Rapid Notifications
Personalization

Aampe creates thousands of combinations from one message to personalize the copy, timing, and channel for your customers.

How does it work?

Aampe is quick to setup
1

Connect your system

Aampe offers easy integrations with several messaging providers. See documentation.

2

Tag KPIs

Add the KPIs you want to influence.

3

Craft copy

Get 100’s of messages in minutes with Aampe's message composer

4

Press GO

Aampe automates message sending across channels and iterations based on personalization.

Aampe has a different approach

Automated, not manual

Aampe sends messages automatically based on each new learning and insight.

Results that matter

You control the KPIs to track and Aampe will maximize your lift based on ongoing customer behaviors.

Copy that iterates itself

Provide a base message with snippets and Aampe creates thousands of personalized iterations

Understand real behavior

Go beyond “message click” to understand if you’re driving deeper actions

Features

Create personalized content faster than ever before

Create a message, choose and tag a few alternatives, and Aampe will put together all iterations and dynamically personalize messages. It selects which message to send based on a deep, iterative understanding of user behavior, so customers who are sold by offers while returning home in traffic don't get messages promoting value propositions during lunch.

Select audiences, set
limits - you’re in control

Set up what you want and when you want it. Don’t want app audiences to get web-focused texts? Aampe follows those limits and automes the send, iterations, learnings, and results tracking.

No manual A-B Testing

Aampe sends thousands of iterations to millions of customers, automating which message to send each minute. You can track messages, customers, and responses in real time.

Get insights, not only data

Select the exact KPIs you want to track, the events that matter. Aampe will target that lift and share results, in reports that make sense across your company.

See how Aampe better serves customers, from
repayment to engagement

Case studies
Problem, solution, findings
MXPlayer - Video Streaming

Video engagement in an ad-supported platform.

Background
MX Player is a video streaming and on-demand platform with over 280 million users globally. The platform operates on an ad-supported model and has a streaming library of over 150,000 hours across 12 languages.
Problem
Users have constant competing demands on their attention, and no user, no matter how engaged, can sift through 150,000 hours of content to find what they want at the current moment. The app needed a way to learn when to reach out to users to entice them to use the service.
Solution
Result
Total watchtime increased by over 2% among users whose notifications were managed by Aampe. That is over 500,000 hours of additional watch time. Watchtime for already active users increased by an average of 35 minutes, and notifications led to an average of 12 additional days of app usage per user per month.
Problem, solution, findings
Zalora- E-Commerce

Fashion and lifestyle offerings.

Background
Zalora is Asia’s leading online fashion, beauty and lifestyle destination, and one of the region’s pioneer large scale ecommerce platforms. It attracts over 50 million visits per month from customers who discover authentic products from over 3000 brands in apparel, shoes, accessories, beauty, and lifestyle products.
Problem
In ecommerce, the path between discovery to purchase has many stopping-off points, such as adding to a wishlist or adding to a cart, where users can indicate their intent without actually committing money. These are opportunities to reaffirm value and incentivise conversion, but only if the platform can reach the customer with the right calls to action at the right time.
Solution
Result
Aampe notifications driven by personalized preference scores lifted add-to-wishlist events by 15%, add-to-cart events by 14%, and checkout events by 12%.
Problem, solution, findings
ZestMoney - FinTech

Accessible consumer lending and money management.

Background
ZestMoney is the largest and fastest growing consumer lending fintech company in India, meaningfully improving the lives of more than 300 million households. The platform uses mobile technology, digital banking and artificial intelligence to put customers in touch with lending partners and manage their credit for them.
Problem
The platform’s users are expected to pay an installment on their loans each month. ZestMoney faced the problem of increasing ontime and early repayments.
Solution
ZestMoney used Aampe’s Composer to quickly generate over a thousand unique repayment reminder notifications emphasizing different unique financial motivations and value propositions, from a customer’s credit score, to future financial success and rewards. Aampe’s personalization models identified customer preferences, values, and optimal calendar cycles to send messages that best prompted customer action.
Result
The average month-over month change in early repayment rose by 9.75%. The average total early repayment in 4 months of using Aampe was 23% higher than the average for the 3 months previous.
Problem, solution, findings
Charge Running - Fitness

Engaged fitness with real-time feedback and on-demand classes.

Background
Charge running offers live audio running classes for every experience level. A variety of on-demand runs offer specialized focus areas and track user stats, allowing users to compete with past runners. Each class caters to the user’s own experience level.
Problem
Every Charge user rus for different reasons and on different schedules. They continually adjust their habits and schedules to the world around them, so static segments and standardized user journeys aren’t enough to get a motivating message to the right person at the right time.
Solution
In just the first month of using Aampe, Charge Running expanded its push notification template library from a few original templates to hundreds of personalized messages. This allowed Charge Running to consolidate user messaging preferences into personalization scores that summarized the probability of each user reacting to a particular message received at a particular time.
Result
Aampe lifted app engagement by over 200% - and that lift held consistently for multiple weeks - just from creating personalized content and learning how users preferred to be contacted.
Problem, solution, findings
CoLearn - EdTech

Personalized and engaging learning - on-demand or live.

