How ScaleFrame unlocked social media insights at scale

Industry

AI and machine learning

Challenge

ScaleFrame needed to extract critical public data from complex, dynamic websites for the AI platform. Other scraping providers either couldn't deliver the required data or charged prohibitively high prices, while building an in-house solution was too costly and time-consuming.

Industry

AI and machine learning Link arrow

Challenge

Solution

SOAX scraper APIs

Results

Hundreds of thousands of dollars saved in development costs, and a significant competitive advantage in the industry through access to unique data and increased agility.

ScaleFrame’s requirements

ScaleFrame, an innovative force in the AI and machine learning sector, relies on public data from complicated dynamic websites (including video hosting websites) for sales prospecting research and to fuel its cutting-edge AI platforms. However, they required a reliable and cost-effective method to acquire this data.

ScaleFrame needed to find a solution that could handle dynamic content, large-scale data extraction, and anti-scraping defences at a manageable price point. Building custom infrastructure in-house would require at least one full-time developer, and would come with maintenance costs and bottlenecks.

"We knew we needed a scraping provider," explains CPO Ben S., "The problem was, other providers either didn't offer the capabilities we needed, or their pricing was astronomical."

The search for a solution

ScaleFrame evaluated over 20 different scraping providers, but none could match SOAX's data access, precise targeting, and competitive pricing. "The capabilities of the platform were much greater than anything we found anywhere else for the price point we were looking for," says Ben. "That combo of capabilities plus the pricing made it a no-brainer for us. We couldn't find that anywhere else."

How SOAX helped

SOAX's scraper APIs proved to be the perfect solution for ScaleFrame. With SOAX, ScaleFrame was able to target specific parameters on their target websites, giving them a level of access and control that other scrapers weren’t able to provide.

Finding SOAX’s solution allowed ScaleFrame to avoid a massive investment in building and maintaining their own custom scraping solution, saving significant time and resources. "It saves us the headache and significant cost," Ben explains. "We don't have to worry about building a solution, or the ongoing maintenance. SOAX handles all of that for us. For example, if a website changes their security measures to prevent scraping, it's not our team that has to go fight that fire. We have a team of people [at SOAX] that specializes in scraping and has been doing this for many, many years to fight that fire for us."

The outcome

Using SOAX to access unique data led to significant cost savings, estimated in the hundreds of thousands of dollars, by eliminating the need to develop an in-house scraping solution. "We would have had to hire at least one full-time developer if we hadn't found SOAX, which in the US, is well over $100,000." Ben notes.

Beyond the financial benefits, SOAX has provided ScaleFrame with a distinct competitive advantage. "We're able to scrape data that our competitors can't, or that they have to spend significant resources to get," Ben says.

SOAX’s scraper APIs gave ScaleFrame exactly what they needed:

Specific data points from complex dynamic websites that other providers couldn’t deliver at a reasonable cost
Advanced capabilities at a price point that made sense, saving ScaleFrame from spending over $100,000 a year on building and maintaining an in-house solution
Handling all scraping complexities and maintenance so ScaleFrame could focus on their business instead of worrying about platform updates or anti-scraping roadblocks.
Unique insights that competitors struggle to replicate, improving ScaleFrame’s market positioning.

How ScaleFrame unlocked social media insights at scale

ScaleFrame’s requirements

The search for a solution

Ben S.

How SOAX helped

The outcome

Transform your business with data