The Big Data Revolution – How It All Started

Big data has been taking the business world by storm for more than a decade. In 2005, Roger Mougalas probably wanted to make things official and coined the term Big Data for the first time; for the extremely large and complex datasets that traditional data processing applications were not able to manage.

By the beginning of the 2000s, the technology big guys such as Google and Yahoo! started working on new methods in order to manage complex and the huge amount of quantities of data, which was accepted as the beginning of the big data revolution. After that, the open-source methods enabled organizations to manage and process huge amounts of data cost-effectively and efficiently.

New Asset: Knowledge Hidden Behind Big Data

In today’s data-intensive world, having big data isn’t a cool asset anymore unless you generate insights and know how to utilize big data. Therefore numerous industries are embracing big data for many reasons now. Whatever business you are in, you need to get the best out of big data technologies in order to;

  • Gain customer insights
  • Enhance customer experience and engagement
  • Increase efficiency
  • Improve strategic decision making
  • Improve innovation process/time to market
  • Achieve financial savings
  • Achieve an effective digital transformation
  • Improve compliance with laws and regulations
  • Improve relations with other stakeholders
  • Improve security, reduce fraud

to name a few. In fact, according to an international survey* 43% of the companies indicated that they received at least one of the benefits aforementioned.

*DNV GL – Business Assurance in conjunction with research institute GFK Eurisko

Center of the Businesses – Customer

In order to utilize big data efficiently, you need to fully understand big data – what it means to your organisation, what it does for you for better business. Since big data is bigger than it sounds, you can start utilizing your customer data -since it is the core of every business- to start with. So, how do you do that?

First step: Analysing Data

Making Sense of Big Data and using it for future decisions has become the major values of organisations and Business Analytics play a key role here. Through some techniques such as Predictive Analytics, Real-Time Data Insights, and Data Mining; Business Analytics uncover trends in your data, provide greater and faster insight, help you to track and act on performance immediately so that you can build more efficient pricing, sales and marketing strategies and improve customer satisfaction. So, good news: you don’t need a crystal ball to predict the future and act wisely!

Make the Complex Simple: Visualize

Data analysis might make a lot of sense to data analysts and data scientists but in real-life; marketers, your sales team, or other stakeholders will also need to interpret your analysis.

Data Visualization comes to the rescue when you have enormous amounts of different datasets by translating your multiple information into a language that is easy to understand, process and present. Data visualization allows you to discover hidden patterns or trends so that you can connect the dots and see the ‘big picture’ in your data. Having more meaningful data enables you to increase customer satisfaction, improve decision making in marketing activities, sales and business strategies and drives revenue growth where you can also predict failure points for future strategies.

Time to Take Action

After you analyse your data and visualise it, now your data makes sense to you and you are ready to take wise actions. For example you can leverage your segmentation strategy by adding advanced behavioral segments to your current segments which are simply based on customer demographics, locations, or lifestyles. An advanced segmentation will enable you to track your customers’ behavior patterns and act on them simultaneously, or even before they occur. For instance, by integrating all channels together you can track various data gained from customer e-mails, website actions, user forums, call center, user behavior etc. and can build unique customer profiles.

With this information gained from different channels, a bank for example, can easily detect if a customer is about to leave if they are following a similar pattern with other customers who already canceled their accounts and take immediate automated actions. In three steps, you can target audience, define campaign offer and identify marketing channels. You can boost your customer engagement with rich media and deliver your marketing messages across all channels.

Moreover, in addition to being aware of problems before they get complicated; you can also easily offer your customers upselling and cross-selling opportunities real-time.


Using big data technologies wisely is the crucial step for a better digital transformation and prioritizing customer and customer journey in your data analysis is important for all your business and service units. However in order you to take the right actions which truly affect your business; you need to have an integrated solution covering data analysis, data interpretation and taking immediate and automated actions.

At Commencis, we help you grow your business with our integrated and simplified marketing platform “Connect” and build your roadmap for better business.

It is now possible for you to truly make sense of your data and even boost conversion rates by fixing where you lose customers via Connect;

  • Big Data & Insight
  • Unifying customer and product data into a single and centralized platform to drive impactful insights and predictions powered by AI Experience Analytics
  • Measuring and optimizing the effectiveness of your digital products, marketing campaigns and end-to-end customer experience
  • Cross-Channel Marketing
  • Building real-time contextual and personalized experience across channels through a simplified marketing platform