Imagine that you want to run a marketing campaign targeting your active customers with personalized recommendations. As described in earlier blog posts on this site, you have multiple options on what recommendation strategy to adopt: talk about their favourite...
Deploying predictive models, and why the modelling algorithm is perhaps the easiest aspect of the problem. Predictive models, specifically propensity models, are a staple of data science practice across organizations and verticals. Be it to understand whether a...
In our previous post, we spoke about how various recommender algorithms work, and why the nature of the data suggests what might work for whom. But having a good list of personalized recommendations is only half the battle. So what’s the other half? Imagine picking a...
The problem of personalizing customer engagement can be broken down into three broad problems: Recording how customers engage with the brand: the most obvious aspect of this is a transaction, but non-transactional signals such as web/app behaviour, service-related...
Businesses, nowadays, are increasingly relying on advanced technologies to enhance their revenue generation strategies. Amid these technologies, recommender systems have emerged as powerful tools that not only improve customer experience but also significantly impact...
