Teradata ebook: Big Data Marketing Hero
Teradata new ebook, freely available, gives guidelines on how to integrate information from all marketing channels, connect with customers in relevant ways, and help internal stakeholders understand the threats of divided data.
Generating big ideas from big data analytics requires business leaders to think big.
In a single year, people generate 1.8 zettabytes of data - the equivalent to every U.S. citizen tweeting three times per minute for 26,976 years! Harnessing such massive amounts of data is a challenge of heroic proportions, yet the rewards are greater perspective of your total marketing portfolio and unrivaled customer insight.
With technology's increasing reach into people's lives, marketing is now more than just about competing to be the best. The most successful companies are taking advantage of consumer data to carefully target the most likely consumers and make it easy for them to buy. The marketing leaders of these innovative companies are today's big data heroes.
Assembling large amounts of information about customer behavior is the easy part. The challenge is how to ascertain why consumers make the choices they do. Knowing what's worth measuring and how to use that info is what differentiates failure and success in data-driven marketing. The payoff consists of greater efficiency, effectiveness, and profitability, all of which are capable of happening quickly if you have the tools to respond.
The evidence is proving that companies that act quickly based on data-driven decisions are succeeding over their peers. Budgets are being used more efficiently, messaging and branding are having a greater impact, differing marketing campaigns are viewed as one unified endeavor, and the ability to adapt to the market is happening immediately as changes occur.
This guide can help you:
- Integrate information from all marketing channels to improve efficiencies.
- Connect with customers in relevant ways to boost profitability.
- Help internal stakeholders understand the threats of divided data.