You have data. Lots of it. But turning your big data into truths is like looking for a needle in a needle-stack. That is where data science comes in. Data science helps you separate the signals from the noise. Coupled with great design and engineering, data science can be the backbone of creating the next secret sauce that will drive your business for the decades ahead.
Approach to Data Science
We see data science as a means to business results. Enabling businesses to act is as important as the predictive models themselves. Our approach to data science starts from a business problem and aims to demonstrate business results as early as possible. Below are the steps involved:
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Understand business problem: Our engagements start with understanding your business goals.
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Identify data opportunity: We look at your data, as well as public sources of data, and figure out if there is a smart way to achieve your business goals using data science.
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Explore data: We experiment with data, building and testing predictive models.
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Implement actions: We implement systems that allow you to use the results of the predictive models in decision making or to improve your customer experiences.
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Continuous refinement: We iterate and refine our systems to improve their accuracy and performance.
Our Capabilities
Data science is a broad field, but we have expertise in some of these areas:
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Data architecture: Structure data flow to store, integrate and deploy data in an organization. Use scalable architecture to adapt to changing volumes of data.
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Recommendations: Uncover consumer behavior patterns to target their future needs. Increase customer engagement and satisfaction.
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Predictive modeling: Generate data-based real-world models and simulations for more complete and consistent information in decision making.
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Personalization: Tailor offerings and experiences to each individual customer. Analyse data in real-time to quickly respond to changes in customers preferences.
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Reinforcement learning: Determine personalised ideal actions for individual customers to maximise gains in short and long run. Automatically updates recommendations to reflect shifts in customer behavior.
Success Stories
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Apple Daily, a media company with over 10 million active users, worked with Altitude Labs to develop a scalable data warehouse to power personalization in their applications. -
Zalora, Asia’s leading fast-fashion retailer, used Metisa to implement product recommendations that doubled engagement and increased sales conversions. Read more. -
Yuehua, a leading Chinese lifestyle department store, worked with us to identify high-potential customers for events and VIP promotions. Read more.