Guide to big data analytics tools, trends and best practices
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Businesses must adopt data discovery tools at a faster pace if they want to run effective marketing campaigns and
compete for customers in emerging data service industries, according to industry analyst Tom Davenport.
Whenever I hear marketers disparaging IT or IT disparaging marketers I think this is not going to work out well, and often that's true.
professor of Management and Information Technology, Babson College
Big data is opening up new business opportunities that will be available to organizations that move quickly to make data analysis a central part of their operations, said Davenport, professor of Management and Information Technology at Babson College, during a Marketing Science Institute webinar titled The Rise of Big Data Analytics for Marketing.
He cited the example of General Electric Co., which has traditionally been a manufacturing powerhouse. In recent years, the company moved to adopt a more data-centric approach, and today it brings in more than 50% of its revenue from data services.
The opportunity is there for organizations that are willing to embrace it, Davenport said. Today's data discovery tools can help businesses understand the customer experience at a deeper level, attribute sales to marketing touches and determine the most efficient ways to spend their marketing budgets. These opportunities could boost marketing campaigns within an organization to support their primary work or become a line of business unto themselves.
"The decisions we have to make with [data analysis] are more important than ever," Davenport said.
So how does an organization embrace these opportunities? Davenport said that data discovery tools are important. It's hard to get started without a significant technology investment. That investment may range in size depending on how deeply a business wants to get involved in data analysis. There are some simple data visualization systems that can allow non-technical users to spot trends and make meaningful connections within data sets. However, businesses that want to make analysis more central in their operation may want to purchase more sophisticated tools, which may require hiring a data scientist.
Either way, businesses will to need to have at least one person on staff who understands both the analytics and business objectives. This individual should have a slight technical background (for example, being able to write queries in SQL), but also understand where the technology fits within the business's larger goals.
Lastly, a well-planned governance model is important, Davenport said. Before investing in technology and staff, organizations should determine whether the data discovery work will be owned by IT or the individual business users. Support for data discovery must come from the top for an initiative to work, and managers need to ensure that business users and IT support staff are on the same page.
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"You really need IT managers who support the business with technology and discovery ability," Davenport said. "Whenever I hear marketers disparaging IT or IT disparaging marketers I think this is not going to work out well, and often that's true."
Few marketing departments have the budget to run impactful data discovery initiatives right now, Davenport said. But he feels businesses will start to see the value in basing marketing decisions on data, which will lead to increased support. This will drive the development of more mature governance models, which will help set data discovery projects on firmer ground and enable organizations to take advantage of emerging opportunities in marketing and data services.
"It's clearly the early days of this phenomenon, but as it develops we'll have data discovery groups within organizations and I think marketing will either be its home or one of its primary customers," Davenport said.