Software Marketing Advisor Blog

Financial startups don’t have the cachet of a Tinder or Uber: instead of promising easy hookups or a revolution in urban transportation, they focus on mundane issues like credit scores. But they are having a moment in the sun all the same.

Thanks to technology and a new ecosystem that provides unprecedented access to the traditional lords of finance, so-called “fin-tech” is emerging in New York and elsewhere as its own class of startup scene — though it often looks little like the culture of Silicon Valley.

Big banks and outside entrepreneurs

The two-day Finovate event in New York this week saw dozens of fin-tech startups and entrepreneurs talking up their ideas for applying tech to a host of everyday financial operations: opening accounts, checking credit scores, serving risky borrowers and so on.

The scene was notable in large part because, a decade ago, startups focused on the financial sector barely existed.

“In the past, technical innovation always took place within incumbent firms and…

Your best prospects are people who have purchased from you before. They have already experienced the products you offer as well as the service you provide.

They know you, like you and trust you. (At least they did when they first bought from you… enough, at least, to give you their money.) Hopefully, things haven’t changed. And ideally, your relationship with them has improved.

Research shows that it costs around six times more to acquire a new customer than it does to sell something additional to an existing customer.

So, if nothing else, it makes good financial sense to attempt to sell your existing customers before looking outside for new prospects.

One of the best ways for doing this is to constantly keep in touch with them. Make it impossible for them to forget you. Let them know you really appreciate not only their business, but their friendship, as well.

Big data has become so big, it’s spread beyond the tech world. When 163-year-old publication New York Times hired a chief data scientist earlier this year, it became clear that even non-technical organizations were hopping on the big data train. To successfully predict what their customers want or how they might behave, companies that know how to mine big data — also know as companies who hire good data scientists — have the advantage.

To do their jobs effectively, data scientists must do a whole lotta dirty data work. The New York Times calls it “data janitor work.” In a recent article, NYT reported that data scientists spend from 50 percent to 80 percent of their time laboriously collecting and prepping data before it can be extracted into digestible insights.

“Data wrangling is a huge — and surprisingly so — part of the job,” Monica Rogati, VP for…