Skip to main content
#
DATA SQUARE
Home
Integrated Marketing Platform
Strategic Consulting
Marketing Database Design and Hosting
Business Intelligence and Reporting
Analytics
Campaign Management
Email and Digital Marketing with Digital Square
Clienteling with Client Square
Integrated Solutions
Solutions
Industry
Companies
Conferences
Papers
Experience
Case Studies
Key Personnel
About Us
Careers
Contact Us
 Analytic Techniques 

Bayesian Methods

  • Predict the brand a household will choose for a given purchase occasion

Bayesian Networks

  • Build integrated models of consumer behavior that can be estimated with limited amounts of data using monte carlo simulations

CHAID

  • Identify and differentiate characteristics of best customers from others in the database

Cluster Analysis

  • Segment  customers into discrete groups based on multiple dimensions
  • Group products into bundles based on similarity
  • Segment markets and determine target markets
  • Develop product positioning and launch new products
  • Select test markets

Collaborative Filtering

  • Predict items (movies, music, books, news, Web pages) that a user may be interested in, given some information about the user's profile

Conjoint Analysis

  • Determine the combination of attributes that would be most satisfying to consumers

Discriminant Analysis

  • Predict propensity to respond vs. buy based on prior purchase and promotion history

Factor Analysis

  • Obtain underlying dimensions from responses to product attributes identified by the researcher

Fuzzy Logic

  • Determine baseline sales to enable a more accurate measurement of promotion and advertising effectiveness

Genetic Algorithms

  • Optimize the placement and numbers of callouts within a web page layout to grow, on an ongoing basis, a page's marketing gains

Linear Regression

  • Predict the dollar value of purchases associated with a mailing

Logistic Regression: Binary

  • Predict customers that are most likely to respond to a mailing

Logistic Regression: Multinomial

  • Predict customers that are most likely to purchase different products in a catalog mailing

Logit Analysis

  • Assess the scope of customer acceptance of a product, particularly a new product. Determine the intensity or magnitude of customers' purchase intentions and translate them into a measure of actual buying behaviour.

Markov Chains

  • Forecast store choice

Multidimensional Scaling               <<

  • Obtain underlying dimensions from respondents' judgements about the similarity of products

Neural Networks

  • Predict customer demand and segment customers into well-defined categories

Perceptual Mapping

  • Display the perceptions of customers or potential customers on attributes such as position of a product, product line, brand, relative to competitors

Preference Regression

  • Determine consumers' preferred core benefits. Supplement product positioning techniques like multi dimensional scaling or factor analysis to create ideal vectors on perceptual maps.

Structural Equation Modeling

  • Hypothesise models of market behaviour, and test or confirm these models

Survey Design and Analysis

  • Collect information on product attributes and/or spending potential on a sample of the customer base

                                 Back to Analytics
                   


    © 2011-2019 Data Square, LLC | 396 Danbury Road | Wilton, CT 06897 | info@datasquare.com | 1-877-DATASET | 1-203-964-9733      Privacy Policy