Getting More Out of Your Customer Data

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Getting More Out of Your Customer Data
Corey M. Ryan
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Getting More Out of Your Customer Data

• Background
• Obtaining Data
• Maintaining Data
• Using Data to Drive Incremental Profits
• Questions and Answers

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Corey M. Ryan

• Former Vail Resorts Director of Marketing
  Technology and Database Marketing
• Former Senior Manager Inforte Corporation CRM
  Practice
• Former Senior Consultant Andersen Consulting /
  Accenture

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Background

• Recently founded Ophrys, LLC
• A Marketing Technology firm focused on
• Building / Advising Marketing Technology
  Platforms
• Direct Marketing Strategy
• Campaign Management / Analysis
• Data Hygiene and Data Entry

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Why should we collect customer data?
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Why is it important to obtain data on our
customers?

• Your past guests are the keys to future
  profitability
• Limited Resort guests in the marketplace
• Intense competition
• They can act as your virtual sales force, if you
  treat them right

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Guests Expectation

• Consumers have a very loyal relationship with
  their preferred resort
• They expect timely and relevant communications
• High rollers want to be treated as such, they
  want to be part of a club
• You cant get away with a mailing list you need
  a database

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What types of data should we collect

• At first anything you can get
• Customer
• Demographic
• Behavioral
• Psychographic
• Preference

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Customer Data

• Get a complete name and mailing address
• Household information
• Email address
• Sourcing information

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Demographic Data

• Age
• Income
• Family Status
• Media Consumption

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Behavioral Data

• What did they buy?
• When did they buy it?
• How much did they pay?
• Where did they buy it?

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Psychographic

• What is their vacation planning process
• What do they look for in a resort?
• Where are they in their relationship with your
  properties?

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Preference

• What type of communications do they want to
  receive?
• How frequently should you communicate with them?
• What types of offers do they respond best to?
• Be aware of Privacy and Spam Laws
• Marketing expertise
• Legal review

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Obtaining the Customer Data
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• Marketings data collection efforts in conflict
  with operations goals
• Work together and develop common goals
• Share in the costs / rewards
• Fully leverage your technology

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Systems

• Point of Sale
• RPOS and RTPOne are optimized for data
  collection and profile development
• Track behavior to media / customer
• Household
• Address standardization
• Phonetic Matching and search
• Merge
• Inactivate
• Customized profiling
• Enterprise wide system

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Systems

• PMS and Central Reservations
• Most complete look at the vacation
• Arrival / Departure data
• Folio spending
• Source of Business tracking
• Requires a complete physical address
• Typically dated, Mainframe or AS400 applications
  that can be overly challenging to integrate
• Very difficult to customize
• Data is frequently horrific

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PMS Data some real examples

• FirstName Kelly noon checkout
• Address Line 1 AT CHECK IN SEE F11
• City Who knows?
• RPOS examples

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Surveys

• Best potential source for preference,
  psychographic and some demographic profiles
• Expectations of Anonymity
• Need a compelling prize
• Are you really getting your guests?
• Technology as an enabler and the destroyer

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Source Vignette Corporation Product Vignette
Dialog
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Loyalty Programs

• RTP is the recreation industry leader in design
  and implementation
• Determine the purpose before you begin
• Generate loyalty
• Populate your database
• Very few do both well

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Offline sources

• Legal Waivers
• Sweepstakes cards
• mounting/registration cards
• Partner data
• Inquiry fulfillment
• Tips and Tricks

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Storing and Maintaining Customer Data
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Can our OLTP system act as our DSS?

• What are Marketings needs?
• What are the available resources?
• What systems are involved?
• What is our risk tolerance?
• What is our budget?
• There is no right answer, every resort is
  different

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Common Requirements of a Marketing Database

• Ability to store and access thorough customer and
  behavioral profiles
• Ability to scale and handle large volumes of data
  movement
• Ability to enforce business rules and enact
  translations
• Ability to Integrate with multiple systems

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Integrating Your Data / Middleware

• Common Meta Data
• Matching
• Exact
• Phonetic
• Householding
• Address Standardization
• Database inter-connectivity

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Maintaining Your Data

• Data Quality is typically the hidden cost of any
  Marketing Database
• Data Quality ensures that your communication
  reaches your guest and contains accurate
  information
• Data Quality is necessary to support analysis and
  direct marketing strategy

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Cleansing Your Data

• Data gets old, quickly
• People Move (40 dont notify USPS)
• People change names
• People request removal
• People stop using your product
• People die

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Maintaining Your Data

• Cleanse your Data (2x year)
• Address Standardization
• NCOA / XCOA / DSF2 / LACS
• Household / Merge / Purge
• Privacy / Do Not Call
• Deceased Coding
• Real ROI comes from Clean data (VRI 20 - lt5)
  over time Millions of . Industry avg 23 not
  deliverable

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Other data hygiene considerations

• Clean it as it comes in
• Operationally or on imports
• Process returned mail and bounced emails
• Only send what you expect to reach the guests
  (including emails and bounce handling)

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Using your Data to talk to your guests
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Customer Acquisition and Retention Strategy
Customer Acquisition and Retention Strategy
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What should be done

• Know who your customer is
• Factor Analysis
• What attributes in our customer database our the
  best indicators of future behaviors
• Segmentation
• Segmenting a heterogeneous population into two or
  more homogenous groups
• How many like populations do we have (or want)
  in our database?
• Can be tactically executed on in marketing or
  operations

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Apply your data to your marketing efforts

• All guests are not alike, stop talking to them as
  if they were
• Should High Rollers get Ski Free Stay Free ?
• Should Gen Xers get the Slopeside Penthouse
• One to One Marketing does not have to be one to
  one
• Personalize the Communication!

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Test, Test and Test Some More

• Create an actionable testing strategy
• Ensure that the results are measurable (mailing
  list vs. customer database)
• Understand Test vs. Control methodology and
  ensure statistical validity

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What should we test

• Segmentation
• Product Mix
• Offer(s)
• Investment
• Timing
• Channel
• Frequency of Contact

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What / How Should We Analyze

• Incrementality ONLY
• Incremental Response Rate
• Incremental Spend / Respondent
• Incremental Spend / Recipient
• Statistically relevant results
• Database Tracking vs. Phone Logs
• Carefully and Directionally

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Create a database marketing methodology

• Hypothesize, plan, test, analyze, refine
• Incremental profitability comes from
  understanding who NOT to market to and how to
  BETTER market to others
• There is significant profit, but it comes in time
  
• Hire an expert, third-party for consultation or
  outsourcing

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Next Steps

• Begin to collect data
• Inventory data quantity and quality
• Put collection and hygiene procedures in place
• Develop a data strategy
• Develop a database marketing strategy
• Plan and build the infrastructure

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Questions?
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Contact Information

• Corey M. Ryan
• Corey_at_OphrysLLC.com
• 970.376.1724