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The Data People
 

The Data People

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An introduction to The Data People

An introduction to The Data People

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    The Data People The Data People Presentation Transcript

    • All Customers Are Not Equal
      ‘‘
      80% of sales or
      profit will come
      from 20% of
      customers
      ’’
    • What We Do
      We identify Your Best Customers
    • We Build Detailed Pictures of Your Best Customers
      Profitability
      Attitudes
      Demographics
      Lifestyle
      Location
      Usage
      A Marriage of all the Elements
    • Your Best Customers Online
      Combining online and offline data
    • How We Do It
      data
    • Data Interpretation
      What Is Your Data Telling You?
      We will audit your current data and create interpretation from it
      • this often starts with the basics of quality and quantity
      • turning your data into timely, relevant and meaningful information
      • turning that information into marketing advantage
      • Helping you ‘see the wood for the trees’
      data
    • Data Analytics
      What could your data be telling you?
      We will undertake analysis on your data to build a fuller picture. For example:
      Basket analysis - identifies products likely to be purchased together, usually for cross-selling
      Propensity models - help maximise Return on Investment (ROI) by targeting the most suitable audience
      Churn modelling - predicting the likelihood to lapse
      Lifetime value - quantifies the overall value of each customer at a revenue, gross or net profit level
    • Data Strategy
      What will your data allow you to do?
      We develop data led business and marketing strategies to maximise business growth
      • CRM, Acquisition & Retention Strategies
      • Cross-sell & Up-sell Strategies
      • Data Collection & Data Partnerships Strategies
      • Creative Testing & Message Hierarchies
    • Data Planning Process
      short. medium and long term needs
      data
      systems
      business, marketing and communications objectives
      accuracy
      data
      usage
      roi
      audit
      evaluation
      data
      collection
      retention
      lapse
      data
      analysis
      hygiene
      strategy
      acquisition
      trial
      data
      quality
      crm
      data
      enhancing
      analysis
      database
      single
      customer
      view
      predictive
      models
      data:
      profile,
      cluster,
      segment
      data
      needs
      admin &
      reports
      build
      strategy
      future
      proofing
      define
      the objectives
      define
      the problem
    • What We Manage
      Through a network of third party partners we will source and manage
      Data Enhancement
      Data Cleaning
      Database Design & Build
      List Purchase
      Data Collection
      Processing Data
      Data Monetisation
      Web Analytics
    • Who We Are
      A data planning & analytics consultancy
      Based in Yorkshire
      5 core team members with a network of associate consultants & partners
      Working in the private and public sectors
      Part of the Journey Group
    • Peter Rivett-Jones - Director
      20 years of data and marketing experience
      Senior client services and planning positions in top DM agencies including Joshua, GGT Direct & EWA
      Founded DM agency Made With Love (MWL) in 1999 which was later sold to Chemistry in 2003
      Joined Poulters as Director & Shareholder in 2005 heading up all data and direct marketing accounts
      Co-founded The Data People in 2009
    • Steve Raper - Director
      A statistician with 25 years of data analysis and marketing experience
      Started career with British Gas in various sales and marketing positions
      Went agency side in 1994 as Data Manager for Bedrock Communications
      independent consultant since 1996 providing data strategy & data analysis for agencies and clients
      Co-founded The Data People in 2009
    • What Makes Us Different?
      • We are marketeers first and data planners second
      • We turn numbers into words and pictures.
      • We answer the "so what?" of data and statistics
      • We have vast experience in data and all its touch points
      • We are independent consultants with nothing to sell apart from our time
      • We turn the complexity of data into strategies that make sense
      • We champion simplicity
    • Sector Experience
      • NHS & Health
      • FMCG
      • Automotive
      • Industrial
      • B2B
      • Travel & Tourism
      • Airlines
      • Government
      Retail
      Leisure
      Office Equipment
      Telecoms
      Financial Services
      Mail Order
      Utilities
      Drinks
    • Case Study 1
      Alliance & Leicester
    • The Brief
      Alliance & Leicester had been using cold contact lists to direct potential customers to their web site, with limited success
      Registered users of the site were segmented by answers to basic financial questions only upon registration
      Communications to registered users had minimal tailoring
      With results from nearly 2 years’ activity now available, our brief was to optimise results –
