How Data Driven Marketing Has Evolved and Big Data is Affecting the Industry

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Joginder Chhabra
New Update
analytics

The possession of data which once used to analyse the past trends, is now being effectively used to predict the future, with the advancement of Big data analytics.

The need for data driven marketing is essentially driven by evolution of new age customer, who is more informed about the choices than ever before. There is a significant increase in the consumer touch points across offline & online media and  with the advent of social media , customer has multiple platforms to interact and gradually word of mouth marketing has also become important.

IT technology has advanced with multiple Information storage and increased processing power and more meaningful data & insights is available for today’s customer including his current & future preferences with reasonable quantification. Due to this, there is always a increased pressure on Marketer to justify spends and improve customer experience.

The Current Context

Data driven marketing in the current context has the primary objective of engaging the customer & improving his overall experience with the product / service across major customer touch points effectively.

Most of the organizations are dealing with big data more effectively due to advanced / ongoing developments in IT & increased IT penetration in daily life. In marketing, qualitative marketing performance has been replaced by quantitative functional assessment of advertising campaigns using advanced data analytics. Analytics models are also being used to effectively monitor media costs (offline/online), linked directly to sales efficiency.

Using advanced data analytics, organizations have a better clarity on how individual marketing functions and various trade channels have contributed to the overall revenue. The marketers as a result are more informed on ROI for marketing spends across various channels .

Customer & Business Insights

Customer & Business Insights has become a important tool in marketing and organizations are seeking customer opinion via frequent interactions for pre & post marketing activities of all kinds. Organizations are collecting meaningful data about their purchase/ loyalty behaviour of customers to manage the overall marketing function better. More and more focus is on having focused customer Insight  for planning new advertisement, new product launches etc. and  other ATL & BTL activities.

Globally Big data is making inroads into complex problem solving for various areas such as public healthcare, banking, retailing, climate change prediction and fraud investigation etc.

In future organizations which manages and leverage huge amounts of data from different sources such as CRM, Web analytics , search marketing, mobile apps, social media etc. will have a clear differentiating edge over competition in terms of understanding of customer preferences, new product development & overall market share.

Big Data as Information Source

However Big data is more of information source, it can effectively explain what , rather than explaining the process. Therefore marketers must not discard the power of intuition, qualitative insights and innovation not being in sync. 

Effective Big data management within the organisations will lead to meaning full customer and business predictions. The organisations which see data as key marketing input will enhance the overall customer value in along way.

To consolidate data driven marketing in the organisation , the entire focus has to change from traditional acquisition based marketing model to more customer oriented model.

Also required is increased spend & focus on digital marketing and customer insights  as various online and e-commerce companies are doing various innovations for customer retention.

Critical part in achieving data driven marketing is effective collaboration between IT & Marketing within the organization. The data analytics models must be customised as per the organization size and overall marketing objective.

Social Media Marketing consumer behaviour data driven marketing Big Data consumer and business insights