AI Engine for App Developers and Marketers
A single optimization engine that uses AI to model, predict, and influence consumer behavior in order to maximize revenue, retention, and lifetime value for each specific consumer real-time.
AI-Powered Technology
Fueled with:
Machine Learning
Advanced Data
Visualization
Next Best Action
Recommendation
Next Generation
Analytics
Our goal is to make your advertising budget worth every penny by making more out of your already existing audience. They are there, why not make them come back more often and spend more with the power of AI?
Aiming to:
Retain Longer
Engage Deeper
Convert Further
Monetize More
AI-Powered Technology
Fueled with:
Aiming to:
AI-Powered Technology
Fueled with:
Aiming to:
Each consumer counts and we know this because we have analyzed and optimized tons of them.
Over the last 4 years we have integrated our technology into over 80 apps, systems, and data sets. wappier’s Intelligent Revenue Management platform currently analyzes more than two billion data facts per day from over 15+ million consumers. That’s how it’s getting smarter every day.
AI-Powered Technology
Leveraging AI to empower app developers and marketers to track and analyze their consumers’ actions, model their behavior, predict what they will do next.
Know your Audience
Descriptive Analytics: Who they are
Predictive Analytics: What they will do next
Prescriptive Analytics: What they should do next
ML-Based Data Visualization
Manage your Audience
Smart Audience Management:
Advanced Consumer Attributes
Dynamic Clustering
Pattern Identification
Optimize your Audience
Automated Loyalty: Next Best Loyalty Reward and Engagement Tactic
Pricing Optimization: Next Best Price and Offer
Know your Audience
Descriptive Analytics: Who they are
Predictive Analytics: What they will do next
Prescriptive Analytics: What they should do next
ML-Based Data Visualization
Manage your Audience
Smart Audience Management:
Advanced Consumer Attributes
Dynamic Clustering
Pattern Identification
Manage your Audience
Smart Audience Management:
✓ Advanced Consumer Attributes
✓ Dynamic Clustering
✓ Pattern Identification
Optimize your Audience
Automated Loyalty: Next Best Loyalty Reward and Engagement Tactic
Pricing Optimization: Next Best Price and Offer
The Process of Closing the Loop
Track, Analyze, Predict, Recommend, Assess.
Now, automate that.
Track
- Consumer joins
- Data start being tracked
- ML algorithms start being trained
Analyze
- Data are being analyzed
- Consumer behavior is modeled: ✓ retention curve, probability to buy, probability to churn, LTV, …
Predict
- Expected Consumer LTV is X
- Expected Next Best Tactic is Y
- Expected Next Best Time is Z
Recommend
- Platform computes and recommends consumer’s Next Best Action: ✓ Optimal Tactic ✓Optimal Channel ✓ Optimal Timing
Assess
- Consumer reacts to personalized recommendation which results in 30-50% performance increase
The Process of Closing the Loop
Track, Analyze, Predict, Recommend, Assess.
Now, automate that.
Track
- Consumer joins
- Data start being tracked
- ML algorithms start being trained
Analyze
- Data are being analyzed
- Consumer behavior is modeled: ✓ retention curve, probability to buy, probability to churn, LTV, …
Predict
- Expected Consumer LTV is X
- Expected Next Best Tactic is Y
- Expected Next Best Time is Z
Recommend
- Platform computes and recommends consumer’s Next Best Action: ✓ Optimal Tactic ✓Optimal Channel ✓ Optimal Timing
Assess
- Consumer reacts to personalized recommendation which results in 30-50% performance increase
The Process of Closing the Loop
Track, Analyze, Predict, Recommend, Assess.
Now, automate that.
