ANISHA VENKATESH

foundational analyses

density forecasts

• Working with a team of analysts provided comprehensive analysis and recommended solutions to address complex issue of declining stores traffic by examining shifts in customer channel preference post pandemic, impacts of reducing direct mail coupons and high attrition rate of recently acquired customers
• With the same team conducted another in depth exploration to understand the cause and recommend solutions for declining email engagement
• Developed media mix model using geo level Bayesian hierarchical modelling to attribute sales to various marketing channels and calculate ROAS
• Analyzed and reported on market intelligence from several external sources like NPD, iRi, Numerator among others by developing robust data pipelines and intuitive dashboards to report on market shares and assess factors impacting growth and profitability across key product categories and brands
• Also provided comprehensive analysis around impact of permanent store closures on the retailer's market share using advanced analytical methods
• Developed a thorough report for the Executives which established strong correlations between declining sales and a drastic reduction in direct mail coupons with recommendations on reinstating coupons in a more targeted manner
• Led a team of 3 analysts to develop "Coupon Playbook" compiled as a set of learnings on various couponing strategies such as different offer types, effect on customer acquisition and retention, effects of creative testing on different channels and customer behavior wrt medium of coupons
• Utilized advanced querying and statistical methods along with visualization tools to develop a dashboard to measure incremental sales from everyday marketing promotions in absence of proper control measures
• Created and cultivated test and learn culture among CRM and digitization groups, creating and executing structured experimentations based on data-driven and market ideas.
• Coached, developed and motivated team members and mentored junior analysts and data scientists on SQL, SAS and data mining techniques

• Worked as a part of the personalization lab which was a cross functional agile team executing multiple personalized marketing campaigns at scale in a test and learn format where my duties included identifying the appropriate audience and measuring the results of various A/B tests and use quantitative methods to perform deeper analysis and provide key insights to the rest of the team
• Using methods like market basket analysis and detailed exploratory data analysis into customer spending behavior, helped in creating personalized content tailored to a customer’s preferences and life stage
• Determined the ideal no mail control sample size using a Power analysis to measure true incremental sales from mailing a monthly coupon mailer
• Developed a model to predict the likelihood of a customer to respond to a BBB promotional catalog using a combination of logistic regression and decision trees
• Developed a churn/attrition model to predict attrition of loyal customers using a Pareto/ NBD methodology
• Created the entire data framework to scale the successful personalized campaigns which are projected to add incremental sales of $20M annually
• Identified retroactive controls using advanced statistical methods to match campaign customers in order to measure incremental sales
• Performed various other analysis to understand profitability of loyalty program using artificial controls, understand the factors for same store decline and calculate incremental sales from monthly catalogs
• Performed multiple hypothesis testing with marketing campaigns starting from properly designing the experiment to using statistical techniques to measure KPIs and provide insights to the business

• As a part of Global Data Insights and Analytics team, my projects included:
• Building and maintaining sales and service retention model which scores all the consumer households based on their probability to purchase/ repurchase a vehicle
• Building and regularly upgrading customer service propensity models which predicts the likelihood of customers bringing in their
• Ford vehicle for a service and also the propensity to service for a specific commodity
• Working with customer Lifetime Value models which predicts the probability and value of a three year revenue stream at a consumer and household level
• Forecasting the quarterly sales of major aftermarket parts at Ford dealerships using time series analysis like exponential smoothing and ARIMA to set targets and incentives for various dealer based marketing campaigns
• Working on text mining projects which included developing a Sentiment Analysis model in R to identify positive and negative consumer sentiment around vehicle experience and dealer experience using a machine learning algorithm to train the Naive Bayes classifier
• Created a rule based model with over 400 different categories to classify text documents into various vehicle components and corresponding malfunctions using intricate and precise business rules for text mining data sources like customer surveys, dealer experience surveys, call center data, prototype pilot test drive data, warranty repair claims etc
• Assisted in developing a scoring model for testing the precision and recall of the text mining model
• Analyzing the customer service segment migration patterns to identify various trends of loyalty and defection and underlying causalities if any
• Analyzed various marketing campaigns to determine if they produced an incremental lift in average customer spending at the dealership or an increase in monthly traffic
• Produced regular and ad hoc reports analyzing and summarizing the aftermarket sales and service data to determine performance trends and market penetration of various parts and commodities across multiple regions
• Developed a dashboard for determining potential market opportunities from multiple Ford service channels and to measure dealer performance in terms of monthly financials and customer traffic counts for different Ford vehicles and part brands
• Helped identify gaps in database due to keen observational skills and attention to details, thereby creating a more robust system

• Responsible for the monthly planning, scheduling & procurement of various automotive parts
• Analyzed production schedule and determine monthly supply planning while accounting for existing inventory levels and buffer quantities
• Reporting of supply chain performance metrics which included inventory levels, schedule adherence, internal customer satisfaction etc
• And responsible for the inventory asset management system
• Developed the pricing for indirect part purchases using cost models by analyzing material costs, labor, transportation and overhead costs
• Also maintained existing cost models for other similar parts
• Developed an intuitive GUI using VBA for entering the defect data of a vehicle as a quality control measure and integrated it with
• Rockwell Automation software
• Programmed PLCs used for shop floor automation using ladder logic algorithms