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Ambit Energy Alteryx User Cases


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Ambit Energy describes how they use Alteryx for creating probability of attrition models, adhere to regulatory document reporting requirements, and customer survey analytics.

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Ambit Energy Alteryx User Cases

  1. 1. Ambit Energy Alteryx User Cases Alteryx Roadshow July 23, 2015
  2. 2. Ambit Energy Analytics Team Organizational Relationships Customer Experience Commercial Sales Marketing Operations Consultant Support BI / IT Product Mgmt Analytics
  3. 3. 1. Better Company 2. Better Client 3. Better Process Three Business Cases with Three Different Alteryx Solutions:
  4. 4. Probability of Attrition Model (Better Company)
  5. 5. Probability of Attrition (PAT) Model PAT Model • Scores customers on a % scale of likelihood to leave us, so we can intercept the more valuable ones before they leave, via offers or promotions. • Program created in 2011 and structured in a way that is not scalable, manageable, visible and has gone stale to the point to where no one wants to use the output or touch the process
  6. 6. Original PAT Model Process SQL SQL Base data CRM schema 1. In 2011, one-off coefficient exercise created in SAS 2. Results are embedded back into a SQL database as a lookup table in the CRM schema 3. Lookup table is then referenced in a nightly job that calculates the Probability of Attrition score for each customer and stores that data in the CRM schema Lookup Table
  7. 7. Alteryx Creates Better Visibility, Manageability, and Quality Challenges of Existing Solution • Engineered to produce result with least work; details at customer level not practical or visible • Gathering and computing coefficients became a “black box” when person who created it left the company; algorithm difficult to refresh • Inflexibility of process to evaluate other models or go beyond the base data for better variables Benefits of Alteryx Solution • Short refresh exercise and quick tweaks for base data changes • Invites improvement and expansion through rapid development cycle • Customer detail feed to Tableau for richer insights
  8. 8. New PAT Model Process 1. 28 step Alteryx process to produce 100,000 clean customer records 2. Run clean customer list through predictive models to create new variables to populate CRM lookup table 3. Validate new model against old model
  9. 9. Ad-Hoc Regulatory Document Report (Better Client)
  10. 10. Ad-Hoc Regulatory Document Report Business Case • New Connecticut regulatory rules required new documents to be sent to customers prior to their contract expiring • Requirements for new documents are complex and require the analytics team to work very closely with the business unit to assure accuracy Challenges of Non-Alteryx Solution • All business requirements rolled up in a large SQL stored procedure • Client does not understand SQL and does not have direct visibility into how each data requirement impacts the dataset • Results in ongoing code changes and modifications to satisfy the client
  11. 11. Ad-Hoc Regulatory Document Report Process SQL 1. Pull customer data components from SQL server and run through Alteryx to perform ETL, data extraction, prep/transformation and output/load 2. Process results displayed in Tableau for business client to review 3. SQL table created from Alteryx, creating the mail merge file Base data 4. Mail merge data relays to Pitney Bowes process for final output of documents to be mailed to customers
  12. 12. Alteryx and SQL, Together in Harmony
  13. 13. Customer Survey Updates (Better Process)
  14. 14. Ambit Energy Customer Surveys • Ambit Energy has been using customer surveys since 2013 to gauge overall customer sentiment and gain deeper understanding of customer behaviors • Net Promoter Score • Customer Effort Score • Customer Satisfaction Score • Measure call center agent performance • Hold time impact on customer satisfaction and effort • Deep dive analysis on what makes a customer happy • Develop baseline for predicting customer behavior • Customer journey mapping Analyses produced using customer survey data:
  15. 15. Ambit Energy Surveys and Data Sources 15 Customer Satisfaction Survey Defector Survey Post Call Email Survey Post Call IVR Survey Survey Name Data Source Data Output Qualtrics Survey Portal Tamer Survey Portal Ambit Databases
  16. 16. Old Data Update Process Total Time: 6 to 8 Hours 16 2. Lots of spreadsheet updates, formatting and manipulation, append customer information & validation Approximate Time: 4-5 hours 3. Create tables in SQL database and validate data Approximate Time: 1-2 hours 1. Download Data Approximate Time: 15-30 minutes 4. Update and validate Tableau dashboards Approximate Time: 10-20 minutes
  17. 17. New Data Update Process With Alteryx ryx Total Time: 35 to 60 Minutes 17 2. Using Alteryx, format and manipulate data, append customer information, data validation and create tables in SQL database Approximate Time: 7-10 minutes 1. Download Data Approximate Time: 15-30 minutes 3. Update and validate Tableau dashboards Approximate Time: 10-20 minutes
  18. 18. 1. Better Company 2. Better Client 3. Better Process