increase effectiveness.
Analytic consulting can blend into full fledged analytic system development projects. Analytics is often the first step in developing automated and augmented business analytics infrastructure. For example a final outcome might include an end-to-end email campaign tracking system, including analysis of outcomes and revenue impacts. Or you could end up developing datamarts focused on profitability or delivering targeted messages and other interactive marketing. In these cases, we can act as architect, implementor, and analyst.
Our analytic approaches are best suited to client businesses with many thousands of customers, many millions of dollars in revenue, and a million or more dollars in customer acquisition expenditure. Typically, our clients have a million or more customers, engage in many multi-million dollar marketing efforts, and strive for or have revenues of a billion dollars or more.
These clients typically have many domain level experts who understand their business lines very well. They seek additional information and insight to meet challenging new business objectives. This is where we come in.
Our Predictive Modeling Process
When you invite us to create a predictive model for your company we enter into a process of consultation, concrete demonstration, and infrastructure enhancement. The initial consultation, and often this entire process, is free and without obligation. Because we are able to demonstrate the real world value of our predictive models when applied to specific business problems, without giving the model itself away, we are able to provide our prospective clients with a way to see the value of our work before making a financial commitment.
The process works as follows:
Step 1: A free Consultation
We meet with you to identify the greatest opportunities for benefit from predictive models. For example,
- parameters which lead to the fewest defects in manufacturing processes;
- identify customers most at risk of switching to competitors;
- identify prospects most likely to respond to a marketing offer, and the most profitable offer to make to them.
Step 2: Predictive Variable Dataset
We assess your existing database systems for their ability to support predictive analysis.
If sufficient data exists to produce a predictive model, we help to define a predictive dataset for our use in creating a predictive model. Otherwise, we can help to define and build the processes and databases necessary to create an analytic datamart. Producing a comprehensive dataset can be very time consuming. Frequently, we can help you produce a simple dataset that will serve the purpose of achieving substantial improvements over your existing processes.
Step 3: Your Custom Model
Given a dataset for our use, we can produce a free custom model applicable to your immediate business needs. The model results are presented in the form of specific predictions abou the outcome of individual events. We also provide measures of the overall predictive power of the model.
Step 4: Independent Evaluation of Our Model
To see that our models really work as claimed, we ask our clients to give us explanatory data, but not the outcomes, for several thousand cases. We will confidently identify the small group of cases that contain virtually all of the outcomes of interest.
For example, a business might lose 3% of their customers each period. One of our models could predict the probability that each customer would leave. The prediction would use past data given to us by the client. Typically, we could use this data alone to provide a list of 25% of the customers that we will contain 80% of the customers who end up leaving. Although we are not given knowledge of the actual outcome, our client knows which customers left and can independently confirm the power of our predictions.
A model such as the one in this example can produce substantial financial benefit when used with current data to predict the future. Assume $10 were going to be spent on 100,000 customers to help retain their business. Using our model, $20 could be spent on the 25,000 customers most at risk. This new strategy would likely be more effective and cost $500,000 less to implement. Alternatively, the original $10 campaign could be rolled out in a more focused fashion to the smaller 25,000 customer segment, resulting in a similar outcome at a quarter of the cost.
Having seen a demonstration of our ability to predict outcomes for today using only knowledge of yesterday's data, we provide independent validation and confidence in our ability to predict tomorrow's outcomes using data from today.
This ends our free, no obligation, demonstration which can transition into a rapid implementation of this and other models.
Step 5: Using our Models
If a client wishes to proceed, our next step is to make predictions about future outcomes which address urgent business needs. We can 'score' a set of existing data and provide a dataset that can be used to prioritize customers. We can also provide parameters and a program that can be included in existing datawarehouses and business intelligence systems to make realtime predictions and decisions. In either case, the scores and parameters will be useful for making decisions for the next few months, or few years, depending on the business problem and characteristics of the particular business. We will continue to work with you to implement effective and industry leading prediction-based decison making.
For more information, call business intelligence consultant, Lawrence Sinclair, at (415) 407-1475 or (212) 933-9324.
Frequently, clients do not have analytic datmarts or other data sources that can be readily used to make predictions about their current business problems. Before we can do our predictive magic, these systems need to be in place. We frequently build, assess, and re-engineer analytic datamarts for our clients. Creating such systems can take anywhere from a few weeks to a few months. Analytic datamarts support a wide range of reporting, analysis, quality assurance, and decision making in addition to predictive modeling.
Once in place, an analytic datamart enables us to provide a