PrefSolve™
Feature Document
|
| ZZZ |
PrefSolve™ 7.5 |
Unique to PrefSolve™ |
| Type of Data
That Can Be Analyzed |
| Importance data (preference data) |
ü |
ZZZ |
| Stated |
ü |
ZZZ |
| Inferred (calculated) |
ü |
ZZZ |
| Part worth utilities, main effects only |
ü |
ZZZ |
| Part worth utilities, main effect with interactions |
ü |
ZZZ |
| Performance data |
ü |
ZZZ |
| Expectation |
ü |
ZZZ |
| Stated |
ü |
ZZZ |
| Inferred (calculated by utility apportionment) |
ü |
ZZZ |
| Gap between preference and expectation |
ü |
ZZZ |
| Utility Calculation
Options |
| MANOVA** |
ü** |
ü* |
| non-metric regression |
ü |
ü* |
| OLS** |
ü** |
ü* |
| Proto-utility assignment using only prior data |
ü |
ü* |
| Utility Calibration |
| Calibrates to claimed behavior using correlation
to full profile concept |
ü |
ZZZ |
| Creates over 1000 utility sets to find optimum
fit between simulator and claimed behavior |
ü |
ü |
| Identifies best natural exponent automatically |
ü |
ü |
| Identifies best priors to pairs ratio automatically |
ü |
ü |
| Identifies best tau value cut-off automatically |
ü |
ü |
| Automatically graphs utility spectrum to assist
in selecting best overall utility set |
ü |
ü |
| Stores best overall utility set as the final set |
ü |
ü |
| Calibrates best fit individual logic function
for LOP modeling |
ü |
ü |
| Calculates best fit global likelihood function
(across respondents) |
ü |
ü |
| Provides option for the user to elect to employ
the best fit likelihood global function to replace poor fitting individual
respondent functions |
ü |
ü |
| Uses expert system to calculate best parameters** |
ü** |
ü |
| Analysis Setup
Options |
| Data can be run weighted or unweighted |
ü |
ZZZ |
| All analyses can be run on all attributes or a
selected subset |
ü |
ZZZ |
| An infinite number of subgroups can be set-up
and run (up to available memory) using run groups |
ü |
ü |
| Run groups can be made inactive or active |
ü |
ü |
| Run groups can be saved to a file and restored |
ü |
ZZZ |
| Market filters can be created allowing certain
segments to be excluded regardless of the run group setting |
ü |
ZZZ |
| User customizable technical and environment settings
can be saved with the preference file (thus determining settings when
the file is reloaded) |
ü |
ü |
| Configurable statistics settings (alpha level
for T-tests, ANOVA, LOP cutoff) |
ü |
ü |
| Report can be customized to include or exclude
features (i.e. titles, attributes, significance, segments, sorting) |
ü |
ZZZ |
| Report output selectable in either spreadsheet
or ASCII format |
ü |
ZZZ |
| Reports can be saved in native Excel format |
ü |
ZZZ |
| Descriptive
Analytical Capabilities |
| Calculates aggregate attribute utilities (or by
group) |
ü |
ZZZ |
| Calculates aggregate level utilities |
ü |
ZZZ |
| Calculates aggregate performance values |
ü |
ü |
| Calculates aggregate expectation values |
ü |
ZZZ |
| Calculates aggregate gap between performance and
importance |
ü |
ü |
| Tests differences across more than two groups
of data means (ANOVA) |
ü |
ü |
| Tests differences between two group data means
(T-tests) |
ü |
ZZZ |
| Outputs data by any respondent segment |
ü |
ZZZ |
| Runs multiple data reports in customized batches |
ü |
ZZZ |
| Scans automatically for all significant differences
in the data across segments by attributes (one-way segment-scan) |
ü |
ü |
| Scans automatically for all significant differences
in the data across multiple layers of segments by attributes (multi-way
segment-scan) |
ü |
ü |
| Terse output of significance scanning |
ü |
