5   Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions   Profitable Multi Channel Marketing   March 2010
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5 Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions Profitable Multi Channel Marketing March 2010

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Collecting, analysing and using multi-channel data to make better marketing decisions....

Collecting, analysing and using multi-channel data to make better marketing decisions.
Methods of collecting data and the process of analysing data to create actionable information about how your marketing budget could and should be allocated.

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  • Urchin will allow you to use regular expressions as wildcards so you can be more flexible in defining goal paths. For example, you have 5 pages in your / products / directory. You want the second page in the goal path to be 1 of 3 pages out of the total 5. The other 2 should not be included. So, the path you want visitors to follow looks like this: Page 1= /index.html The home page Page 2= /products/shoes.html shoe shopping page Page 2=/products/shirts.html shirt shopping page Page 2= /products/hats.html hat shopping page (don’t want to include /products/ties.html or /products/coats.html) Page 3= /cart/checkout.php purchase page Goal= /cart/thankyou.html Thank you Since page 2 can be one of 3 pages but can’t include 2 other similar pages, you must use a regular expression that matches all 3 but excludes the other two when creating the second step in the goal path. This cannot be done using the wizard; you write this directly into the Web Addresses box. Step 1: /index.html Step 2: /products/(shoes|shirts|hats).html Step3: /cart/checkout.php Goal: /cart/thankyou.html
  • [Notes to presenter: Describe the goal and funnel report in Google Analytics.] In the Funnel Visualization Report, the centermost column of boxes represent the steps in one of your defined goal funnels. Shown within each box is the percentage of visitors still in the defined funnel at each step. Shown at right, under Abandonment Points, are the visitors who abandoned the funnel and where they went. Shown at left are the Entrance Points, points from which visitors arrive to the funnel. Google Analytics’ Funnel Visualization Reports give you information to help you figure out the answers to the questions on the bottom right.

5   Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions   Profitable Multi Channel Marketing   March 2010 5 Collecting, Analysing And Using Multi Channel Data To Make Better Marketing Decisions Profitable Multi Channel Marketing March 2010 Presentation Transcript

