Driven by the motto of ‘Big on Data Science,’ the company extensively leverages data from multiple touch points and clubs it with ‘deep learning tools’—an emerging trend in data science—to extract value from the massive volumes of data. When applied in social media analytics, this technique can exploit the untapped potential from messages, photos, and videos that consumers upload and share every day. “The Artificial Intelligence component in our solutions revolutionizes social media marketing by improving content personalization, social listening, predictive ad targeting and others,” says Kirillov. “This makes us different from competitors who do simple social listening and don’t implement advanced analytics in their products,” the CEO adds.
InData's platform for social media analytics, MoneyGraph uses statistical algorithms and scalable machine learning to predict demographic data, income and interests of social media users. This kind of data has found application in various business areas including CRM enrichment, marketing, credit scoring and recruiting. Organizations use MoneyGraph to know their customers, measure and improve their social media marketing efforts, complete their CRM system with social graph data and create innovative apps based on social data insights.
We use data science techniques to analyze social media data that brings deeper insights and understanding to customers
InData Labs’ client, Captiv8—an online marketplace, where top social media influencers connect with brands, can be portrayed as one of the best examples of InData’s effective data management solutions. MoneyGraph fulfilled Captiv8’s requirement for a social media analytics platform in a cost-effective and timely manner. The company also helped the client to build an advanced analytics platform for Instagram, Vine, and Twitter. MoneyGraph powered the real-time analytics on the platform and brought powerful insights into social media user behavior, from Instagram, Vine and Twitter. This provided the client with a superior analytics and marketing view.
Adding to these capabilities, InData’s next-best-action marketing tool, SNIPE uses sophisticated data mining models to identify customer micro segments and to recommend the next best offer for each customer segment. “SNIPE is highly flexible and includes an extensive selection of filters, automated and manual categorization capabilities and alerts,” says Kirillov. Upon integrating SNIPE with CRM systems, organizations can gather automated reports on a regular-basis that are easy to setup in order to save valuable time.
“Our strength is our team that possesses business acumen, engineering, and data science skills to bring deeper insights and understanding to our customers,” extols Kirillov. In collaboration with academia, InData’s data science laboratory engages the most talented students and mathematicians. “In an era of Big Data, befitting our name ‘InData’, we take a very ‘deep look’ into data to generate valuable insights for our global clients helping them to solve their most critical business challenges,” concludes Kirillov