I want to know how big data will change my marketing strategy
How can I use big data in my marketing strategy?
"Big data" makes marketing strategies more effective.
Its importance is increasing, and many companies are using big data to improve their performance.
However, some people may not be able to imagine how to change specific aspects of their marketing strategies.
This article explains how big data will change your marketing strategy . It also explains
the specific changes in business operations and how to put them into practice , so it is recommended for those who are considering using big data.
In conclusion, what the use of big data does is change the time it takes from analysis to action .
By obtaining highly accurate analysis results from large amounts of data, marketing strategies can be planned and decisions can be made more quickly.
If you want to improve your business and grow your company, read this article to the end.
table of contents
Big Data: How it Changes Marketing Strategies
Elements of Big Data
Types of Big Data
Examples of big data usage
Big Data Changes Marketing Strategy [5 Business Operations to Improve]
Data collection
Customer behavior analysis
Personalization
decision making
PDCA Cycle
How big data can change your marketing strategy
Clarify the purpose of using big data
Collect and process only the data you need
Analyze and visualize correctly
Take thorough security measures
Show more
Big Data: How it Changes Marketing Strategies
An arrow points from a group of icons representing big data to a computer.
Big data is a huge amount of data that humans cannot comprehend.
A wide variety of data is generated every day, and it comes malta business email list in a variety of types and formats, including text, images, videos, and audio.
However, there is no clear definition of big data, and its interpretation varies depending on the industry and the person handling it.
[Big data examples]
POS data that records sales information in physical stores
Customer data that records customer attributes, place of residence, etc.
Email content, SNS posts and comments
Customer information for EC sites, websites, etc.
Elements of Big Data
Big data is made up of elements known as the "3Vs."
Building blocks of big data Features
Volume Huge capacity (tens of terabytes to several petabytes)
Variety Including unstructured data
Velocity (real-time data) High data update frequency and high processing speed are required
Currently, there is a tendency to consider the 5Vs, which add "Veracity" and "Value" to the 3Vs above , as components of big data.
Types of Big Data
Big data can be broadly divided into three types: structured data, semi-structured data, and unstructured data.
Of these, semi-structured data and unstructured data make up the majority.
Data Type Features example
Structured data Two-dimensional tabular data with rows and columns
Ready to use
Low growth expected POS data
Customer data
Excel format
CSV format
Semi-structured data The complete structure has not been determined, but there are boundaries regarding regularity.
Data needs to be organized and converted to be usable.
The trend is likely to continue to grow. SNS data
Log data
Sensor data
in XML and JSON formats
Unstructured Data Data that has no regularity and cannot be converted into a two-dimensional table format
This trend is likely to continue Audio, image, video
Text
PDF format
There are various ways of classifying big data.
The Ministry of Internal Affairs and Communications classifies it into the following four categories, focusing on data generated by the government, companies, and individuals.
Open data: Open data provided by national and local governments
Digitalization of knowledge: Digitalized and structured data of corporate know-how
M2M data: Streaming data collected from IoT devices via M2M communications
Personal data: Data related to an individual's attributes, behavioral history, etc.
(Reference: Ministry of Internal Affairs and Communications | 2017 Information and Communications White Paper | Definition and scope of big data )
"Digitalization of knowledge" and "M2M data" together are referred to as "industrial data."
Examples of big data usage
The following are some cases in which big data can be used in actual marketing strategies:
Customer behavior analysis using eye tracking data
Improving business efficiency by using weather data and traffic congestion information
Personalization using search, behavior, and purchase history
There are cases where sales increased after analyzing customer gaze movements using eye tracking and changing product displays to be more effective . For websites, you can optimize the placement of CTAs
by visualizing click locations with a heat map tool .
Weather data can be used to check customer trends, which is effective in adjusting the timing of sales and inventory levels .
Utilizing traffic information and traffic forecasts can help improve fuel efficiency and make deliveries more efficient.
The vast amounts of customer data from big data are also useful for personalization, which is essential in modern marketing strategies .
It makes it possible to provide recommendations and useful information that meet the needs of each individual customer.
Big Data Changes Marketing Strategy [5 Business Operations to Improve]
Two men discussing data
Utilizing big data will bring changes to the following tasks related to marketing strategies:
Data collection
Customer behavior analysis
Personalization
decision making
PDCA Cycle
By changing the above operations, the time from analysis to decision-making in marketing strategies will be significantly shortened.
Strategies can be planned and measures can be implemented smoothly, enabling a speedy PDCA cycle.
