Entries by vijay

The Case For Predictive Segmentation – Part 1 of 2

Retention & Growth marketers are often interested in taking action on a segmented base of users. Classic segmentation methods include Lifecycle based segments: new, active, lapsed etc. Behavioral segments based on user behavior on the website/app Demographic: Age, gender, location, household income, education based Traffic source based First purchase product/category etc. Given all these ways of […]

5 Essentials For E-commerce Push Notifications

Mobile commerce is growing much faster than ecommerce. Mobile apps are not only extending commerce beyond the desktop, but also enabling new e-commerce use cases like  on-demand services. However, e-commerce apps tend to have much lower retention than other categories like messaging apps. According to a study, e-commerce apps only have a 13% retention after 1 […]

4 tips for #CyberMonday

It’s that time of the year, when everyone in the Ecommerce world gets warm and fuzzy about delivering delightful savings to customers (and in turn, logging their biggest day of the year)! We have dug through tweets from 2013 to help you avoid tripping on Cyber Monday!   Do offer mobile deals Save Extra 5% […]

PREDICTIVE LIFECYCLE MARKETING – PART 2

In the previous post in this series, we had talked about the early evolution of predictive models for customer response and lifetime value. In this second part, we will talk about how marketers can improve or influence lifetime value through marketing campaigns or promotions. To determine the ideal target audience for a promotion, you could […]

Connecting Hive and Spark on AWS in five easy steps

Hive and Spark are great tools for big data storing, processing and mining. They are usually deployed individually in many organizations. While they are useful on their own the combination of them is even more powerful. Here is the missing HOWTO on connecting them both and turbo charging your big data adventures. Step 1 : […]

The A/B Testing Paradox

Has this ever happened to you: You ran 30 a/b tests over 6 months 20 of which showed an average lift of 2%, and you promoted the winning variant to show to the entire traffic base. Yay!! 10 of the tests did not show a lift over the base configuration, and you killed the variant […]

Predictive Lifecycle Marketing – Part 1

Predictive Lifecycle Marketing – Part 1 In a previous post, we had talked about the metrics that matter to the lifecycle marketer, and an approach to improving them. In that post, we outlined ideas for measuring metrics along the edges of state transitions, and creating experiments for improving the measured numbers. But what if you […]