Alooma Lines Up Retail Data For Easy Analysis | PYMNTS.com

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Analyzing data is tough, but a lot of products and services have solved for that. When Alooma CEO and cofounder Yoni Broyde talked to retailers, he found that for most of them, analysis wasn’t the problem. The problem was getting all their data into one place first.

“Eighty to 90 percent of companies we spoke with were having trouble moving data and bringing it together in one place,” Broyde said. “Especially when dealing with cloud data or real-time data. There were solutions to deal with analyzing and visualizing it once it was in a data warehouse, but there were few solutions for connecting, enriching and streaming that data into data warehouses or analytics tools.”

TechCrunch explained the process that makes Alooma work: “The Alooma platform focuses on three problems: connecting to multiple data sources such as Cassandra, ElasticSearch, MySQL and many others without a lot of fuss; transforming and cleaning all of the data very quickly, then loading it into a data warehouse (right now that is mostly Amazon Redshift); and finally using the Python coding language to write business logic on top of the data.”

In a sense, the Israeli startup’s founders kind of came in through the back door. Instead of coming up with a brilliant data-processing concept and trying to market it, they went out of their way to create exactly what the market wanted. Six months and 150 companies out of their way.

“We felt we shouldn’t write one line of code before we understood the pain points customers were facing. We wanted to solve the biggest problems we could find,” Broyde said.

After they spent six months talking to retailers across North America and Europe, the founders built and launched the Alooma cloud service in 2013. PYMNTS caught up with Broyde to find out how it all came about. An excerpt of the interview is below.

PYMNTS: Can you explain the business?

YB: The Alooma Platform enables organizations to connect their disparate data silos in real time, for increased agility, decision-making and ability to compete.

PYMNTS: How does your business overlap with the payment processing or retail/e-merchant world?

YB: Our users are using Alooma to get real-time data from payment processing platforms, alerts on chargebacks or failed charges and aggregate business metrics.

PYMNTS: What’s the company culture like?

YB: We work hard to bring work-life balance to the typical startup lifestyle.

Since the company was founded, Alooma has always been centered on customers’ needs, from sales, to engineering and marketing. We thrive on customer input and our support organization maintains regular communication via Slack.

Our Redwood City office in Silicon Valley offers flexible work hours and days off to support a work-life balance. Teamwork and collaboration are the norm. We have an open kitchen stacked with food and snacks, indoor and outdoor games for rejuvenation, and open communication to foster transparency.

With the fast growth the company is experiencing, our mantra is work hard, play hard and have fun.

PYMNTS: To what do you attribute your success over the years?

YB: We experiment, make data-driven decisions and wake up every day excited to take on the next challenge and move Alooma forward.

PYMNTS: Looking back since founding, what has been the proudest moment for the organization?

YB: After two months of working with Invoice2go (one of Alooma’s first customers), we spoke with them and found out they had connected over 30 different data sources during that time and truly transformed their data-driven culture.

PYMNTS: Can you give me some personnel growth numbers?

YB: We started with three founders and have grown 1,150 percent in 36 months to over 40 employees. Today, there are more than 60 paid subscribers to the Alooma product.

PYMNTS: What is next? What does the future look like?

YB: First, enterprises will move their data center infrastructures from on-premises to the cloud at a faster rate in order to take advantage of its unlimited, on-demand storage and compute cycles. This allows companies to increase agility and speed.

Second, more and more retail companies will deploy the infrastructures and capabilities needed to use real-time data as a competitive weapon. A good example is Uber’s real-time pricing models, that charge riders higher fees when demand spikes.

Third, in order to support real-time data, enterprises will accelerate the transition from batch data uploads and instead continuously stream data to their data warehouses.

PYMNTS: Biggest hurdle? How did the company overcome?

YB: Scaling. Whether it is the product, individual team, and/or the company in general – scaling has been our biggest hurdle, but we experiment, adjust and work together to overcome scaling obstacles. We don’t see that as a hurdle that will ever truly go away, which is a good problem to have.