Marketing 0

Step 2: Identify Data Requirements and
Availability
In the digital era, the volume of data is growing exponentially. Not
only is the level of detail deepening, but the variety is also widening.
However, not all of the data are valuable and relevant. After
companies zoom in on the objectives, they must start identifying the
right data to collect and analyze.
There is no one right way to classify big data. But one of the practical
ways is to categorize based on the source:
1. Social data, which includes all the information that social media
users share, such as location, demographic profile, and interests
2. Media data, which includes audience measurement for
traditional media, such as television, radio, print, and cinema
3. Web traffic data, which includes all logs generated by users
navigating the web, such as page views, searches, and purchases
4. POS and transaction data, which include all records of
transactions made by customers, such as location, amount,
credit card information, purchases, timing, and sometimes
customer ID
5. IoT data, which includes all information collected by connected
devices and sensors, such as location, temperature, humidity,
the proximity of other devices, and vital signs
6. Engagement data, which includes all the direct touchpoints that
companies make with customers, such as call center data, email
exchange, and chat data

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Marketers need to develop a data collection plan that lays out every
piece of data that must be acquired to achieve the predetermined
objective. A data matrix is a useful tool that maps the required data
against the goal. Looking at the data matrix horizontally, marketers
can determine if they have enough data to accomplish the objective.
To have valid insights, they need data triangulation: having multiple
data sources that contribute to a convergent understanding. Looking
at the data matrix vertically also helps marketers understand what
information they need to extract from each data source (see 
Figure
8.3
).
Some of the data types mentioned in the numbered list previously,
such as transaction and engagement data, are internal and accessible
for marketers. However, not all internal data is ready for use.
Depending on how well organized and maintained the records, data
cleansing may be required. It includes fixing inaccurate datasets,
consolidating duplicates, and dealing with incomplete records.
FIGURE 8.3
Data Matrix Framework
Other datasets, such as social and media data, are external data and
must be acquired via third-party providers. Some data can also come
from value chain partners, such as suppliers, logistics companies,
retailers, and outsourcing companies.

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