Guesswork is a machine learning platform that predicts customer intent. It helps CRM and e-commerce companies use this knowledge to personalize product recommendations. Founded in 2013, the platform was launched this week and has three large OEM deals in the pipeline.
Guesswork was founded by Mani Doraisamy and Boobesh Ramalingam who have known each other since college days and have worked together for five years. They both have more than 14 years of experience in building technology platforms. Prior to founding Guesswork, Mani had co-founded OrangeScape where he created two rules engine platforms on the cloud – Visual PaaS and Kissflow. While building an app for understanding and responding automatically to customer feedback, they found that machine learning was ineffective – at least during the initial stages. They solved this problem by creating a rules engine layer on top of the machine learning algorithm and thus was born the idea for Guesswork.
Guesswork makes use of publicly available social data to build personas that reflect the customers’ individual preferences and interests. It is one of the most accurate machine learning platforms for predicting customer intent as their rules engine is optimized to understand customer profile and semantic meaning of customer inquiries. Further, it is built on top of the state-of-the-art Google Prediction API, which adds to their prediction accuracy.
Machine learning is now being adopted by companies other than Google and Facebook. However, it still needs huge investment. With Guesswork, CRM companies can integrate predictive intelligence into their product at a fraction of their investment in time and resources. Their main value proposition is that their learning engine is highly accurate and very easy to use and integrate, enabling CRM companies to go to market faster with this differentiated functionality. Its main competitors include Skytree and BigML.
Their early traction was through their contacts. Their beachhead was the CRM usecases that they built on Guesswork: auto-responding to customer inquiries, lead scoring, and newsletter and product recommendation for email marketing.
Their top target segment is SaaS-based CRM product companies. They plan to generate revenue by licensing their product. The pricing is determined separately for each customer based on the number of users and ML models. The average pricing range is 10% revenue share or $15,000/month.
The CRM market grew 13.7% to $20.4 billion in 2013. Excluding the top five (Salesforce, SAP, Oracle, Microsoft, and IBM), the market size is about $10 billion. Mani estimates the total available market (TAM) at $600 million assuming 60% market share * 10% OEM revenue * $10 billion.
They have bootstrapped the business using the $20,000 prize money they won in several hackathons that they took part in. As a winner of one such hackathon, they were invited to the Tata Communications accelerator at NestGSV, Redwood City, California during Nov ‘13 – Jan ’14. Karl Perkins, Chief Architect of Tata communications, advised them to take the platform approach looking at the potential of the technology. They also received a grant of $30,000 without diluting any equity.
Mani says they have currently narrowed their focus to predicting customer intent for CRM companies. By offering a vertical solution targeted at CRM product companies, they plan to accelerate adoption and acquire customers faster. In the future, once they have attained scale, they plan to make their platform available to other enterprise markets such as financial institutions, healthcare and other machine learning usecases where rules engine accuracy matters.
Mani says their ideal investor should understand OEM partnerships for technology products and help them scale. They plan to raise $1.5 million in the next 6-9 months to scale customer acquisition.
This segment is a part in the series : The 1M/1M Incubation Radar 2014