Who We Are

Dan Wood specialises in championing the customer, relentless in pursuing essential customer insight to recognise behavioural patterns and enable effective customer centric strategy. Leveraging an intuitive grasp for transactional, CRM, loyalty and clickstream data to provide actionable B2B and B2C solutions which amplify loyalty and value through applications such as segmentation and propensity modelling.

Drawing from 20 years advanced analytics experience covering marketing optimisation, cluster and regression modelling through to real-time machine learning using big data customer personalisation algorithms across telecommunications, travel, insurance, grocery retail, oil, membership and technology sectors.

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Insight:

  • Profile and Trend analysis to understand value and behaviour.

  • Cluster Segmentation to identify distinct groups.

  • CHAID decision trees to differentiate and weight attributes.

  • Logistic & Linear predictive models to predict who and by how much.

  • Text Mining to extract sentiment and key terms.

Optimisation:

  • Lifecycle Status classification as New/Growing/Established/Risk/Decline/Lapse/Lost.

  • Next-Best-Action to predict best Repeat/Up-Sell/Cross-Sell opportunity objectives.

  • Retention by identifying churn risk and retention strategy.

  • Prospect Scoring to maximise returns from acquisition investment.

Reporting:

  • Cohort Tracking to evaluate growth and potential performance.

  • Forecasting trend for target setting and impact analysis.

  • Campaign Results lift and ROI success measurement.

  • Dashboard KPI tracking for stakeholder visibility.

Action:

  • Strategy definition that is both data driven and Win-Win.

  • Innovative Campaign Planning to achieve strong response rates and a positive ROI.

  • Project Management seamlessly efficient to exceed delivery expectations.

Specialities

  • Python - data wrangling, modelling and API pulls with Jupyter/HEX.

  • R – analysis and modelling with Rstudio-Server & Shiny.

  • SQL - selection, aggregation & automation in SQL Server, Hive, Impala, Terradata, Oracle.

  • Google Cloud - BigQuery, CloudCompute, Storage, ML & AI.

  • Amazon Web Services - Using AWS Redshift, S3, SPARK, Databricks & Qubole.

  • Looker, Google DataStudio, Tableau, Qlikview, Qliksense and other visualisation tools.

  • Adobe Omniture, Google Analytics, iJento & Webtrends WebAnalytics platforms.

  • SAS - programming in Base, Guide and Studio.

  • Hadoop - both Horton Works and Cloudera.

  • SPSS - including Modeler.