Is Big Data Boring? For This Singapore Analytics Start-Up, It’s A Resounding ‘YES’
As far as your company’s data is concerned, smart (data) is apparently the new sexy
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Behold, one of the least thrilling words in the English language: Reports.
It’s a sentiment felt by Aleetza Senn, CEO and co-founder of Sparkline, a Singapore-based start-up that works with large businesses to “train, mentor, support, and analyze data in a consolidated way.”
A Googler for almost 10 years across Asia-Pacific, Senn had sat through many “reporting” meetings wherein “it was obvious that businesses used data to report on performance, but didn’t have any sense of actionability.”
Senn had seen a niche in the market to develop a company that can “act on behalf of businesses to simplify, aggregate, and make their data accessible, and more importantly, actionable.” And so, in 2013, Sparkline was born. The company that has since grown from a team of two to 30, Senn relates that her team firmly believes that “it’s better to have smart data, not big data.”
A buzzword in this ever-increasing digital world, more and more companies are ranking “Big Data” high up on their priority lists—and for good reason.
As stated in this Inc. article, by the year 2020, an estimated 1.7 megabytes of new information will be created each second for every person on earth. “Big Data, and data in general, is complex and ongoing. It’s large, messy, and fast. And if you are digital, gone are the days of being given three to four months to work on an analytics project where you have time to cross T’s and dot I’s. Today it’s all about being nimble, agile, and iterative,” says Senn.
Here’s how Sparkline is helping businesses navigate the complex world of data analytics:
1. By focusing on small, digestible changes and iterations
While effectively leveraging analytics varies from one business to another—“There is no one-size-fits-all solution,” says Senn—one way they suggest companies may begin their data analytics journey is to do so incrementally.
“The question we often pose is, what do you use your data for today? Does it help drive decision-making and how accurate is it? These are good first step questions. The point is to start—just start! Businesses reticent to use data to acquire and retain customers will ultimately become irrelevant. We have many proof points showing data-driven businesses drive profitability so it is worth the investment,” she says.
2. By making digital information easy to digest
Sparkline is all about democratizing the digital landscape, says Senn. “We want to make digital information simple, accessible, and more importantly, actionable for all businesses. Through our customers and our ambitions, we are developing business-relevant products and services to solve real market problems,” she says.
One company Sparkline recently worked with, Reebonz, came to them to understand “how they could gain better clarity of their customers across devices and invest their ad dollars for maximum impact.” Senn shares they recommended using Google Analytics 360 to implement a single view of a customer across devices, and upon setting that up, “our analysts investigated the data and found that when mobile web is part of purchase, conversions improved by up to 2.8 times. Armed with the knowledge, Reebonz implemented a robust marketing approach that doubled cross device conversions and saw an overall increase of 50% Return on Ad Spend on search advertising,” reports Senn.
3. By providing hands-on training and practical data management products
One way to effectively manage data is to avoid overload, says Senn, adding that it’s when tool sets are not consolidated and the infrastructure is not well-defined that metrics spiral out of control. “Reaching 2,000 to 3,000 metrics will make it impossible to make meaningful decisions,” she says.
Sparkline provides Digital Maturity and enablement programs for businesses—from start-ups to mid-sized SMBs and large enterprises—to grow skills in-house and provide the right infrastructure for future growth. “Organizations need the right skills to analyze data for insights to drive decisions across marketing, product, user experience, and customer behaviors. Training and mentorship are essential,” she says.