Infinite Analytics, Inc. is a Big Data & Social Data Analytics Company. Its flagship Personalization Platform provides an advanced personalization engine for the web. It creates a Social Genome of a user, based on the user’s structured and unstructured data on the social networks, uses NLP, Machine Learning and predictive analytics to predict user behavior for e-commerce, media and content, travel and enterprise businesses.
Infinite Analytics has a super team from MIT with over 70 years in e-commerce and technology, along with advisors in Sir Tim Berners-Lee – the inventor of the World Wide Web and Deb Roy – Chief Media Scientist at Twitter.
In an interview with Analytics India Magazine, Akash Bhatia speaks more about his company.
AIMAnalytics India Magazine: What are some of the main tenets (philosophies, goals, attributes) of analytics approach and policies at your organization?
ABAkash Bhatia: Our philosophy is: Big Data is impersonal. Insights make it personal.
We are data hogs. No data is small for us. Any data source that allows us to push the envelope on personalization even a tad further is valuable.
Simplicity is key. Whether in implementation, or in visualization, if it is not simple enough to understand quickly, then we are not trying hard enough.
AIM: Can you brief about some of the services you provide?
AB: Infinite Analytics has two products – Personalized Recommendation Engine and Infinite Insights.
The Personalized Recommendation Engine
We create an e-commerce customer’s 360 degrees profile based on the user’s social graph, and use predictive analytics on the genome to provide personalized news and content recommendations to these customers.
Using Social Analytics, we are able to predict the following for both, individual users and an aggregate of users:
- Brand Affinity
- Places and Venues
- Media Habits
- Brand Advocacy
You could call it – creating a segment of 1. This provides a complete insight into the user and his entire network as well as the most relevant recommendations to the user.
Our ability to merge multiple sources of fans data (Facebook, Twitter, Linkedin, Google +, Transactional Data, ClickStream Data) providing us a 360 degree profile of the user in our Personalized Recommendation Engine, along with constantly looking for new data sources to enhance user data (census data, etc) has led our clients to achieve 20-25% uplift in user engagement as well as gain tremendous insight into their users.
Based on our analytics of the 360 degree profile of the user, we provide our clients complete insight into their consumers. Everything that we talked about in the 8 points above, along with insights particular to their business is a part of the Infinite Insights product. This allows them to achieve other aspects of their business, like manage inventory, optimize media buying, supply chain, and the list goes on.
AIM: What are the key differentiators in your analytical solutions?
Our use of Semantic Technologies:
On the User side:
We create extensive relationships between different entities in a user’s profile – for e.g. the likes, interests, profession, education, etc
On the Product Catalog side:
Similar to the one on the user side, we use Semantic Technologies to create extensive relationships between the products in the catalog. This gives our algorithms a very good sense of the relationship between users and the products that they might be interested in buying.
It is important to understand both the customer and the product catalog before one can hope to optimize the experience for them.
Our ability to merge different sources of data for a superior customer genome – the Infinite Genome:
We are data hogs. We utilize every data source possible to provide that unique insight into the consumer. Our patent-pending algorithms merge this data so that the correct user’s data is processed across different data sources, to get us that unified view of the consumer, which is so essential in driving the analytics.
We take care of the Cold-Start problem:
Most personalization engines (whether in-house or off-the-shelf) take a long time to implement as well as a very long time to collect customer data and get started. That’s a huge opportunity lost to increase conversions.
Our cloud-based solution takes barely half a day to implement (shortest implementation time has been less than half a day and the longest has been 15 days), and our engine starts throwing out personalized recommendations from the moment it goes live. There is no waiting period, no collection period. We are able to drive up conversions for our clients right from day 1. That’s added revenues right away.
Snappy/ Ease of Implementation:
As mentioned earlier, our implementation is very simple. We have a cloud-based solution. Our clients can choose either a server-side implementation or a client-side implementation. They do not need to maintain a data analytics team, and even for the implementation, all we need is one engineer to do the needful at their end, for that half a day and we are good to go. Everything else is maintained/handled by us. Our shortest implementation has taken less than half a day, and our longest implementation has taken 15 days.
