CUSTOMER ANALYTICS ESSENTIALS

 New to data analysis and targeting? Click here to see our straightforward guide. 

The following items are perfect for data analysis and should be considered priority items. Tech4T can supply these as a discounted bundle solution from a single source.

• New Direct Marketing - perfect reference book

• FastStats Discoverer ( and/or KbaseT ) - for the database marketer and data analyst who needs to quickly analyse any volume of data - customer, transaction, prospect, etc. data - then build nested cross-tabs, charts, maps, profiles, scored models, etc. and quickly export for marketing action. Fast and easy to use. Functionality includes transaction and basket analysis (combinations/patterns of products purchased)
  See also Profiling, Scoring, Predictive Modeling...

• MapPoint and Geo-concept - geographic mapping, territory analysis...

• SPSS Base - file manipulation, recoding, restructuring, cross-tabs, regression...

• SPSS Tables - tabular and nested reporting (add-on for SPSS Base)

• SPSS AnswerTree - response modelling and segmentation

• QPSMR - complete market research survey analysis system - CAPI and CATI - including design with skip and fill rules, fast data capture and extensive cross tab analysis and reporting, and export to SPSS for additional statistical analysis and charting

• ORA - web delivered campaign and management information reporting

• Tech4T tailored training - skills-transfer working with your own data

• Consultative and technical support

For organisations wishing to undertake data analysis tasks in-house, Tech4T can supply the specialist software, tailored training and single contact 'one-stop' support. Software can generally be used stand-alone, configured as a tailored combination of modules to meet specific marketing, analysis and business objectives, or used to complement existing I.T. systems.

For Tech4T's analytical services - click here

See an analytics example - click here

CUSTOMER ANALYTICS - UNDERSTANDING YOUR CUSTOMERS

• Getting started - or need the perfect reference book that helps you apply statistical analysis to data-driven marketing, buy The New Direct Marketing

• Data storming - As data technicians, analysts and direct marketers tend to work creatively, there is a need to capture ideas, structure them and turn them into action with maximum ease. With Mind Manager you can create mind maps to clearly explain all of your thoughts and processes and easily translate them into a synchronised project plan in MS Project, a MS PowerPoint slide-show, MS Word document, fully linked website and more!

• Data preparation and exploratory marketing/data analysis - for Data Mining and Customer Knowledge/Analytical CRM. To see how Tech4T undertake analysis, click here. Getting started with the analysis essentials - file sorting, selection, transformation, missing value analysis, date conversion, data banding, labelling, cross-tabs, graphing, task automation and elementary data analysis. SPSS - introduction to database marketing,  SPSS Base, SPSS Tables. Also WPS (Based on SAS Base), DBMS/Copy and KbaseT.

• Lifetime value analysis. How to measure customer cost and profitability. Understand purchasing patterns and find out how to apportion promotional spend correctly in order to maximise return on marketing investment. The approach you take would depend on how you wish to define Lifetime Value - total sales value per customer over X years, total sales value by product group after say the initial relationship building period, profit contribution over time however defined - i.e. how do you take account of order returns or transaction cancellations based on the cause, etc. Once defined, you then need to develop an approach and determine the computation needed. This would include first bringing together sales values, profit contribution, marketing spend, sales and customer service costs, etc., applying the necessary calculations and then correctly apportioning values to each customer in a format that suits what you next wish to do with the information - using for segmentation or profiling, targeting, looking at change... Techniques to take include file and record merge, aggregation, file flattening, split file processing, predictive modelling and ‘marketing effort’ scoring.
  * For the marketer and I.T. support team - KbaseT
  * For the analyst - SPSS Base, SPSS Tables, FastStats Discoverer plus KbaseT

• Profiling, Database Segmentation and Predictive Targeting. See also RFM - Recency, Frequency, (Monetary) Value. Who are your customers, what do they look like? How do their personal, business and trading characteristics differ? When profiling and segmenting your customer base there are several approaches that can be taken. For B2B it might be as simple as grouping by company size, number of employees, etc., or with B2C grouping by age, gender, demographics, lifestyle, etc. This can be enhanced by merging external data from mailing lists, surveys and marketing statistics and also by deriving new fields such as lifetime value. However you can enrich this process by using statistical analysis. Either look for natural groups or clusters in your data, letting software such as SPSS determine the strengths of your variables (fields), or look for groups (segments and their profiles) based on their differences to take a particular action - buy or not buy blue widgets, etc., using predictive modelling. Once segmented and profiled, you can then see how groups of similar customers compare over time after being for example, subjected to different kinds of marketing treatment. Techniques for segmentation and profiling (putting descriptions to the segments) include correlation, weighting, ranking and scoring, factor and cluster analysis, predictive and response modelling...
  * For the marketer and I.T. support team - KbaseT
  * For the analyst - FastStats Discoverer, SPSS Base, SPSS Tables, AnswerTree,
    4Thought (Neural Network), KXEN plus KbaseT

• Modelling for improved campaign response and reduced fraud. To identify database segments more likely to respond to specific offers and to predict future sales and purchase activity together with customers likely to cause bad debt. This is really an extension of database segmentation listed above. Techniques typically include sampling, marketing profit and loss, predictive and response modelling, (inc. CHAID) modelling, logistic regression, discriminant analysis...
  * For the marketer and I.T. support team - KbaseT
  * For the analyst - 4Thought (Neural Network), AnswerTree (credit example),
    SPSS Base, SPSS Tables, SPSS Regression, KXEN plus FastStats Discoverer
    and KbaseT

• Churn or customer attrition analysis. Find out why customers defect, develop corrective retention and acquisition strategies and help define service levels to maximise loyalty. Techniques usually applied include predictive modelling, competitor analysis, forecasting...
  * For the marketer and I.T. support team - KbaseT
  * For the analyst - SPSS AnswerTree, 4Thought (Neural Network),
    SPSS Base, SPSS Tables, SPSS Regression, KXEN plus FastStats Discoverer
    and KbaseT

 

• Market research and survey analysis. See some ideas on what you might like to learn - click here. Use questionnaires to gather additional data to enrich your customer understanding and database targeting. Also research customer perceptions of your products and services and determine their fit in the marketplace. QPSMR, SPSS Data Entry, SPSS Base, SPSS Tables, SPSS Conjoint, SPSS Categories, SPSS AnswerTree

• Geographic analysis. For penetration and competitor analysis, media coverage, sales territory rationalisation, resource optimisation, etc.  MapPoint, Geo-concept, Tactician, SPSS Maps plus KbaseT

• Forecasting. For demand business forecasting use 4Thought (Neural Network), ForecastPro, SPSS Trends or KXEN

• 'Rules-based' - Magenta application using 'Agents' to define the appropriate outcome to your problem - however complex!