Being a giant has its perks. You can invest in technology your competitors can only dream of. One such tech is personalization, that is, utilizing personal data to modify a person’s experience of using the site with the aim of making him buy more stuff.
Building such capabilities from scratch doesn’t just need web development knowhow. You need to be well-versed in data analytics and consumer behavior. These things are out of reach of small online retailers and offline brands venturing online.
But startups are now rushing in to fill this gaping hole. One of them is Linkcious, a Singapore startup founded by serial entrepreneur Weichang Lai (disclosure: Lai owns a tiny amount of equity in Tech in Asia) and computer engineering fresh grad Jason Tan. Both own an equal stake in the company.
Linkcious offers users a product recommendation widget which users can embed onto their websites. It allows online retailers to save thousands of dollars in development costs and drastically shorten deployment time.
The product promises to boost a user’s bottom lines through contextual recommendations. In other words, it crawls the content on the page you embed the widget, and then recommends products based on that. Soon, it hopes to factor in user interactions, such as which ads they click on.
Lai developed the product to meet his own business needs. He runs Otaku House, an online and offline retailer selling Japanese toys and oddities. And like many ecommerce companies, he ran into a brick wall.
“There was no way for small merchants to show related products beyond putting them into categories. So we built one in-house. It works very well, and it dawned upon me that we can spin this off. That was two years ago, and we took our time to develop this,” says Lai.
Linkcious has received a small grant from the Singapore government’s iJAM program to speed up development and prove the concept. It’s now beta testing with a few businesses ranging from a few hundred stock-keeping units (SKUs) to hundreds of thousands.
Welcome the competition
It needs to move fast. At least a couple of other startups in the region are also launching their own personalization engines. In Malaysia, Predictry has begun running trials and raised US$230,000 in seed funding from the Malaysian Development Corporation (MDeC).
While some firms are charging US$30,000 to implement recommendation widgets, Predictry founder Seng Teong Chua, who did global business development at Rebate Networks, contends that he can do it for much less, since older players have sunk a lot of money into legacy infrastructure and as a result need to charge more to recoup costs.
Chua isn’t always going after the biggest clients. “Essentially, I want to make sure that at first, these sites have enough click-through to survive,” he said in a previous interview with Tech in Asia. “So my strategy is quite different: I’m focusing more on mid-sized players, rather than concentrating on the top five ecommerce firms out there.”
India’s TargetingMantra has also spotted a similar opportunity. Started by a group of ex-Amazonians and backed by investment firm 500 Startups, the company is perhaps the closest to understanding Amazon’s secret sauce.
After all, co-founder Saurabh Nangia was part of the team that put together a recommendation engine for Amazon’s subsidiaries – IMDb, Lovefilm, Audible, Shopbop, and Zappos.
Using machine-learning algorithms, TargetingMantra can learn a buyer’s shopping behavior and recommend products to the person. It is highly customizable, taking into account the needs of different ecommerce categories and the preferences of business owners.
Personalization-as-a-service is still in an early phase. These three companies were founded in 2013 and after, just when ecommerce in Asia is about to take-off. Some of these startups have not even finalized their pricing yet.
While online retailers big and small are the stars of the show, a plug-and-play ecosystem of support services like recommendations and logistics will play a crucial role in giving merchants an immediate boost at the starting block.
It’s outsourcing on steroids: in the long run, the cost of relying on a third-party may not differ much from building in-house, but it means not needing to manage the extra server load, troubleshoot, or reinvent the wheel.
Empowering the smaller players levels the playing field, and gives hope that the likes of Amazon and Alibaba do not concentrate enough firepower to bulldoze over merchants with onerous contractual terms.
As ecommerce gains in prominence, more than an elite few should be able to reap the rewards.