AIM: Please brief us about the size of your organization and what is hierarchal alignment, both depth and breadth.
AB: We are a 9 person team, with operations in the US and India. All our data scientists sit out of our Cambridge/Boston office, which is right next to MIT. In India, we have two people, for Sales and implementation/infrastructure.
Akash Bhatia is the Co-founder & CEO of Infinite Analytics
Puru Botla is the Co-founder & CTO of Infinite Analytics
AIM: What are the planned next steps/ road ahead for your organization?
AB: The road ahead for us is to continue enhancing our flagship personalized recommendations product and our Consumer Insights product – Infinite Insights. Our quest for newer data sources continues as well. We are always on the lookout to explore new verticals that would require either of the products
AIM: What are the most significant challenges you face being in the forefront of analytics space?
AB: The challenge is in educating decision-makers about analytics. These days, anyone who can spell Hadoop feels they are a big data analytics shop. How do they distinguish between a genuine analytics company and someone who just provides reports/ data mining, or even a social listening tool.
AIM: How did you start your career in analytics?
AB: Having come from my earlier start-up, KyaZoonga (www.kyazoonga.com), where we use a lot of analytics, to figure optimal ticket pricing or even discounts and offers and customer segmentation. Everything was analytics driven, which spurred my interest in data and the insights that it can provide.
In 2011, while at MIT for my MBA, my co-founder and I took a class with Sir Tim Berners-Lee, the inventor of the World Wide Web. We built a prototype of what would eventually become our product – the Infinite Genome, in the class. Sir Tim thought it was one of the best in the class, and so we decided to take it from a class project to a startup. Thus began my journey with Infinite Analytics, and big data analytics, in general.
AIM: What kind of knowledge worker do you recruit and what is the selection methodology? What skill sets do you look at while recruiting in analytics?
AB: Our recruiting process is very stringent. Since analytics is core to us, our focus is on hiring data scientists. Our data scientists are athletes – who mine, scrub, analyze data, write algorithms, write code, and build the product. Hence, those are the kind of skills we look at while hiring in our analytics team. Can you think through a problem? Can you quickly hack through a problem? Do you have the aptitude and the attitude to approach a problem differently and quickly? Can you take a dataset, build an algorithm, code it, deploy it, and test it, all by yourself?
We have a very lean team, and every one pulls their weight in the company. Even our sales/biz dev people can quickly implement an HTML site or create images at the very minimum, without having to wait for some engineer/designer to provide that support to them.
Sir Tim Berners-Lee with the Infinite Analytics team at the Boston office
AIM: How do you see Analytics evolving today in the industry as a whole? What are the most important contemporary trends that you see emerging in the Analytics space across the globe?
AB: Analytics, and especially big-data analytics, is still very nascent. With so much data being generated every single day, with the Internet of Things on the anvil, we have barely scratched the surface on what stories data can tell us. Every device is generating tremendous amounts of data. How does one link all of this data that is being generated to tell us something meaningful, is what the race is going to be all about? Can we use Semantic Technologies and Linked Data Technologies to integrate these data sources? And if the Indian Government adopts Open Data practices, similar to that in the US (www.data.gov), then a whole new set of analytics and application can be built which will then provide more and more data for more and more apps and analytics.
The ability to link and merge all these massive data sets and to provide actionable insights along with the action into a product, rather than a service, is going to be the most important trend emerging in the analytics space.
AIM: Who do you think your main competitors are?
AB: We are the only company to provide a personalization and analytics product based on such varied data sources. Other companies provide recommendation engines that only use the clickstream data and transactional data of the client to provide recommendations. Some companies are focused on providing analytics services, but that’s not an area we are focused on.
AIM: Anything else you wish to add?
AB: We are Data Hogs. Our platform acquires and synthesizes billions of data points about a user which allows us to bring in a multi-dimensional view of the user and thereby offer advanced personalization.