managing-marketing-metrics

Managing Marketing Metrics at Intuit [video]

“The difference between twelve months and thirteen months is going from idiocy to brilliance, because you have that year-over-year trend.”

Quicken and Mint work towards a vision of optimizing how people handle their finances. Intuit has a healthy dissatisfaction with the status-quo. They are continuously improving everything by using analytics to make the process better. There are 120 Data Analyst jobs open at Intuit right now.

The role of the analytics team is to:

  • Optimize the site experience
  • Increase conversion
  • Drive customer acquisition
  • Help Intuit get better through testing

George Roumeliotis is in the Business Intelligence and Optimization (BIO) team. Dylan Lewis is in the Consumer Group, which includes Quicken and Mint.
Lewis is concerned with business limitations, while the BIO group is focused on techniques that they can apply to collected data. Together the two groups drive results, formulating hypotheses and deciding which questions to ask of the data.

What is a Successful Business Data Analyst?
Collaborates and influences to drive actions that impact revenue, units, or resource allocation.

The steps in analytics at Intuit:

  1. Create a learning plan for every program. What questions do you have and what metrics will you track against every question? Analysts and Product Managers (or Marketing Managers) need to have a close relationship in order to determine what analytics are important. Analysts and Product Managers need to feel that they are partners working towards the same goal. The learning plan helps create this partnership.
  2. Define the data. Every system needs to be understood. Analysts need to understand each system and know who owns it. It’s important to know where data can get stuck, and who can answer the questions. The layers are financial data, engineering logs, web analytics, customer surveys, and focus groups.
  3. Alert the business to opportunities.
  4. Experimentation. Use experiments to answer questions and add happy customers.

Dylan Lewis asks what a data scientist is. He says it’s a data analyst who lives in California. He describes the tools, from paper and pencil to advanced statistical analysis programs.

A Proven Data Science Project Methodology

  1. My understanding of the business problem
  2. How I will measure the business impact
  3. The available data, cleansed and documented
  4. The initial solution hypothesis
  5. The solution
  6. The business impact

It’s important to help customers effectively use the products, and it’s especially important for the customer to make it all the way through the free product in order to pay. Tiny reductions in abandonment rate are major financial gains.

For example, natural language processing is used to look at questions asked in the help in order to tell the teams which topics need to be addressed in order to help complete more tax forms using the form itself or the FAQ without additional help. They also want to predict abandonment by analyzing customer behavior, to offer instant help to customers in a course of imminent abandonment. They can also use this information to offer successful customers additional products.

Dylan Lewis, Group Manager, Web Measurement, Intuit

Dylan LewisDylan Lewis is currently the Group Manager, Web Measurement at Intuit. In his role, Dylan leads the TurboTax End-to-end measurement team. The team is focused on optimizing the TurboTax experience through analytics and experimentation. Dylan joined Intuit in 2005 after working at Visual Sciences. Prior to Visual Sciences, he worked at SmartDraw.com as the Director of Marketing. Dylan earned a bachelor’s degree in Psychology from UC Santa Cruz, and a master’s in Industrial Organizational psychology from San Diego State University.

George Roumeliotis, Leader of Analytics Engineering for Product Innovation, Intuit

George RoumeliotisDr. George Roumeliotis leads a team of Data Scientists at Intuit who develop advanced analytics algorithms that have been applied to everything from enabling new product features to optimizing internal business processes. Dr. Roumeliotis began his career as an Astrophysicist at Stanford University, before co-founding two venture-backed companies, in online marketing and supply chain optimization, respectively. He has been leading strategic initiatives that apply advanced analytics at Intuit for over three years.

Intuit has been a hotbed of analytical power for over ten years. It’s only logical that as company that makes a living with financial and tax preparation software should be numbers-oriented, but this group is serious data drive. Dylan and George describe their corporate culture and reveal some of the in-house analytics applications that optimize this well-known brand.