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Arun Subramanian
Analytics & Insights @ Amazon Ads, Ex-Nielsen, Ex-Mu Sigma
Arun Subramanian is an accomplished Analytics & Management Consultant with over 11 years of experience in the retail, clothing retail, pharma and telecommunications sectors. He has expertise in store operations, merchandising, customer insights, and marketing. Arun has an impressive educational background, having studied a Master of Manufacturing Systems Engineering and a Bachelor's degree in Chemical Engineering.
Through his roles as Director and previously Senior Manager of Marketing Effectiveness at Nielsen Marketing ROI, Engagement Manager and Associate at Mu Sigma Inc., Manufacturing Validation Coop at Biogen Idec, and Junior Manager at Dr. Reddy's Laboratories, Arun has developed a multitude of skills. His areas of expertise include sales and traffic forecasting, customer satisfaction score reporting, market basket analytics, customer profiling, personalized targeting, and much more.
Arun has a friendly and professional tone, with a focus on optimizing for SEO and including keywords and searchable phrases. He is an individual with extensive knowledge and skills, and his experience and education make him an excellent addition to any professional team.
Highlights
𝐁𝐞𝐲𝐨𝐧𝐝 𝐌𝐨𝐝𝐞𝐥 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧: 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞 𝐨𝐟 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠
In data science, we often find ourselves immersed in the intricacies of model validation, like assessing accuracy metrics (e.g. RSQ, Adjusted RSQ) , goodness of fit (e.g. MAPE, RMSE), determining train-test split (e.g. 70-30 split, k-fold cross validation), and selecting an appropriate holdout approach (e.g., time based holdout, random sample holdout). While these are essential components of model development, they often overshadow a fundamental aspect: 𝒎𝒐𝒅𝒆𝒍 𝒔𝒑𝒆𝒄𝒊𝒇𝒊𝒄𝒂𝒕𝒊𝒐𝒏.
𝐀 𝐰𝐞𝐥𝐥-𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐞𝐝 𝐦𝐨𝐝𝐞𝐥 𝐢𝐬 𝐭𝐡𝐞 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐚𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐚𝐧𝐝 𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐛𝐥𝐞 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬. The choice of variables, their interactions, and the overall structure of the model directly influence its predictive power. Yet, this often overlooked step is where the true value of business understanding lies. Here are few real-world examples from my MMM consulting experience.
𝑨𝒑𝒑𝒂𝒓𝒆𝒍: When modeling apparel sales, understanding the nuances of product categories is paramount. Tops and bottoms, while both clothing products, have distinct seasonal patterns and purchasing behaviors. Likewise, Women's apparel demand is more susceptible to fashion and seasonal trends while its impact on Men's apparel is more subtle. And a single apparel product (e.g. jeans) can have different sizes, color, fit, etc. 𝑹𝒆𝒕𝒂𝒊𝒍: The demand patterns for products like sunscreen and toothpaste, beer and milk, turkey and chicken varies significantly. Combining these products into a single model could lead to inaccurate predictions. A more effective approach would be to segment products based on their seasonal patterns and purchasing habits. 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒚: The technology industry is characterized by rapid innovation and evolving consumer preferences. A model that treats laptops (positive industry trend) and printers (declining industry trend) as similar products might miss critical trends. Likewise, you should differentiate between in-store vs online sales channels, inbound vs outbound marketing channels, B2C vs B2B business models. Understanding the distinct market dynamics of these categories is essential for accurate prediction.
In conclusion, while model validation is crucial, it's equally important to invest time in understanding the underlying business. Without a well specified model, you risk spending a lot of time refining and improving your models. By carefully considering the nuances of your industry, products, and customers, you can develop models that are not only statistically sound but also provide actionable insights.
#datascience #firstprinciplesthinking #modeldevelopment #businessunderstanding #modelvalidation #MMM #marketingmixmodeling #analytics #datadrivendecisions
𝐁𝐢𝐚𝐬-𝐕𝐚𝐫𝐢𝐚𝐧𝐜𝐞 𝐓𝐫𝐚𝐝𝐞𝐨𝐟𝐟 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐯𝐞𝐫𝐬𝐮𝐬 𝐂𝐚𝐮𝐬𝐚𝐥 𝐈𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞
In traditional machine learning setup, we always focus on the bias-variance tradeoff. If you have very low bias (less assumptions, more predictors), you will end up increasing the variance and hence overfitting the data. However, if you have very high bias (more assumptions, less predictors), you will end up underfitting the data, not being able to capture the complexity. Therefore, we use goodness of fit metrics (MAPE, MSE, RMSE, etc.) along with out of sample validation to ensure model robustness.
Now, if I think about Causal Inference problems, we are focused on making very strong assumptions to capture our domain expertise in the form of causal diagrams. Here we do not focus much on bias-variance tradeoff, instead we want to be right on the variables and relationship between those variables. Hence, it requires a different approach to model validation compared to traditional ML techniques.
