Gravity Labs

Gravity Labs is at the core of our commitment to innovation. It was established to harness the latest in technology breakthroughs to solve some of the world’s most complex and intriguing business problems. And we have deployed our best minds to the job.

Gravity Labs is led by an elite team of computer scientists and experienced business process architects with advanced degrees from the most respected universities who have published papers in international journals. They are that rare combination of visionaries, dreamers, and hardnosed pragmatists whose passion is to find elegant solutions to multi-dimensional business problems that drive strategic business value. And we put this brain trust to work.

At Gravity Labs, we work closely with our clients to understand their problems – complex challenges that they are unable to address with the generally available enterprise technology solutions. We bring to bear our expertise in a wide range of areas such as Machine Learning, Natural Language Processing, Algorithms, Information Retrieval, Statistics and Data Science to advanced coding using Java, Python, Spark, and Torch7, to come up with solutions that are game changers for our customers and result in measurable business outcomes.

Here are some initiatives in which we are helping our customers:

Company hierarchy set up and audit

Building accurate and complete customer hierarchy data is a common challenge for most enterprises. Third-party providers have limited parent-child information, which is often incomplete and inaccurate. We are solving that problem by crawling many publicly available sources of data as well as unstructured information from the Web to build accurate and complete relationships. Our engine runs continuously to capture vital information such as changes in company ownership, mergers, and acquisitions. The result is vastly more accurate customer hierarchy data leading to improved account planning and business outcomes.

Techniques and Methods used: Natural Language Programming, Machine Learning, Data Mining
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Applying data science to drive optimal pricing

Pricing decisions have a direct bearing on the top line and bottom line of companies. Products and services that are priced too high discourage sales; prices that are too low decrease profits. Studies show that objectively driven pricing can lead to between 2% and 7% improvement in profits. Despite the critical nature of pricing decisions, at many enterprises hundreds or even thousands of pricing decisions are made subjectively by customer-facing representatives with little to no insight into a customer’s willingness to buy at a given price. We provide pricing analytics solutions that offer insights into buying behavior. Using advanced data science we comb through a multitude of transaction history data to find patterns and correlations. Our analytics engine integrates with our client’s CRM or CPQ system to provide real-time analysis that sales representatives can use to arrive at the right price.

Techniques and Methods used: Data Science, Hadoop/Hive, Spark, MySql/postgre, R, Data Visualization

Managing contact data quality

CRM systems are only as good as their contact data. Enterprises often struggle to maintain accurate information about their contacts, and the lack of clean contact data can negatively impact sales and marketing. Our solution tracks a contact by detecting movement from one company to another; it auto-updates email addresses, infers derivative relationships and suggests increasingly granular and dense relationships between contacts and accounts. This constantly improving core data quality tool minimizes missed opportunities and reduces effort wasted on redundant sales calls.

Techniques and Methods used: Natural Language Programming, Machine Learning, Data Mining