Aampe for e-commerce apps: connecting in-app events to the bottom line
Transactional apps, and particularly e-commerce apps, present a unique opportunity to very precisely determine ROI – how much an app needs to move the needle in order to justify the cost and effort it takes to engage users. Aampe boosts targeted in-app behaviors Here’s something we recently did for one of our e-commerce customers: The […]
Is optimized messaging really worth it?
So someone like Jim Laurain drops into your DMs. You already follow all the industry best practices, but Jim says there’s a better way. Well, yeah, there’s always room for improvement. Everyone knows that. The real question is: how much upside can you potentially see from making your messaging better? This can be a hard […]
The hidden costs of canvas journey builders
We have often heard that campaign and journey visual builders (e.g., Braze’s Canvas feature) are attractive features in conventional CRM and CEM platforms. But having paid close attention for a long time, we’ve observed that the most enthusiastic marketers are the ones that haven’t used the Canvas-type builders extensively. More importantly, we noticed that lifecycle […]
“How do I know it works?” A (somewhat) technical explanation of Aampe’s learning systems
A while ago, we released A User Story, an explanation of our Aampe’s algorithms, told in the form of a storybook. We wrote A User Story because we wanted anyone, from any background, to be able to understand our systems well enough to comprehend why they work. Now we’re releasing “How do I know it […]
Drop Last Touch Attribution: How Machine Learning is Changing Marketing.
Attribution is the practice of assigning credit to different marketing channels or touchpoints that contribute to a customer’s conversion. The goal of attribution is to understand the effectiveness of various strategies in influencing consumer behavior. Last-touch attribution is the default attribution offered in Google Analytics, though GA also offers other formats such as first-touch, “position-based” […]
Markov models vs. Naive Bayes: How to scale propensity models for in-app behavior and retention
The world of marketing has a bit of a love affair with Markov models. Attribution is a really important topic in marketing, and Markov models have allowed marketers to move past first-touch/last-touch attribution and other similarly simplistic heuristics. So when people find out Aampe uses propensity models to enable more intelligence targeting, they often ask […]
Solving model class imbalance through class construction based on coverage changepoints
This post is about a geeky model-training issue that has very substantial business impact. It’s about conversion events If you have an app, there’s lots of things you want your users to do, but for most apps there’s just one or two things that you really want your users to do. These are […]
New on arXiv: validating Aampe performance with adaptive synthetic control groups
When people start using Aampe, they naturally want to understand how the system is performing. And when they ask how the system is performing, they naturally understand that Aampe can’t take credit for every app visit, add to cart, or purchase that happens in close proximity to a message being sent. There’s a baseline level […]
How do I know Aampe is actually working?
Every day, Aampe sends out thousands of different messages across your user base, learns your individual user preferences based on who responds to what, and then automatically adjusts your messaging timing, content, and copy to fit those learned preferences. [Note: We also monitor your users’ activity after we send them a message, which allows us […]
Aampe + GPT-3: A power combo
When I first started looking to use GPT-3 as part of Aampe, I was skeptical. Two reasons: 1. Asking GPT-3 to write your customer communication is like asking Twitter to write your customer communication. Most of the time, it’ll be fine. Sometimes it’ll be surprisingly good – maybe even brilliant every once in a […]