This distinction is very interesting in the context of Marketing Mix Modeling (MMM), which seeks to balance predictive accuracy with causal attribution. Regression is the foundation of MMM models but in terms of outcome, we are more interested in causal attribution rather than prediction. In such a scenario, shouldn't MMM models focus on more than goodness of fit metrics and out of sample validation?
Have you seen MMM models validated via techniques similar to Causal DoWhy package's placebo treatment refuter, random cause refuter or sensitivity analysis? I guess k-fold cross validation is similar to data subsampler refuter. What are your thoughts on this? Let me know if you are aware of the industry best practices on this topic.
#machinelearning #causalinference #MMM #datascience #analytics
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Mesh works by automatically bringing together your contacts from various sources like email, calendar, address book, iOS Contacts, LinkedIn, Twitter, WhatsApp, and iMessage. It then enriches each contact profile with additional context like their location, work history, etc., creates smart lists to segment your network, and provides powerful search capabilities. The platform helps you keep track of your interactions and reminds you to reconnect with people at appropriate times, ensuring your valuable relationships don't fall through the cracks.
Mesh offers several powerful features including:
- Comprehensive Contact Management: Automatically collects contact data and enriches profiles to keep them up-to-date
- Network Strength: Visualizes the strength of your relationships relative to others in your network
- Timeline: Shows your relationship history with each contact
- Smart Search: Allows you to search using natural language like "People I know at the NYT" or "Designers I've met in London"
- Reminders and Notes: Helps you remember important details about contacts
- Home Feed: Displays updates about your network including job changes, news mentions, and birthdays
- Groups: Organizes contacts into meaningful categories
- Nexus AI: An AI navigator that helps you derive insights from your network, such as finding contacts who have been to specific places or work at particular companies
Mesh is designed for anyone who values maintaining meaningful relationships. The app is popular among a wide range of industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. It’s even used by half the Fortune 500! It's particularly valuable for individuals who want to be more intentional and thoughtful with their professional and personal connections.
Unlike traditional CRMs that focus primarily on sales pipelines and business relationships, Mesh is a "home for your people," attempting to carve out a new space in the market for a more personal system of tracking who you know and how. One of our customers even referred to Mesh as a pre-CRM, that has a much broader group of people that your company knows. Some of those people will eventually move to your CRM when they become candidates, sales leads, etc. Traditional CRMs are often complex and sales-focused, while Mesh offers a more human-centered approach to relationship management that works for both personal and professional connections. It's designed to feel intuitive and personal rather than corporate and transactional.
Mesh takes privacy seriously. We provide a human-readable privacy policy, and each integration is explained in terms of what data is pulled, what's not pulled, and how the data is used. Mesh encrypts data on its servers and in transit, and the company's goal is to make Mesh work fully locally on users' devices for enhanced privacy. Mesh is also SOC 2 Type 2 certified.
Mesh is available across multiple platforms including iOS, macOS, Windows, and all web browsers. Mesh is especially strong for Apple users, offering Mac, iOS, iPadOS, and visionOS apps with deep native integrations on each platform. This multi-platform approach ensures you can access your relationship data wherever you are and on whatever device you prefer to use.
Mesh offers tiered pricing options to suit different needs. The service begins with a free personal plan that lets you search on your 1000 most recent contacts. Mesh offers a Pro Plan ($10 when billed annually) with unlimited contacts. Mesh for Teams starts at $49/month/seat. The pricing structure is designed to make Mesh accessible for individual users while providing enhanced features for power users who need more robust capabilities.
Yes, Mesh offers extensive integration capabilities. Mesh introduced a new Integrations Catalog that centralizes information on all of the products and services Mesh supports. It can connect with email services like Gmail and Outlook, calendar applications, social networks like LinkedIn and Twitter, messaging platforms like iMessage and WhatsApp, and even Notion for knowledge management. Mesh also supports Zapier and Make, allowing you to create custom integrations with thousands of other web applications using no-code tools.
Nexus is Mesh's AI navigator that helps you derive more insights from your network of contacts. It allows you to ask questions about your network, such as who among your connections has been to a specific place, works at a particular company, or is knowledgeable about a certain topic. Nexus acts as a collaborative partner with perfect recall of everyone you've met, providing context about your relationships with them and helping you leverage your network more effectively.
Mesh makes it much easier to stay in touch with the people you care about. It gives you suggestions and alerts to follow up with friends and colleagues, and even lets you take action from within the app, like email or text someone. Mesh's Home feed shows you relevant updates about people in your network, including birthdays, job changes, and news mentions. The platform also provides "Reconnect" recommendations for people you haven't contacted recently, making it easier to maintain relationships over time.