      Increase visits to the site from dm activity
      Maximise the potential value of visitors to the site
    • The Solution
      The first step was to take the client’s database of registered users, plus a sample file of non-respondents, and append lifestyle and demographic overlays to the data
      CHAID modelling based on each set of overlays was carried out and gains charts compared to improve targeting
       The client’s registered user base was segmented in terms of their long-term behaviour in relation to the site
      The resulting 6 clusters were profiled in terms of their likely financial requirements and long-term value potential
      The rules for optimum allocation to segments were modelled using discriminant analysis
    • The Solution
      A series of new questions at registration were identified to give the client data to allocate the new user immediately to the appropriate segment
    • The Results
      There was an immediate increase of over 100% in site visits generated from direct mail through the improved targeting
      Value models within the segmentation allowed the client to estimate long-term potential value
      Thus determining the products advertised and marketing investment for each segment
      In addition, extra information about customers’ potential value are being added to the model as experience gives us more accurate information about the web-site’s longer term usage patterns and sales values
    • Case Study 2
      Holmes Place
    • The Brief
      Like many of its competitors, Holmes Place concentrated on acquisition during the unprecedented growth phase of the industry
      Customer retention and improved targeting for acquisition were recognised as important business drivers as:
      competition increased
      cost of acquisition increased
      attrition rates exceeded 50% per annum
      Little was known about the customer, and no estimates of customer value and what drives it had been evaluated
      The brief was to understand the customer better to allow for smarter and more efficient marketing activity
    • The Solution
      The first step was to take the client’s membership and transaction databases and combine them
      Append demographic and lifestyle information
      Identify valuable customers through data modelling – including length of membership and additional spend (e.g. personal training)
      Profiles for each club by value band were compiled
      Key variables – transactional and lifestyle - for predicting closure of membership were identified
      The resulting churn model was applied to the customer base to predict the likelihood of attrition
    • The Solution
      Although there are many factors affecting renewal of membership (such as moving away from the area), many members do not renew because of their lack of usage of the facilities available
      The models allowed us to identify the probability of each member renewing, and allows communication strategies to be put into practice for valuable but potentially disloyal customers
    • The Results
      Targeting for new customers has been revitalised
      After years of reducing returns from marketing targeted by demographics only, the new models coupled with data cleaning processes have resulted in a five-fold increase in response rates
      Costs per new member have been reduced
      Average value of each new member acquired was increased
      Early indications are that the modelling of likely defectors, coupled with communications designed to retain them, is starting to reduce churn rates
    • Case Study 3
      Nescafe
    • The Brief
      A major development in the Nescafe Ultra Premium brand strategy was to narrow the target audience that for marketing communications
      Extensive work by the brand team had re-defined the audience that Nescafe UP would target
      Two target audiences called Roast & Ground Dippers and Instant Dippers had been identified – c1.7m HH’s
      The brief was how, from a data perspective, do we find this audience to allow a major dm sampling campaign to take place
    • The Solution
      Nescafe did not have marketing data of their own
      There was not sufficient volumes of external data to purchase that identified ‘dipping’
      In order to get the quantity and quality of data needed we proposed data modelling
      In simple terms, this meant creating a profile of the people we wanted and then finding lookalikes
      The secret lay in having the most accurate profile at the start
    • The Solution
      We recommended using Tesco Clubcard data to create the profile that the data model would be built around
      The model were built using CHAID and then applied to external lifestyle data sources
    • The Results
      The data model used in the direct marketing campaign proved to be highly successful
      The mailing delivered £280k uplift in the first three months alone
      The mailing had an impact on customers behaviour resulting in sustained change over a year – once customers had tried it they remained loyal
      Customers moved from the targeted product areas of Freeze Dried and R&G proving the model’s accuracy
      At a brand level customers were most likely to have moved from Kenco Ultra Premium and other Premium freeze dried coffees
    • The Data People turn customer data into greater profits
    • Thank You