Next Generation Analytics
Descriptive Analytics
Summarize History: What Happened and Why
- Summary Statistics
- Evaluating and visualizing the KPIs that matter the most:
✓ Retention
✓ Stickiness Ratio
✓ ARPU
✓ ARPPU
✓ LTV
✓ Time to 1st Purchase
✓…
Analyzing The Past
Predictive Analytics
Forecast Behavior:
What Will Happen
- Machine Learning
- What/If Scenarios (Counterfactuals)
- Predicting the most relevant consumer behavior:
✓ Purchase LTV
✓ Ad LTV
✓ Probability to Churn
✓ Probability to Buy
✓ Probability to Share
✓…
Predicting The Future
Prescriptive Analytics
Affect Future:
What Should Happen
Affect Future:
What Should Happen
- Convex Optimization
- Optimally sized and timed Next Best Action Recommendation:
✓ ML-Recommended Marketing Tactics
✓ Optimal Pricing
✓ Bundling
✓ CTA Optimization
✓…
Influencing The Future
Next Generation Analytics
Descriptive Analytics
Summarize History: What Happened and Why
- Summary Statistics
- Evaluating and visualizing the KPIs that matter the most:
✓ Retention
✓ Stickiness Ratio
✓ ARPU
✓ ARPPU
✓ LTV
✓ Time to 1st Purchase
✓…
Predictive Analytics
Forecast Behavior:
What Will Happen
- Machine Learning
- What/If Scenarios (Counterfactuals)
- Predicting the most relevant consumer behavior:
✓ Purchase LTV
✓ Ad LTV
✓ Probability to Churn
✓ Probability to Buy
✓ Probability to Share
✓…
Prescriptive Analytics
Affect Future:
What Should Happen
Affect Future:
What Should Happen
- Convex Optimization
- Optimally sized and timed Next Best Action Recommendation:
✓ ML-Recommended Marketing Tactics
✓ Optimal Pricing
✓ Bundling
✓ CTA Optimization
✓…
Analyzing The Past
Predicting The Future
Influencing The Future
Machine Learning Methodology That Makes Us Smart
State of the Art Interdisciplinary Approach
Formal Modeling
We don’t just rely on black-box methods; the first line of attack is model-based. Families of features are judiciously chosen, based on reflection, introspection, and model-derived empirical equations.
ML Enhancements
We don’t just stop in the approximately optimal output of the model-based approach. Machine learning takes charge to derive the first best. Features are transformed, controls are added, intermediate model estimates feed other models as new features and numerous techniques are automagically and recursively applied.
Statistical Validity Proof
We don’t just claim we boost KPIs, we employ statistics to prove we do and to quantify by how much. A/B/n Testing t, Paired t, Wilcoxon-Mann-Whitney, F Bayesian Framework Benchmark Ad Hoc Heuristics, Structural Modeling.
Machine Learning Methodology That Makes Us Smart
State of the Art Interdisciplinary Approach
Formal Modeling
We don’t just rely on black-box methods; the first line of attack is model-based. Families of features are judiciously chosen, based on reflection, introspection, and model-derived empirical equations.
ML Enhacements
We don’t just stop in the approximately optimal output of the model-based approach. Machine learning takes charge to derive the first best. Features are transformed, controls are added, intermediate model estimates feed other models as new features and numerous techniques are automagically and recursively applied.
Statistical Validity Proof
We don’t just claim we boost KPIs, we employ statistics to prove we do and to quantify by how much. A/B/n Testing t, Paired t, Wilcoxon-Mann-Whitney, F Bayesian Framework Benchmark Ad Hoc Heuristics, Structural Modeling.
Next Best Action Recommendation: Taking Personalization Beyond Segments
The wappier platform uses AI to compute, recommend, and serve real-time the next best action for the optimal consumer at the optimal time. Each consumer journey is different and composed by multiple, diverse touchpoints.
Let’s see an example. John is a loyal player who loves to play towards the end of the week and during late hours. Suddenly his typical, expected behavior changes. He logs in on a Monday at 09:00 am.
What should we do? Should we serve him an offer now or wait until he logs in again when he is more likely to?
We are not another ad network. We are not a CRM company. We are not another analytics dashboard. We use AI to visualize data in a way that has never happened before and optimize consumer behavior automagically.
Does all this sound complicated? Well, it is. The good thing is it is all automated. Let us give you a product tour and explain how it all works.