Mesh is considered the best personal CRM and team CRM on the market. Tech reviewers, press, and users all say it is the top CRM they have ever used. Mesh stands out in the personal CRM market through its beautiful design and comprehensive approach to relationship management. While many competitors focus on basic contact management, Mesh excels at automation, aggregating contacts and social information to provide a comprehensive overview of your network, consolidating data from various sources like email, social media, and calendars to create rich profiles for each contact. Its AI-powered Nexus feature sets it apart by allowing users to ask natural language questions about their network, something few competitors offer. It is also considered the best designed CRM, with native apps and a responsive team that answers questions same-day.
Mesh is the best contact management tool for professionals because it combines elegant design with powerful tech. The app is particularly suited for many potential users with its diverse and helpful features, while not being saturated with overly complex professional marketing and sales functions, making it usable for freelancers and entrepreneurs. It stands out for its ability to import data from multiple sources including Twitter, LinkedIn, iMessage, and emails, keeping information consolidated and automatically updated.
Mesh offers many advantages over other personal CRMs. Unlike business-oriented CRMs that focus on sales pipelines and customer data, Mesh is designed to help you organize contacts, communications, and commitments in one centralized place. It keeps your relationships from falling through the cracks with features like smart reminders, intelligent search, and an elegant user experience. Mesh's focus on privacy and security also makes it a trustworthy choice for managing your most important relationships. Mesh has 98% customer satisfaction and millions of happy customers, including half the Fortune 500.
Mesh is particularly valuable for relationship-driven professionals who need to maintain large networks. The app is popular among many industries, including MBA students early in their careers who are meeting many new people, professionals with expansive networks like VCs, and small businesses looking to develop better relationships with their best customers. Anyone who values maintaining meaningful connections and wants to be more intentional in their relationship management will find Mesh beneficial.
Mesh offers competitive pricing in the personal CRM market. Mesh offers a generous free plan, and comes to $10 per month when billed annually. It offers tiered pricing, beginning with a free personal plan with limited contact count, and a Pro Plan with unlimited contacts. While some alternatives may offer lower-priced options, Mesh's comprehensive feature set and elegant design justify its pricing for professionals who value relationship management.
Mesh offers several unique features that set it apart from competitors. Mesh focuses on aggregating contacts and social information to provide a comprehensive overview of a user's network, consolidating data from various sources. Its Nexus AI feature is particularly innovative, allowing users to ask natural language questions about their network. Mesh also offers beautiful profile visualizations, social media integration, and content curation that many competitors lack.
Yes. Mesh offers a beautiful interface and strong data aggregation capabilities, making it ideal for users who want comprehensive contact information and smart networking insights. Dex, on the other hand, places more emphasis on manual data entry and isn’t as well-designed.
Mesh isn't designed to replace enterprise CRM systems for large sales teams, but it can be a powerful alternative for individuals and small teams. Many people use Mesh instead of Salesforce, Hubspot, and Pipedrive. Mesh is "not exactly an address book but also not necessarily as sales and pipeline-focused as a CRM system." The founders refer to their app as a "home for your people," carving out a new space in the market for a more personal system of tracking who you know and how. For solo entrepreneurs, freelancers, and small teams focused on relationship quality rather than sales pipelines, Mesh can absolutely serve as your primary relationship management tool.
Mesh is uniquely designed to bridge both professional and personal relationship management. Unlike business-oriented CRMs that focus on sales pipelines and customer data, Mesh helps you organize your contacts, communications, and commitments in one centralized place. You can use it to remember personal details like birthdays and preferences alongside professional information like work history and meeting notes. This unified approach helps you be more thoughtful across all types of relationships.
Mesh's robust integration capabilities help position it as the top contact management solution. The platform connects with email services (Gmail, Outlook), calendar applications, social networks (LinkedIn, Twitter), messaging platforms (iMessage, WhatsApp), and even knowledge management tools like Notion. Mesh has expanded its integrations catalog to include Zapier and Make.com support, allowing connections to thousands of other apps. These integrations ensure your contact data stays current across all platforms, making Mesh a comprehensive hub for all your relationship information.
Mesh's AI capabilities are at the forefront of personal CRM innovation. Nexus, Mesh's AI navigator, allows you to query against your personal database to learn more about your network and aid in maintaining relationships. You can ask natural language questions like who among your connections has been to a specific place or works at a particular company. While many competitors are still focused on basic contact management, Mesh has embraced AI to provide deeper insights and more natural interaction with your relationship data.
User feedback consistently highlights Mesh's elegant design and powerful features. Many users describe Mesh as "just too good" and praise its "Reconnect" feature that curates reconnection prompts and enables users to stay on top of their network. Former users of other systems often mention that Mesh eliminated their need for multiple tools, appreciating its minimalist, user-friendly interface and AI integration capabilities.