Software Marketing Advisor Blog

When we think about data science, we think of a mythical laboratory where scientists are feverishly crunching numbers to provide a clear quantitative view of the future. We’ve been sold on the idea that these transformative findings will unlock increased performance numbers. Large companies hire teams of academics to sift through their massive repositories of data, believing in data science as it is currently described: academics doing glorified business intelligence.

Startups and small businesses must take a drastically different approach if they want to see real value.

For startups, data science should not be seen as a separate scientific initiative but as an integrated part of the product. Speed and efficiency are key factors to burgeoning companies; hiring and building out a team of data scientists, or more aptly named “data product engineers,” is paramount. Once you accept that data science is about building data products, you will see that…

We’ve all heard the term pivot by now. When a startup isn’t working out, it’s time to try something different, thus the concept of pivoting to a new idea. What most people don’t know is that a large number of successful startups became successful after doing a pivot. I was reminded of this again a few days ago when Alan Dabbiere, chairman of AirWatch, spoke at the (co) lab summit. Both of Alan’s huge successes were pivots:

• Manhattan Associates (NASDAQ:MANH – Market cap of $1.8 billion) – Started out as a solution for printing packing slips in warehouses and eventually pivoted into supply chain software
• AirWatch (raised a $225 million series A round in early 2013) – Started out doing WiFi management for a restaurant chain (Panera Bread) and eventually pivoted into mobile device management software

On the personal front, Pardot started out as a pay-per-click lead…