Every day, humanity creates 2.5 quintillion bytes of data (to give you an idea, a quintillion is a billion trillion, or 10 to the thirtieth power!), an amount that is expanding faster and faster and from which companies are trying to get the most information, with the aim to make predictive analysis and try to identify potentially interesting consumer trends.
The concept of Big Data has been coined to describe this phenomenon: a large aggregation of data from multiple sources (customer data, competitive data, online data, etc..), which bulk requires specific tools to be aggregated, analyzed and interpreted .
The advantage of Big Data lies in the fact of being able to carry out the interrelationships between the different sources, providing information impossible to obtain from an analysis of small data sets.
It is appreciated how Big Data can be a resource for all marketers: dealing with market analysis and make valid predictions has become a critical success factor, especially for analysts who work in the so-called “fast moving consumer goods. ”
By monitoring the immense amount of data coming from the Web, for example, it is possible to check the sentiment of the market for certain products or identify potential crises and disputes before they become unsolvable.
A recent survey by SAS and the CMO Council shows that most of the marketing directors used the Big Data to perform predictive analysis about their own customers (71%), trying to identify and target the most profitable market segments.
A good part of the analysis were carried out to profile their customers in the best way (53%), identifying more precisely their habits .
Nearly half, however, has used the Big Data to improve their customer service and monitor customer feedback, while 42% of marketers surveyed constantly monitors the activities of their customers on social media.
In any case, the spread of this trend, which is offering to marketers incredible new opportunities, also poses new problems.
Analyzing large amounts of data when trying to take the relevant information is difficult and often can trap more curious marketers in long analysis, not always useful.
61% of respondents of the previous research, in fact, claims that Big Data hides of large obstacles, and that their companies still have a long way to go in order to take advantage of this opportunity.
A further 5% of respondents said that Big Data is a big hurdle and not an opportunity. You can deduce then that marketers have only begun to discover this world, and they’re only deducting the possibility that offers.
To avoid wasting time and resources, there are 7 key points that can help those who want to take advantage of Big Data in order to obtain relevant information, useful to all analysts who often have to work to make the analysis of more “compact” sources.
Ask the right questions
Before you start collecting data is always good to clarify what you want to search.
Being more aware of what you want, there will be more opportunities to find the data you need.
Thanks to Big Data it can be discovered, for example, that a specific portion of the market is more loyal to a particular brand or which type of consumer might be more inclined to buy a given product.
Clarifying also serves to give priority to the objects of analysis and allocate resources (time and money) of the most important ones.
Define how you will use the information
Should the analysis be carried out with periodic intervals?
Or is it needed a focused analysis of a specific case, as the launch of a new product?
Answering these questions can give you a better idea of how to organize your work and make it more efficient.
Think beyond the initial question
After the analysis has answered the original question may arise more ideas.
For this reason it is important to structure the data in such a way as to obtain different levels of detail, so you can answer the questions that gave rise to the first analysis.
Identify the different sources of data that needs to be connected
Once it is clear that the output you want to achieve, it must be established which data sources are required for the analysis.
The operation can not be trivial, because after identifying the sources, the data must be formatted to be used by the different tools that are usually used for the analysis of large databases.
Organize the data sources
Draw a simple map of interpretation, in order to keep in mind from where the data come from.
In this way it will make it more clear and simple to work also for your superior and employees.
Choose the right tools for your organization
The tools to analyze large amounts of data may be different, and the choice of the most appropriate may be trivial.
Many platforms, such as those provided by Oracle and IBM are designed for large companies, but there are also relatively cheaper suite, such as Jaspersoft or Pentaho BI.
Google also offers a service for the analysis of Big Data (Google BigQuery), but with flexible pricing policies.
Determine how the output should be represented
In this way you will already have an idea of how they can be used representations of data sets and what information may be identified by their reading.