SmartStock is one of our pre-eminent Azure Machine Learning solutions, and the first in the Decision Profit Model family of models created by Neal Analytics. This solution was developed out of the knowledge our team gleaned through experience in the beverage and cell phone industries. SmartStock takes basic enterprise resource planning to the next level through more accurate demand-side forecasting for better stocking and resupply. Smartstock currently has models that plug and play for the predictive factors social media, weather, promotions, local event, and competitive data. These demand-side forecasts truly predict the demand of businesses on a channel-by-channel basis, and we’ve seen real success integrating with Dynamics and SAP ERP modules. We are very interested in building out other models, so let’s talk about how your company’s stocking problems can be solved by big data with SmartStock.
BidProfit is our other flagship Azure Machine Learning solution offering. This solution is designed to automate the highly painful process of keyword bidding for paid search engine results on Google or Bing. BidProfit provides a rapid feedback loop and uses machine learning to accurately predict the appropriate bid for a desired search rank. This machine learning solution saw outstanding results during its first implementation at a large travel retailer in their tail keyword portfolio, and as a result of this, Microsoft is implementing it in their Azure marketing group to save and optimize their Search Engine spend. Additionally, this solution was featured at Microsoft’s WorldWide Partner Conference in 2014, where Joseph Sirosh, VP of Azure Machine Learning, presented the solution with Dylan Dias, Neal’s CEO.
Neal Analytics offers the technical services required for you to get the most out of your product research data. Our research teams specialize in offering high-quality managed research services in the technology and retail industries. We meet you where you are at in your research life-cycle, assist your team with growth as your product changes. Typically, our teams operate in groups of five, with a team project manager, and several individual branching focuses. We find that our technical expertise in applied data science and analysis allows you a leg up on the competition in social media, telemetry, survey, and product use data. If you want to get the most out of your product research data, Neal Analytics can help.
Data Science Managed Services
Neal Analytics enjoys partnership with businesses as closely as possible to drive better ROI and profitability through better use of data. Neal Analytics Data Science Managed Services allow Neal to best utilize our technical competency to bring you superior results from your data. Our unique approach to teaming, structure, infrastructure usage, and technology allows us to function as a leader in this space. This approach is why our business grows so rapidly within our customer-base, and why we are relied upon so extensively to provide data science services to our customers across the globe. Typically, our teams begin by proving value through a set of structured “Proof-of-Profit” engagements, and we proceed to partner with business units to provide the structure required to identify, quantify, and resolve data science problems. We find that a managed services approach to this work allows us to partner most closely and easily with management teams, along the lines of several predefined service level agreements.