Make Your Business Data-Driven
Data is the lifeblood of your business, and analytics can help you track how well things are going and determine what is and isn’t working. Today’s leading companies are successful because they use their data to help them operate more efficiently, and they leverage insights obtained from data to deliver superior products and services to their customers.
Most companies, however, are not effectively using the data they have. Their data is disorganized and difficult to access, their internal processes are much less efficient than they should be, and they lack the insights necessary to make important decisions. If this sounds familiar, we’re here to help!
Data Science and Analytics Services
We’ll help you organize your data, intuitively quantify and analyze your operations, and optimize your processes so that your business operates more efficiently and profitably.
Data Cleaning & Organization: Extract data from systems and clean, combine, organize, and store it where it can be accessed and analyzed by those who need it.
Reporting & Visualization: Gain visibility into your operations with intuitive reporting that provides you with exactly the information you need to see.
Data Analytics: Deep analysis of your data to discover existing trends, patterns, themes, and perspectives that can help you make more-informed decisions.
Data Mining & Modeling: Discover hidden relationships, generate accurate predictions and forecasts, and model important scenarios that impact business performance.
Process Automation: Streamline and automate complex, time-consuming, and data-intensive tasks so that your business operates as efficiently as possible.
Data Product Development: Leverage the power of your data to build customized systems and applications that improve your business’ products, services, and operations.
To get started, click the button below.
How it Works
Here's what working with us looks like and what you can expect as we go through each step in the process.
Step 1: Complete Questionnaire
When you click the Get Started button on this page, you’ll be taken to a questionnaire where we will ask you some questions to learn a little bit about your business, your data, and your analytics needs. The information you provide will help us get a better understanding the analytics you currently have in place, what your goals are, and how we can best help you achieve them.
Step 2: Customized Proposal & Quote
Based on your answers to the questions in the questionnaire, we will put together a proposal for the services that are most appropriate for your business. The proposal includes a list of deliverables for the project, a quote for how much we estimate development would cost, and an estimate for how long we estimate the project will take.
Step 3: Development & Deployment
Once you've accepted our proposal, we will get started working on your project. Throughout the project, we will provide you with weekly updates and ask questions when we need clarification to ensure that what we are producing meets your expectations. Once your solution has been developed, we will deploy it, make sure it is working as expected, and provide training to you and your employees on how everything works.
We'd love the opportunity to work with you and show you what we can do. If you'd like to work with us as well, click the button below to get started.
Past Data Science & Analytics Projects
Our team members have successfully completed projects across a variety of industries. Below are some examples of our past work.
Retail Analytics Projects
Sales Forecasting and Inventory Optimization: Significantly improved forecasting accuracy by leveraging supervised machine learning algorithms. Developed custom optimization system on top of forecasts that identified obsolete inventory at stores and transferred it to locations with the highest probability of selling the items.
Automated Inventory Reconciliation and Monitoring: Automated the inventory reconciliation process, reducing the total effort required by 80%, reducing errors, and increasing accuracy. Developed and implemented an automated inventory monitoring system that tracked purchases, receipts, inventory, and sales. The system sent weekly reports containing action items to store managers for resolution.
Dynamic Pricing and Allocation System: Developed system to monitor competitor pricing in online marketplaces and price merchandise competitively while still achieving target margins. Pricing algorithms ran multiple times per day to ensure that products were always priced as competitively as possible. The system also dynamically allocated inventory to the most appropriate sales channels based on demand for products.
Ecommerce Reporting Automation: Automated complex, spreadsheet-based report generation and distribution, saving 9 hours of employee time per week. Functionality included automatic extraction of data from ecommerce systems, automatic aggregation and calculation of metrics, automatic export of finalized data, automatic import into pre-formatted templates, and automatic email distribution of reports to stakeholders.
Marketing Analytics Projects
Customer Propensity and Capacity Modeling: Assisted sports marketing company with the development of priority and capacity machine learning models to predict the probability that prospective customers would purchase season tickets to sporting events and the magnitude of each customer’s expenditure. This resulted in a functioning data product that combined data from multiple sources and generated more accurate predictions than the company was previously able to achieve.
Direct Response Predictive Modeling: Built predictive models to identify households that were most likely to make a donation to a particular cause for a non-profit organization’s direct mail campaign. Significant demographic data was combined with previous household donation behavior to build the required models, which increased the number of donations as well as company revenue.
Finance Analytics Projects
B2B Credit Scoring and Loan Prediction: Worked with finance company to validate and improve machine learning models that predicted the creditworthiness of prospective clients and helped determine whether loans should be issued. This allowed the company to offer instant credit decisions and pre-approvals to businesses in need of working capital.
Education Analytics Projects
Data Science and Analytics Curriculum Development: Designed and developed curriculum for a coding boot camp’s data analytics program. Lessons developed ranged from introductory topics like Python programming, relational databases, and statistical data analysis to more advanced topics such as recommender systems, machine learning, and distributed analytics. In addition to the lessons, hands-on exercises and projects were also developed so that students would have the opportunity to practice their newly-acquired skills and solidify their understanding of the material.
Data Analysis and Business Intelligence Reporting: Assisted education company in analyzing data, discovering insights, and building business intelligence reporting, visualizations, and dashboards in Periscope. Data science methods leveraged included data cleaning, data aggregation and transformation, calculation of descriptive statistics, hypothesis testing, and network analysis.
Textbook Subject Classification System: Designed and developed a textbook subject classification system that used course textbook adoption data, similar titles, and machine learning algorithms to determine the subjects and topics of books where they were previously unknown. This system was used to accurately categorize over 80,000 textbooks and enabled new kinds of reporting at the organization.
Communications Analytics Projects
Phone Communications Network Analysis: Analyzed phone and messenger communications between different parties, inferring and modeling relationships via graph analytics. The analyses conducted identified clusters and communities within communication networks, the most important and influential individuals within those clusters, and instances that appeared to contain interesting or potentially suspicious network activity.
Cybersecurity Analytics Projects
Threat Intelligence Platform Design: Put together designs and specifications for a threat intelligence platform that would allow a cybersecurity client to monitor threats to their clients’ supply chains, identify current vulnerabilities, conduct asset inventories, and compare threats across similar firms. The design included methods for collecting and restructuring data from several APIs (including information on domain spoofing, sensitive data found on the dark web, and social media conversations), setting up and storing the data in a scalable fashion, and building search, analytics, and visualization interfaces on top of the data.