  • Collecting, analysing and using multi-channel data to make better marketing decisions
  • We’ll cover
    • The multi-channel business
    • What to collect
    • How to collect
    • The analysis process
    • The decisions we can make
  • The catalogue business Housefile Mailings Requester Mailings Database Purchases Order Data Catalogue Requests Space Ads Card Decks Lists OTP Inserts View slide
  • The catalogue and retail business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Purchases Order Data Order Data Lists OTP Inserts View slide
  • The multi-channel business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases E-mail Programme Home Shopping Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Web
    • Natural Search
    • Paid Search
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Orders Purchases Order Data Order Data Order Data Lists OTP Inserts
  • The integrated multi-channel business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases E-mail Programme Home Shopping Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Web
    • - Search Engines
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Orders Purchases Retail Mailings Order Data E-mail Programme Retail
    • Natural Search
    • Paid Search
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Lists OTP Inserts
  • The integrated multi-channel business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases E-mail Programme Home Shopping Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Web
    • - Search Engines
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Orders Purchases Retail Mailings Order Data E-mail Programme Retail
    • Natural Search
    • Paid Search
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Lists OTP Inserts
  • What to collect
    • The challenge
      • Profiling customer behaviour based on transactional data
  • What to collect Customer Record Name, Address, Email, Transaction history, Mailing preferences
  • What to collect Transaction Record Value, Shipping, Tax, Date, Item lines, Product (SKU), Quantity, Price, Channel, Source Customer Record Name, Address, Email, Transaction history, Mailing preferences
  • What to collect Transaction Record Value, Shipping, Tax, Date, Item lines, Product (SKU), Quantity, Price, Channel, Source Customer Record Name, Address, Email, Transaction history, Mailing preferences Marketing Record Source, Channel, Date, Promotion
  • What to collect Transaction Record Value, Shipping, Tax, Date, Item lines, Product (SKU), Quantity, Price, Channel, Source Customer Record Name, Address, Email, Transaction history, Mailing preferences Marketing Record Source, Channel, Date, Promotion
  • How to collect
    • Channel by channel
  • The catalogue business Housefile Mailings Requester Mailings Database Purchases Order Data Catalogue Requests Space Ads Card Decks Lists OTP Inserts
  • How to collect
    • The call centre
      • Diligent capture
    • Mail order
      • Order form capture
  • The catalogue business Housefile Mailings Requester Mailings Database Purchases Order Data Catalogue Requests Space Ads Card Decks Lists OTP Inserts
  • The catalogue and retail business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Purchases Order Data Order Data Lists OTP Inserts
  • How to collect
    • A loyalty card
      • At point of sale
    • Customer details capture
      • At point of sale
    • Or match-back transactions
      • A dinning table was ordered in-store
      • To an address for delivery
      • Has the address received a catalogue?
      • Is there a correlation between the catalogue mailing and the retail order and can we therefore attribute a marketing source?
  • The catalogue and retail business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Purchases Order Data Order Data Lists OTP Inserts
  • The multi-channel business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases E-mail Programme Home Shopping Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Web
    • Natural Search
    • Paid Search
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Orders Purchases Order Data Order Data Order Data Lists OTP Inserts
  • How to collect
    • Web Analytics tracking
      • Google Analytics
        • On-line traffic source
        • Multi-channel source
        • Off-line traffic source
  • How to collect
  • How to collect
    • www.actionaid.org.uk/sponsor
      • http://www.actionaid.org.uk/sponsor?utm_source=tube&utm_medium=outdoor&utm_campaign=ad1
    • www.actionaid.org.uk/child
      • http://www.actionaid.org.uk/sponsor?utm_source=bus&utm_medium=outdoor&utm_campaign=ad2
    • QR (Quick Response Codes)
  • The multi-channel business Catalogue Requests Housefile Mailings Requester Mailings Database Purchases E-mail Programme Home Shopping Retail Space Ads
    • - Walk Bys
    • - PR
    • Recommended
    • Thin Air
    Web
    • Natural Search
    • Paid Search
    • - Online Ads
    • Affiliates
    • Thin Air
    • PR
    Orders Purchases Order Data Order Data Order Data Lists OTP Inserts
  • What’s possible with Web Analytics
    • How visitors found your web site
    • What visitors are doing on your web site
    • Not WHY they are doing it!
      • Domain of usability/customer experience
        • Onsite surveys
          • Sampling visitors arriving/leaving
          • 4Q
        • Heuristic reviews
          • Experts reviewing your site against a set of criteria (heuristics)
        • Conversion Rate Optimisation
          • A/B testing
          • A/B/n testing
          • Multi-variate testing
          • Google Website Optimiser
          • Clicktale
          • Crazy Egg
        • Usability tests
          • Representative customers completing tasks
            • Usertesting.com
            • Whatuserdo.com
  • What’s possible with GA?
    • How visitors found your website
    • What visitors are doing on your website
      • Not why !
    • Outcomes focused
      • Goals
  • Goals
    • Goals should be commercial
      • The commercial goals of your website
    • Goals should map to visitor tasks
      • Visitors visit sites to accomplish tasks
    • Tasks normally have a series of steps
      • Funnel
      • Measure conversion through the task
    • When goals match user tasks
      • Harmony ensues!
  • The importance of goals for you
    • Commercially justify your work
    • Focus your work
    • Prioritise your work
  • The importance of goals for you
    • Goals map to business metrics
      • Enable you to build a business case for
        • Analytics investment
