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Chart Mogul
Using Deep Customer Segmentation in SaaS
https://blog.chartmogul.com/deep-segmentation-in-saas/
User segmentation is an incredibly powerful tool in analytics and is critical for understanding the types of customers using your product, as well as targeting and measuring the impact of your customer success.
There are many platforms that support advanced customer segmentation, most of which provide their own built-in segments which act as a suitable starting point. To really get the most from such a tool though, you’ll want to create your own custom segments, based on as the most relevant data available for your customers.
With segmentation employed in the right way, you can answer the following questions and much more:
Which types of customer are most profitable for me?
Which marketing channels produce the highest value customers?
How can I better understand where my customers are losing their way in my onboarding process?
Which 20% of customers are using 80% of my customer support resources?
Facebook
#Facebook is using
#AI to help it better understand what content you like. Useaful for a
#DeepCustomerSegmentation
Facebook wants to improve your ad experience and is using AI to help it better understand what content you like
Mid-roll video ads, ads in Instagram Stories and ad experiments in Messenger are just the beginning.
BY
JAN DAWSON FEB 6, 2017, 3:00PM EST
How does this make any sense?
We found people generally believe that larger, more significant outcomes are less likely to happen than smaller outcomes. But the odds of the larger outcome happening seem even smaller when placed alongside the higher odds of the small outcome. For example, a 10% chance of winning a prize feels small already, but it feels much smaller when it is compared to a 60% chance of winning other prizes. As a result, people feel that they have less chance of winning an unlikely large prize, and that makes the whole sweepstakes feels less valuable.
Thus, adding prizes that make a sweepstakes objectively more valuable ends up decreasing the sweepstakes’ perceived value. Similarly, noting smaller side effects that make the drug objectively more dangerous can in fact make it appear less dangerous by making the larger side effect seem even less likely to happen. This biases us against taking positive risks and avoiding negative ones.
These results have wide-ranging implications for both marketers and policy makers. For example, public service campaigns often describe every single negative consequence of some dangerous behavior, with the hope that this will make it seem riskier. Our research suggests that this well-intentioned strategy can backfire. Showcasing a single large risk instead may deter dangerous behavior more effectively.
Along similar lines, marketers should consider highlighting a single large potential advantage of a product to generate greater sales, instead of highlighting that same large potential advantage plus smaller ones. Companies should think about how employees may be more motivated if their incentive schemes offer a single large payout rather than that same large payout in addition to incentives of lower value. In other words, when it comes to helping people evaluate risk, less is more.
including
Content Personalization
