Pugmarks recommends content that you would love to read

As the world is considering data as the ‘new oil’ and ‘big data’ being the most talked about term these days; it becomes more relevant to understand data usability. Capturing or acquiring data isn’t a hurdle anymore but to make use of that data is the real challenge.

Content discovery is a hot area that has seen good recommendation products emerging globally. As readers, we always love to recommend a good book to our friends. Pugmarks is trying to emulate this experience for digital content. It is a product by Insieve, a content recommendation engine startup based in Bangalore.

Pugmarks’ plugin supplements readers as they browse and read stories. While reading a particular story, users are shown recommended content, ranked based on user’s social networks.

The Insieve platform has graduated from ‘intelligent sharing network’ that tries to understand what one shares within his or her network to Pugmarks, a simple content recommendation engine. Over the years, the team has iterated and tried different models to project using the same platform so that users enjoy seamless experience. It's a good example of how a team has iterated various models but still hasn't lost its core focus – content discovery.

The investors, Ojas Ventures & Blume Ventures, also need to be given due credit for believing in the team and letting them evolve different approaches around the same platform.

What does Pugmarks do?

Pugmarks learns from the content users read in their browsers. It first learns from users’ social network and recommends content to match their interests. These recommendations are served as reading cards that are delightful to consume on mobile devices too. So Pugmarks summarizes, learns, retrieves and renders content for users.

Pugmarks has a complex algorithm that picks useful nuggets from articles. These nuggets are embedded in reading cards, along with a link to the article. So, users do not always need to navigate to the article to figure out what it is talking about.

The ‘Read it later’ feature lets user save their reading cards and enjoy those cards later. Incase, users want to turn off recommendations from a specific site, they can use the ‘Mute’ option. These features are currently part of Pugmarks’ Google Chrome plugin and would be soon on their android app too.

Most content platforms consider ‘CTR’ (Click Through Rate) as the metrics to check the reach of the content. Pugmarks doesn't consider CTR as a metrics. It focuses more on users’ rating on the quality of cards. Users can rate the quality of card either by clicking on ‘Great recommendations’ or ‘Could be better’; the aim here is to ensure that users click on ‘Great recommendations’.

Currently, Pugmarks has close to a thousand active users across platforms. In parallel to the growing mobile user base trend, mobile install base is around 7 times the chrome extension base for Pugmarks.

Team

Founders of Insieve, Venkatesh Sharma and Bharath Kumar, are also the team behind Dhiti, a content discovery engine. They have been working on Insieve for 2 years. Bharath Mohan has a PhD in Information Retrieval from IISc and has worked with Google before starting Insieve. At Google, he was involved with Google News and has worked on text retrieval and ranking algorithms. Venkatesh has earlier worked with Veritas, NetApp, Sonoa, and Agami on scalable file systems and caching. His earlier involvement in critical projects like scaling of VxFS, High Performance Caching at Sonoa gives him a rich experience to bring to Insieve. Aditya Nagesh adds rich consulting and customer development experience to the team. He has prior experience in consultant and developer roles in SAP and is working on customer development at Insieve.

The prior experience of the founding team is a huge asset for the company. Their focus, now, is to work on the product experience to gain a larger and loyal user base. As of now, monetization isn’t big on their agenda.

How is it different?

One might confuse Pugmarks to be a competitor to Outbrain or My6sense at the first sight. Not really. Outbrain mainly caters to publishers who want higher CTR for their content from users while My6sense learns from user behaviour but again, helps publishers. Both these platforms don't recommend or appeal to end-users directly while focusing more on publishers. Pugmarks is a consumer product for those tech-savvy consumers who want content recommendations based on their interests.

Google Now might be termed as a close competitor for Pugmarks. Both these products aim to delight users with their recommendations. Google Now concentrates more on structured data (weather, flight timings, match schedules) while Pugmarks tries to use unstructured data (tweets, shares, blogs) to understand user context and push recommendations.

Privacy Concerns

While companies globally are undergoing huge privacy battles, it’s natural for users to feel worried about Pugmarks too. Pugmarks, like Google, learns from user’s reading interests. The reading history of users isn’t public and Pugmarks only stores the recently read articles history in its own servers. It scans user’s reading history to help translate it into better recommendations. Though privacy might be a concern for users, we feel the advantage the product offers should surpass these concerns.

Future Prospects

Currently, Pugmarks’ content recommendation is focused on user’s reading interests. Its recommendation engine is doing well with its content suggestions to users. Probably, the team shall focus next on structured data (location, calendar etc.), be available on multiple devices (iPhone, iPads) and try to engage with users on multiple touch-points (lockscreen, widgets, notifications etc).

Like Google, Pugmarks too pushes recommended content based on the user reading history it scans. It does sound similar to ‘Promoted Tweets’ or ‘Sponsored Stories’ but unless the product rolls such a feature, we will not speculate. “We shall think over this feature, when we are closer to monetization,” says Aditya, Co-founder of Pugmarks.

Is the contextual search and recommendation market heating up?

Content discovery is definately the future of mobile search. Big players like Google, Facebook and Yahoo are already working on this problem with varied approaches. While few are trying to build technology with in-house talent others like Yahoo are acquiring critical talent and technology to reduce their efforts. Last year, Yahoo acquired content discovery and sharing website Snip.it, but its services have been shut down.

One can’t forget the acquisition of the Washington Post by Jeff Bezos; it would be amazing to see someone like Amazon use content search and recommendation engine with content online to suit user’s needs and interests.

Would you subscribe for recommended content, based on your interest? Tell us in the comments below.