ü |
| Save and print report data into Excel spreadsheet
format |
ü |
ü |
| Save and print report in ASCII format |
ü |
ZZZ |
| Simulation Features |
| Change product concepts by setting attributes
to a discrete level |
ü |
ZZZ |
| Change product concepts by setting attributes
to a weighted combination of levels |
ü |
ü |
| Create new product concepts as a copy (instance
from another concept) |
ü |
ZZZ |
| Create new product concepts from scratch |
ü |
ZZZ |
| Delete product concepts |
ü |
ZZZ |
| Change the reference product for models requiring
a reference product (e.g. switching, retention) |
ü |
ZZZ |
| Save product concept changes to a file |
ü |
ZZZ |
| Simulation Modeling
Outcomes (Models Built into PrefSolve) |
| Share of preference |
ü |
ZZZ |
| Average likelihood of purchase |
ü |
ZZZ |
| Percent likelihood of purchase |
ü |
ZZZ |
| Respondent switching |
ü |
ü |
| Customer retention |
ü |
ü |
| Marginal benefit (maximize preference / minimize
cost) |
ü |
ü |
| Consolidation percentage |
ü |
ZZZ |
| Consolidation revenue opportunity |
ü |
ZZZ |
| Balance growth percentage |
ü |
ZZZ |
| Balance growth revenue |
ü |
ZZZ |
| Customer satisfaction (gap between expectation
and performance) |
ü |
ZZZ |
| Revenue contribution (percent LOP multiplied by
revenue per respondent) |
ü |
ZZZ |
| Enhanced Simulation
Modeling Features |
| Model Normalization: can be competitive or non-competitive |
ü |
ZZZ |
| Model apportionment: model can be set to apportion
share only to a user selected number of the top products (Top-k) |
ü |
ü |
| Top attribute contribution: user can customize
the model to use only a set number of the most important attributes
to contribute to the product |
ü |
ZZZ |
| Attribute sensitivity: automatically runs all
levels of all attributes to produce sensitivity charts for each attribute |
ü |
ZZZ |
| One-way product significant difference scanning:
scans for significant differences in utilities between segments for
products |
ü |
ü |
| User Modifiable
Adjustments to Model Algorithms |
| LOP algorithm adjustable by slope term and LOP
decision rule |
ü |
ü |
| Switching algorithm user adjustable by answer
required for switching, switch latency factor, and percent difference |
ü |
ü |
| Interoperability
with Other Applications |
| Produces normalized utilities for input into SegmentSolve™ |
ü |
ZZZ |
| Creates SPSS™ syntax code to allow SPSS™
to crosstab switchers, or those likely to purchase |
ü |
ZZZ |
| Produces runs to be visualized in PositionSolve™ |
ü |
ü |
| Accepts strategies from PositionSolve™** |
ü |
ü |
| Goal Solving |
| Multiple Attribute Simulation Scanning (MASS)
Millions of scenarios tested automatically |
ü |
ü |
| Visualization |
| Create bar charts for demonstrating all types
of reports |
ü |
ZZZ |
| Create column charts for demonstrating all types
of reports |
ü |
ZZZ |
| Create line graphs for demonstrating all types
of reports |
ü |
ZZZ |
| Create area graphs for demonstrating all types
of reports |
ü |
ZZZ |
| Create pie charts for demonstrating all types
of reports |
ü |
ZZZ |
| Rotate in 3-D for all charts and graphs |
ü |
ü |
| Manipulate chart display customization options:
Change report and axis titles, colors, and properties, and change
data series display properties |
ü |
ZZZ |
| Change geometry customization options: Change
rotation, spacing, and distance settings |
ü |
ü |
| Software platform |
| Visual C++, 32 bit, MFC |
ü |
ZZZ |
| Stingray Objective Grid for Tables |
ü |
ZZZ |
| ZZZ |
| *Comprehensiveness of algorithms used
(PrefSolve™ uses all) |
| **End of 2004 |
