Billshrink Cuts Cell Phone, Credit Card Bills

billshrink-offices

Billshrink's spatious offices at Redwood City's port

A recession is the perfect time to launch an online service that saves people money; and that’s exactly what Billshrink is up to.

The Redwood City, Calif-startup mission is simple: save real money, right away from your cell phone and credit cards bills.

“With Billshrink you can save $300 to $600 from your cell phone service over 2-years and thousands of dollars on your credit card bills,” says Billshrink CEO, Peter Pham.

Billshrink analyses your behaviour to provide a highly personalised answer

How?

Download your mobile phone bill to Billshrink, enter your usage pattern (how many minutes you use per month, texting…) and the startup’s algorithm will find – out of 10 million combinations – the best service at the best price, with or without a new phone. “It’s highly personalised,” adds Pham.

Same thing with credit cards: enter your usage profile (do you pay your bill in full each month? are you looking for the lowest interest rate or you want to best rewards program?) and Billshrink gives you a selection of credit cards that fits you best.

“People could do that themselves with an Excel spreadsheet but it’ll take them hours. And then you would have to do it every month or so as terms change all the time. With Billshrink it’s just a matter of minutes and we send you an alert when there are rate changes, new services, etc,” says Pham.

More “verticals” to come

The venture-backed startup raised $8 million so far – which it said should be enough to take it to profitability – and has currently 8 employees with plans to grow to 10 this year as it adds more “verticals”.

“We’re looking at services with a lot of variables that make it hard for consumers to choose from, like cable bills, mortgages or car insurance,” explains Pham.

With 60,000 unique visitor a month, Billshrink’s business model is strictly based on revenue sharing with partners (mobile carriers and credit cards issuers) and doesn’t rely on advertising.

“We don’t want users to think that our algorithm is biased in any way,” says Pham.

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