Pacific Data Science

Pacific Data Science

Use Cases for Data Science

  • All Applications
  • Customer Engagement
  • Human Resources
  • Inventory Management
  • Operations
  • Risk Management
  • Customer Engagement

    Personalize your Customer Experiences

    Digital marketing is shifting away from generalized campaigns toward targeted micro-moment advertising, tying each audience impression to some tangible exchange of value with an individual consumer. Creating these vital micro-moments involves a bewildering array of factors: demographics, browsing habits, spending patterns, and social networking behavior, just to name a few. Pacific Data Science's advanced clustering algorithms can identify very specific groups of like-minded consumers who value a similar type of interaction, allowing you to create hyper-personalized advertising campaigns.

    Retain Your Talent

    One of the pillars of a successful business is to keep your employees happy. Not only does the expense of recruiting and training new employees directly hit your bottom line, but the intangible costs of attrition can be even more substantial. When an employee quits, their valuable ideas, insights, and customer relationships go out the door with them. The challenges of retention are broad and you may struggle to understand why attrition is occurring in your workforce and to proactively pinpoint individual at-risk employees. Pacific Data Science can work closely with your human resources professionals to develop a custom solution to both of these challenges. Our machine learning algorithms will identify and rank specific risk factors that drive your attrition, and will help you tune employee outreach and incentives to have the maximum possible impact.

    Optimize Your Inventory Levels

    Inventory management is one of the main operational challenges in the retail industry. Often, when a retailer reports disappointing financial results, poor inventory planning is often singled out as the largest culprit for subpar margins. As brick-and-mortar retailers have expanded into the digital realm, this challenge has become even more acute. Planning inventory weeks in advance is a delicate problem, balancing the risks of lost sales and markdowns against excess carrying and shipping costs. It's also necessary to account for a wide range of variables, from internal factors like marketing spend, supply chain dynamics, and contractual obligations to external influences like weather and consumer spending patterns. Traditional approaches, like fixed reorder quantity systems, are still in widespread use despite being inadequate to solve this problem in the modern retail environment. At Pacific Data Science, we excel at solving this type of complex optimization problem, integrating our expertise in time series prediction, search algorithms, and reinforcement learning.

    Boost Your Revenue with Dynamic Pricing

    Sophisticated revenue management is the cornerstone of airlines, hotels, and ride-sharing services. They have blazed a trail with innovative dynamic pricing strategies, and as a result, these industries are enjoying record financial performance. As an abundance of big data permeates the entire economy, there's potential for this approach to have a similar transformative impact on a wider swath of businesses. Pacific Data Science has considerable expertise with algorithms that can be used to segment your customers' willingness to pay, ensuring that you aren't leaving money on the table.

    Stay Ahead of the Demand Curve

    Whether you're a coffee shop or an emergency room, you need to adapt your staffing levels to cope with fluctuations in traffic to your business. If you aren't able to anticipate these variations, you might find yourself facing excessive costs from wasted hours and overtime or, conversely, lost revenue from customers who don't want to wait in line. Pacific Data Science helps you anticipate future demand, and capitalize on this knowledge to improve your bottom line. We build custom solutions that ingest your historical transaction data from any number of physical sites, and generate real-time guidance on how to adjust and reallocate shifts and inventory across those locations.

    Stamp Out Fraud

    More than 60 percent of all organizations, from large established institutions to small e-commerce startups, fall victim to payment fraud every year. Fraudsters are becoming more tech-savvy, exploiting vulnerabilities on an unprecedented scale, making it increasingly difficult for analysts to keep up. Furthermore, traditional detection methods often suffer from high false positive rates, flagging transactions that are actually legitimate and aggravating your valued customers in the process. Pacific Data Science improves upon your organization's static rules-based system with a more flexible and robust model that automatically adapts to rapidly changing fraud patterns. Partnering with us, your risk managers can reduce the amount of time they spend conducting costly manual reviews. Our approach empowers them to be faster and more effective at spotting unauthorized purchases, scrutinizing fraudulent insurance claims, validating the authenticity of new accounts, or reducing the frequency of chargebacks.

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