Ambit Energy Alteryx User Cases
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Transcript of Ambit Energy Alteryx User Cases
Ambit Energy Alteryx User Cases
Alteryx RoadshowJuly 23, 2015
Ambit Energy Analytics Team Organizational
Relationships
Customer Experience
CommercialSales
Marketing
Operations ConsultantSupport
BI / IT
Product Mgmt
Analytics
1. Better Company
2. Better Client
3. Better Process
Three Business Cases with Three
Different Alteryx Solutions:
Probability of Attrition Model
(Better Company)
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
Original PAT Model Process
SQL SQL
Base
dataCRM
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
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
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
Ad-Hoc Regulatory Document
Report
(Better Client)
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
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
Alteryx and SQL, Together in Harmony
Customer Survey Updates
(Better Process)
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:
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
Old Data Update ProcessTotal 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
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 databaseApproximate Time: 7-10 minutes
1. Download Data Approximate Time: 15-30 minutes
3. Update and validate Tableau dashboardsApproximate Time: 10-20 minutes
1. Better Company
2. Better Client
3. Better Process