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Big Data in Marketing

Big Data refers to sets that are too large or complex for traditional data-processing application software to adequately deal with. the now-mainstream definition of it as the three Vs
Volume Organizations collect data from a variety of sources, including business transactions, social media, and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem but new technologies have eased the burden.
Velocity streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors, and smart metering are driving the need to deal with torrents of data in near-real time.
Variety comes in all types of formats from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data, and financial transactions.

Big Data in Marketing

It doesn’t automatically lead to better marketing. There are three types of it are key to marketing

Customer The most familiar category to marketing may include behavioral, attitudinal and transactional metrics from such sources as marketing campaigns, points of sale, websites, customer surveys, social media, online communities, and loyalty programs.
Operational includes objective metrics that measure the quality of marketing processes relating to marketing operations, resource allocation, asset management, budgetary controls, etc.
Financial housed in an organization’s financial systems, this big data category may include sales, revenue, profits and other objective data types that measure the financial health of the organization.

Big Data and analytics will revolutionize marketing and sales. it is providing insights into which content is the most effective at each stage of a sales cycle, how Investments in Customer Relationship Management (CRM) systems can be improved. The following are the ways it is revolutionizing marketing

Differentiating pricing strategies become more achievable to the customer-product level and optimizing pricing using it. assuming there is no loss of volume, pricing has significant upside potential for improving profitability.

revolutionizing marketers are using it and analytics to improve responsiveness to 36% are actively using analytics and data mining to gain greater insights to plan more relationship-driven strategies.

Supported its affiliated technologies The marketing platform stack in many companies is growing fast based on evolving customer, sales, service, and channel needs not met with existing systems today.

Optimizing selling strategies geoanalytics are starting to happen in the biopharma industry. If these companies could more accurately align their selling and go-to-market strategies with regions and territories that had the greatest sales potential, go-to-market costs would be immediately reduced.

enabling enterprises to gain greater insights and actionable intelligence into each of the key drivers of their business. reducing costs and reducing working capital are three core areas where it is delivering business value today.

Customer Value Analytics (CVA) is making it possible for leading marketers to deliver consistent omnichannel customer experiences across all channels. The bottom line is that CVA is now a viable series of technologies for orchestrating excellent omnichannel customer experiences across a selling network. 

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