5 Ways Big Data Has Changed Sales Forever

Big data by definition involves data sets so large and complicated that traditional processing is inadequate. The amount of data that's been collected is mind-boggling, and coming faster. It's been estimated that 90% of all that data was created in the last two years. The ability to aggregate it in meaningful ways still presents challenges. But big data also provides advantages for boosting sales well beyond anything that the marketing gurus of the past imagined. Because of those advantages, more companies are embracing it.

1. Wide-ranging benefits

While large enterprises have led the way in adopting big data technologies, small and medium businesses are flocking to predictive analysis to bolster their own sales. Large enterprises were formerly more likely to have the glut of data and the technical and financial resources to make the most of it, but that's changing. A Forrester study found that 44% of consumer-oriented marketing now utilizes big data. Open source software and cloud computing are making the software easily affordable, while expanding avenues of data collection such as mobile devices and social media are making the data itself more accessible. Include data brokers - companies that exist solely to amass and resell information - and big data is now available to even very small businesses in every industry.

2. Better leads, better retention

Sales conversion has always depended on quality leads to produce sales, and the explosion of big data analytics makes that much easier. It's possible to see in moments who is buying what top-end items, what demographics they represent, and what they respond to. More insight into customer demands and purchasing habits also leads to better customer satisfaction, which means more up-selling and more repeat sales. Salespeople who relied on interpersonal skills to find out what makes customers tick can now have the data-driven answers up front.

3. Spending

Big data is actually saving money. With all of that data to analyze, and increasingly sophisticated software to detect trends and patterns, there is less need of spending money on A-B research (comparing the merits of one strategy to another), test marketing, or cold-calling. Instead, sales tactics are built around hard data and consumer patterns. Proven data structures are being refined by software vendors to the point where standbys such as Hadoop OLAP (online analytical processing) are only improving the science of data mining. The fact is there is simply less trial-and-error and more hard statistics to determine what works with what audience.

4. Business value

Sales intelligence from predictive analysis is more productive than the instincts and experiences of even the most veteran sales people. Sales is now about mathematics. Increasing sales and more cost-effective marketing mean a jump in company value. Bigger sales mean higher stock values and more investors appreciating the superior nature of big data analytics over the guesstimation deriving from a stack of two-dimensional charts. Insuring a business becomes easier and cheaper when it employs big data.

5. Evolving job roles

As more devices are empowered by microcomputers and connected to global networks, it will be the machines gathering data. The Internet of Things may reach 28 billion devices by 2020. Collection of data will be even greater and more refined. Consequently, there is a greater push for AI, adaptability, and more-user friendly solutions to transform salespeople into sales analysts.

At the same time, cloud computing is giving us dashboard solutions to more easily visualize real-time data any way we want to slice it. While this is not the same thing as predictive analytics, that may be getting closer, too. It does provide insights and certainly represents a valuable tool for monitoring consumer activity and measuring success. In short, sales across the board is becoming far less of a gamble and far more of a science.
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