Omologist Incorporates DataForSEO APIs to Devise Bloomberg for Digital Marketers
“Our experience of working with DataForSEO has been fantastic at all levels. In particular, we have been blown away by the professionalism and help we have received from the support team. Not only are they quick to find answers to our questions, but more importantly, their knowledge of the product is what truly stands out. Being so proactive in building upscale data solutions, adding new services, and troubleshooting – that is something unseen among other data providers.”
Sean Cooney, Co-Founder & CEO of Omologist.com
Omologist is a digital marketing agency focusing on paid advertising. The team has a lot of experience working with retail, B2B, e-commerce, and industrial businesses around the world.
Knowing paid advertising first-hand, the company decided to build its own platform, a SaaS product helping digital marketers find the best-fitting channels for running ad campaigns, and better adjust their advertising strategies.
“Omologist is building Bloomberg for digital marketers”, says Sean.
While Bloomberg is supplying its customers with accurate information for decision-making in the world of finance, Omologist is developing an extensive platform similar to Bloomberg Terminal, but aimed at enabling digital marketers to make smarter data-driven decisions.
However, bringing up a comprehensive solution that would provide quality real-time data from a variety of sources is an immense scope of work. After carrying out the project estimation and planning, the company management quickly realized they needed a reliable data supplier.
Sean pointed out: “The key obstacle for us like for many companies is coding which has to be done well and also takes time and is complex”. This is particularly challenging when the aim is “not to just analyze this data but also provide insights, reporting, and tasks to be implemented on campaigns for digital marketers.” Among other important issues slowing down the development process, the company’s CEO mentioned “combining large data sets” and paying attention to the data quality.
As time and money are the scarcest resources for any enterprise, Omologist decided not to reinvent the wheel and look for ready-made solutions that would eliminate the complexities of dealing with data collection.