Background
The CoLearn mobile app is revolutionizing math education in Indonesia. From making it simple to ask questions, to creating practice material, to offering live tutoring sessions, the CoLearn app keeps its users engaged and learning.
Problem
With more than 250,000 videos, plus homework help, CoLearn faced the challenge of guiding users to the content they would find most engaging, when they are most apt to study.
Solution
Aampe seamlessly matched CoLearn’s video CRM with its first-party app user data to generate thousands of personalized notifications. Aampe’s algorithms then used that matching to learn fully personalized timing preferences for each CoLearn user, and delivered a personalized notification, at the precise moment that user was most likely to engage.
Result
Best performing notifications were 70% more effective than no messaging. The app saw a 9% increase in overall user retention after the first week, and maintained a 6% increase after the second week.
Problem, solution, findings
MXPlayer - Video Streaming

Video engagement in an ad-supported platform.

Background
MX Player is a video streaming and on-demand platform with over 280 million users globally. The platform operates on an ad-supported model and has a streaming library of over 150,000 hours across 12 languages.
Problem
Users have constant competing demands on their attention, and no user, no matter how engaged, can sift through 150,000 hours of content to find what they want at the current moment. The app needed a way to learn when to reach out to users to entice them to use the service.
Solution
Result
Total watchtime increased by over 2% among users whose notifications were managed by Aampe. That is over 500,000 hours of additional watch time. Watchtime for already active users increased by an average of 35 minutes, and notifications led to an average of 12 additional days of app usage per user per month.
Problem, solution, findings
Zalora- E-Commerce

Fashion and lifestyle offerings.

Background
Zalora is Asia’s leading online fashion, beauty and lifestyle destination, and one of the region’s pioneer large scale ecommerce platforms. It attracts over 50 million visits per month from customers who discover authentic products from over 3000 brands in apparel, shoes, accessories, beauty, and lifestyle products.
Problem
In ecommerce, the path between discovery to purchase has many stopping-off points, such as adding to a wishlist or adding to a cart, where users can indicate their intent without actually committing money. These are opportunities to reaffirm value and incentivise conversion, but only if the platform can reach the customer with the right calls to action at the right time.
Solution
Result
Aampe notifications driven by personalized preference scores lifted add-to-wishlist events by 15%, add-to-cart events by 14%, and checkout events by 12%.
Problem, solution, findings
ZestMoney - FinTech

Accessible consumer lending and money management.

Background
ZestMoney is the largest and fastest growing consumer lending fintech company in India, meaningfully improving the lives of more than 300 million households. The platform uses mobile technology, digital banking and artificial intelligence to put customers in touch with lending partners and manage their credit for them.
Problem
The platform’s users are expected to pay an installment on their loans each month. ZestMoney faced the problem of increasing ontime and early repayments.
Solution
ZestMoney used Aampe’s Composer to quickly generate over a thousand unique repayment reminder notifications emphasizing different unique financial motivations and value propositions, from a customer’s credit score, to future financial success and rewards. Aampe’s personalization models identified customer preferences, values, and optimal calendar cycles to send messages that best prompted customer action.
Result
The average month-over month change in early repayment rose by 9.75%. The average total early repayment in 4 months of using Aampe was 23% higher than the average for the 3 months previous.
Problem, solution, findings
Charge Running - Fitness

Engaged fitness with real-time feedback and on-demand classes.

Background
Charge running offers live audio running classes for every experience level. A variety of on-demand runs offer specialized focus areas and track user stats, allowing users to compete with past runners. Each class caters to the user’s own experience level.
Problem
Every Charge user rus for different reasons and on different schedules. They continually adjust their habits and schedules to the world around them, so static segments and standardized user journeys aren’t enough to get a motivating message to the right person at the right time.
Solution
In just the first month of using Aampe, Charge Running expanded its push notification template library from a few original templates to hundreds of personalized messages. This allowed Charge Running to consolidate user messaging preferences into personalization scores that summarized the probability of each user reacting to a particular message received at a particular time.
Result
Aampe lifted app engagement by over 200% - and that lift held consistently for multiple weeks - just from creating personalized content and learning how users preferred to be contacted.
Problem, solution, findings
CoLearn - EdTech

Personalized and engaging learning - on-demand or live.

Background
The CoLearn mobile app is revolutionizing math education in Indonesia. From making it simple to ask questions, to creating practice material, to offering live tutoring sessions, the CoLearn app keeps its users engaged and learning.
Problem
With more than 250,000 videos, plus homework help, CoLearn faced the challenge of guiding users to the content they would find most engaging, when they are most apt to study.
Solution
Aampe seamlessly matched CoLearn’s video CRM with its first-party app user data to generate thousands of personalized notifications. Aampe’s algorithms then used that matching to learn fully personalized timing preferences for each CoLearn user, and delivered a personalized notification, at the precise moment that user was most likely to engage.
Result
Best performing notifications were 70% more effective than no messaging. The app saw a 9% increase in overall user retention after the first week, and maintained a 6% increase after the second week.
Security and Privacy

Your customers, your data

Aampe takes security very seriously, and we take your user privacy even more seriously. The best way to be secure in our data industry is to never store data that we would regret losing or cause a problem for our customers. An integral part of working with Aampe is making sure that we filter out any sensitive or PII data before we store it. We have a dedicated security point-person you can reach at security@aampe.com for any specific questions. We are committed to privacy and you can see our statement of responsibilities here.

KPI Manager Aampe
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get@aampe.com

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