        • Analysis investment
        • Action investment
    • Goals focus on important paths and entrances
      • Enable you to home-in on problem areas
        • Reverse Goal Path
        • Conversion to goals by traffic source
    • Monetize goals
      • Enable you to prioritise areas to analyse and optimise
        • Give goals a goal value
        • Analyse $ Index
          • (Goal Value + E-commerce value)/unique page views
          • Page up-to goal contribution
          • Focus on high $ Index pages for improvement
    • You can use Regular Expressions (RegEx) to gain insight into the funnel path:
    • User exhibits behavior:
      • Page 1 = /index.html
      • Page 2 = /category-footwear.html
      • Page 3 = /category-clothing.html
      • Page 4 = /category-headwear.html
      • Page 5 = /products/kangol-tropic-player-trilby.html
      • Page 6= /cart/basketview.html
      • Page 7= /cart/registration.html
      • Page 8 = /cart/paymentoptions.html
      • Goal = /cart/salesorderconfirmation.html
    • Need to know conversion rate of categories to products to purchase:
      • Step 1: index.html
      • Step 2-4: ^/category.*/
      • Step 5: ^/products.*/
      • Step 6: ^/cart/basketview.html
      • Step 7: ^/cart/registration.html
      • Step 8 : ^/cart/paymentoptions.html
      • Goal: ^/cart/salesorderconfirmation.html
    Goals and funnels
  • Goal and funnel behavior
  • Don’t stop at transactions!
    • Goals (with source)
      • Request a catalogue
      • E-newsletter registrations
      • Send to a friend
  • The analysis process
    • Matching back
    • Recency
    • Frequency
    • Monetary
    • Deeper insight
    • Continuous insight
  • The analysis process
    • Matching back to source
      • Channel is always known
      • Source, is often absent in data capture, so requires
        • Correlations between source marketing and transactions
        • To make good assumptions about source of transaction
  • The analysis process
    • Recency
      • Take the most recent discretionary purchase date
      • Sort by that date and the top 20% (in terms of recency) is given a code of "5".
      • The next 20% in terms of recent purchases is coded as "4", etc.
      • Everyone in the database now is either a 5, 4, 3, 2, or 1 in terms of recency.
      • If you now make a test promotion to a representative sample, you will get a response that looks like this:
  • Recency
    • Recency is the number one most powerful predictor of future behaviour
    • Recency is also the most powerful predictor of a customer response to a promotion
    • The more recent a customer is
      • the higher their potential value
    • This is a marketing “constant”
  • Recency decisions (dead certs)
    • Use transaction emails to invoke similar behaviour
      • Promote in high-rate (double) opening email such as:
        • Thank you for your order
        • Your order has been despatched
    • Template emails to customers who purchased
      • 30, 60, 90, 180 and 365 days ago
      • Seasonal adjustments
      • Relevant promotions (RFM)
    • Announce catalogues dispatch/arrival with emails
      • 18% uplift in sales
  • The analysis process
    • Frequency
      • Using the number of transactions with your customers, code by frequency.
      • Sort the database from the most to least frequent, coding the top 20% as "5", and the less frequent quintiles as 4, 3, 2, and 1.
  • Frequency descisions
    • Frequency
      • Frequent buyers respond better than less frequent buyers, but the differences are much less pronounced than those for Recency
      • The lowest frequency quintile always contains the new customers – who are your best responders.
  • The analysis process
    • Monetary (with Frequency)
      • Code customers by the total value sales (average and highest by month, year, or since the beginning of time) giving the big spenders a "5", and the others, 4, 3, 2, and 1.
      • Life Cycle of a Customer
        • Define it by creating a start and end
        • From first order to last infrequent purchase
        • Account not just for sales but for profit
        • “ Net present value” of the customer base should be at the top of the measurement hierarchy
          • The profit over a period, discounted for the value of money
  • Monetary decisions
    • Monetary
      • When you do this, you may discover that your top 20% of your customers gives you 80% of your profits
      • You may also discover that you can't market profitably to these top customers,
        • so you must spend your efforts on service to prevent defections and market to the next tier down
  • Combining RFM to form segments
    • Which groups contribute most - and least
    555 111
  • Deeper Insight
    • Peeking in between the 555s and 111s
    • Asking questions
    • RFM segments and original source
      • What is the true cost of acquiring a customer?
      • What are our best (most profitable) recruitment sources?
    • RFM segments and sale behaviour
      • Are our sales attracting the right customer?
    • RFM segments and product offerings?
      • Do first products attract profitable customers?
    • RFM segments and promotions?
      • Do promotions attract profitable customers?
    • RFM segments and products and promotions on web pages?
      • Do first product purchases justify their web page position?
  • Continuous Insight
    • Turn analysis from a picture to movie
    • Continuous analysis
      • Analysis should NOT be an annual event
      • Continuous transactional data analysis builds most accurate predictive model
    • Analyse to understand channel overlap and identify source
      • To obtain real cost of customer acquisition
    • Monitoring Customer Life Cycle
      • Net present value of customer
      • Combine with source
        • Identify profitable recruitment methods
  • To summarise
    • Collect, analyse and use transactional data to learn
    • How best to apportion marketing spend across
      • Active customers
      • Inactive customers
      • New customer acquisition
    • Through which marketing source mix
    • “ If you allocate money away from activities generating low potential value customers, and allocate this money to activities generating higher potential value customers, you will become more profitable over time.”
    • -Jim Novo
  • Tools and resources
    • http://www.dbmarketing.com
      • Books and spreadsheets
    • http://www.jimnovo.com
      • Books, spreadsheets and software
    • http://www.google.com/analytics
      • Free Web Analytics