The document emphasizes the importance of combining quantitative and qualitative data for effective business intelligence and analytics. While quantitative data provides measurable insights into performance and trends, qualitative data captures unstructured sentiments and intentions, enriching understanding and decision-making. Together, these data types offer a comprehensive view that enhances predictions and supports tailored strategies for continuous improvement.

1. Quantitative &
Qualitative Data:
A Vital Combination

2. Viewed as the bedrock of your business
intelligence and analytics program because
it can reveal valuable insights.
These numbers show performance,
efficiency, reach, market share, revenue in,
and expenses out.
It forms the basis on which you can infer,
estimate, and project future performance,
using techniques such as regression
analysis, hypothesis testing, and Monte
Carlo simulations.
SWIPE
Digging
Quantitative Data

3. Problems with
Quantitative Data
Data from diverse sources lacks uniformity.
Organizing and cleaning are crucial to
prevent errors and maintain data integrity
for accurate insights.
Not all collected information is structured
quantitative data; it may constitute only 20%
of available data. Focusing solely on this
overlooks valuable information, distorting
insights.
SWIPE

4. Exploring
Qualitative Data
Qualitative data is unstructured, coming in
diverse forms like text, social media
comments, phone call transcripts, logs,
images, audio, and video.
Qualitative data describes characteristics
through categorical variables, offering
insights into feelings, opinions, and
intentions. Collected informally through
methods like comments and interviews, it
captures natural language perspectives of
customers, users, or stakeholders.
SWIPE

5. Qualitative Data
Benefits
Qualitative data reveals sentiments, using
techniques like content and narrative
analysis to identify common themes and
interpret feelings for effective changes or
innovations.
Qualitative data enhances decision-making,
providing insights for strategic direction. It
improves predictive analytics by
understanding intention and behavior,
ensuring solid, data-driven decisions from
unstructured data analysis.
SWIPE

6. Better together: Working
with Qualitative Data and
Quantitative data
Qualitative and quantitative data synergy
provides a holistic view, revealing both
patterns and context. Quantitative data
unveils trends, while qualitative data
explores intentions and emotions behind
the numbers.
Enables organizations to make more
accurate predictions, anticipate trends, and
proactively respond to dynamic scenarios
by considering both measurable aspects
and nuanced human elements.
SWIPE

7. Better together: Working
with Qualitative Data and
Quantitative data
Adding qualitative data to customer
analytics goes beyond transactions,
revealing customer experience and
sentiments. This enables tailored products,
services, and marketing strategies that
address both numerical and emotional
needs.
Continuous improvement benefits from
both data types: Quantitative metrics
optimize areas, while qualitative insights
refine processes, products, or services
iteratively.
SWIPE

8. YOUR PREDICTIVE INSIGHTS
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