Set up by an ex-Google employee, Reflektion’s customer data and insights enable businesses to influence customers at every relevant point of engagement.
It may be the time of mobile phones and apps, but business websites are often the primary point for prospective customers to gather information.
There are ad-tech companies that track why people visit a particular website and target them with relevant advertising. However, this form of technology is relevant to a media or publishing company. What about businesses keen to understand the profile of traffic coming to their website and convert them to prospective leads? Think about it like a customer relationship management tool at the intent level. Businesses can today plug in software that profiles customer intent upon arrival on the landing page of the website.
Sounds like Google, doesn’t it? This very business-to-business platform was built by Amar Chokhawala, a 42-year-old former employee of Google. Amar worked in the internet behemoth for 11 years and his experience in building Gmail and Google Adsense made him understand that businesses do not know what to do with the traffic coming in to their website. He used the best lessons in search, intent and tracking technologies, from his Google days, to create Reflektion.
Reflektion uses AI to predict the intent of customer and converts him/her into a prospective business lead. The company has raised $29 million and has more than 60 customers.
Amar is a pensive and no-nonsense entrepreneur. Always gauging intent, he was interested in knowing how YourStory personalises content for readers. Like most businesses in the Bay Area, he has reference customers and lets his work do the talking.
“You have to be on the money in Silicon Valley; it is very competitive and you have to be the best,” Amar says.
The company has 60 reference clients who swear by the Reflektion engagement platform.
Fashion to Figure, the 15-year-old retailer focused on women’s apparel, selected Reflektion’s individualised commerce solution to analyse each customer’s website interactions in real time, interpret a woman’s actions as expressions of their personal preferences and present contextually relevant products.
“Fashion is a state of mind, not a size range. With Reflektion providing us even greater insight into each of our customers, we’re able to be even more effective at helping each woman express her individual style,” says Nick Kaplan, COO and co-founder of Fashion to Figure.
To tell you how Reflektion works, one must look at how the Fashion to Figure team used the product. The F2F team included individualised product recommendations on its homepage, category pages and product pages. It also integrated a highly visual search experience on its site that actively previews individually relevant products as a shopper types in the search box. Finally, they optimised and personalised their mobile shopping experience to accommodate shoppers on the go.
Fashion to Figure’s online shoppers are now greeted with a variety of fashion options upon arrival, and with each click the site responds by prioritising the most relevant products for each individual’s preferences and intent. After only a few clicks, women are essentially standing in a virtual aisle where everything is tailored to their unique needs – whether it’s a formal dress or on-trend casual wear. Once a guest has settled on her style, the site proposes coordinated accessories to complete her look – be it patent leather purses to go with that sleeveless floor-length dress she’s selected or gladiator sandals to compliment her faux leather shorts. And best of all, each time the women return to the site their preferences are remembered, understood and immediately reflected in the experience they receive.
Amar says: “When I set up the company in 2012, I was keen on a platform that can automate experiences by looking at patterns. Data appealed to me because of Google.”
He says the cloud was the single most important change in making AI technologies prominent.
“We all know the internet allows a lot more personalisation. But engagement was always missing and that’s what we do,” he says.
Ninety percent of the web traffic is on FANG stocks, which is nothing but Facebook, Amazon, Netflix and Google. But, there is a lot of traffic on business sites, which go without being monetised.
“Decision making was the key and humans cannot handle so much data,” Amar says.
Amar has two patents filed in his company and he invested $1 million of his own money before raising money from investors. Today, he leads a team of 75 members.
Reggie Bradford, senior VP of Oracle Startup Cloud Accelerator, says, “If a business scales to having reference customers and generating revenues then it is testimony to the good technology and the team that the entrepreneur is able to bring together.”
Just 20 years ago Amar was an engineer who had studied computer engineering at NIT-Surat. He says his stint at Google, in the US, made him think about technology, data patterns, numbers and inspiring team members.
He concedes that all that learning and being challenged for 11 years to build great products led to the formation of Reflektion in 2012.
“I have realised what it means to build a business. Your technology has to make good margins; wafer-thin margins can hurt if the volumes drop,” he says.
A startup must remember to make money by focusing on the product that solves audience needs. The FANGs do precisely that.
“You constantly think about what next and build things that work. You must learn constantly,” Amar says.
He says there are at least 15,000 businesses he is going after and that his company is going to be the predictive platform for businesses that want to understand data to convert visitors into prospective customers.
That’s quite a task, but Reflektion seems well up to it.