--- schema_version: "1" id: 82b7aa931419142d068b5b283525430fd7be7596eb2560113ae9d351d88de5da title: Einstein Send Time Optimization for Mobile Model Card collection: admin version: current locale: en-us portal_url: https://docs.salesforce.com/admin/current/en-us/mktg/264-0-0/mc_anb_einstein_sto_mobile_model_card.md canonical_url: https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5 source_site: help.salesforce.com content_type: documentation content_hash: 7ebf38a8acd781296dd089163dec5279de97043275409964151d60090ce2c191 description: The model in this card analyzes the optimal time to send a mobile message to maximize a contact’s probability of interacting with it. In Marketing Cloud Engagement, Einstein Send Time Optimization for Mobile optimizes notification push time to maximize the overall engagement of mobile apps. products: - Marketing - Marketing Cloud Intelligence release: "264" --- # Einstein Send Time Optimization for Mobile Model Card The model in this card analyzes the optimal time to send a mobile message to maximize a contact’s probability of interacting with it. In Marketing Cloud Engagement, Einstein Send Time Optimization for Mobile optimizes notification push time to maximize the overall engagement of mobile apps. 1. **[Model Details](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** The Einstein Send Time Optimization model in Marketing Cloud Engagement optimizes customer engagement with email content using these training algorithms, parameters, fairness constraints, features, and other applied approaches. 2. **[Intended Use](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** The Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement is intended for these use cases. 3. **[Relevant Factors](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** These factors are associated with the Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement. 4. **[Metrics](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** Einstein evaluates and monitors model performance metrics to ensure and improve the quality of the model. These performance measures are associated with the Einstein Send Time Optimization model in Marketing Cloud Engagement. Customers are responsible for monitoring the accuracy of Einstein Send Time Optimization. 5. **[Training Data](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** You have a customized version of the model that’s trained on your data alone. Data from one Salesforce customer doesn’t affect the behavior for another Salesforce customer. While model training happens for each customer on their data, the initial development of the model is validated with a representative set of pilot customers’ data. 6. **[Ethical Considerations](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** Review the ethical factors associated with the Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement. To avoid bias and other ethical risks, this model doesn’t include demographic data. 7. **[Refresh Cadence](https://help.salesforce.com/s/articleView?id=mktg.mc_anb_einstein_sto_mobile_model_card.htm&release=264.0.0&type=5)** Understand the refresh cadence associated with the Einstein Send Time Optimization for Mobile model. ## Model Details The Einstein Send Time Optimization model in Marketing Cloud Engagement optimizes customer engagement with email content using these training algorithms, parameters, fairness constraints, features, and other applied approaches. ### Person or Organization Salesforce Einstein for Marketing Cloud Engagement ### Model Date and Version - December 2020 - Minor changes can occur throughout the release - Major changes can occur and are communicated via release notes ### Model Type - Recommendation/Prediction, Latent factor matrix factorization ### General Information - In Engagement, Einstein Send Time Optimization for Mobile optimizes notification push time to maximize the overall engagement of mobile apps. - The model chooses the optimal time to send a push notification to the contact to maximize the probability of the contact engaging with the app. Contacts engage either by tapping on the push notification to open the app or launching the app directly. The model also detects individual in-app patterns to avoid sending push notifications when contacts are already in the app. A contact can have different optimal send time for different apps. - We train each customer’s model only using that customer’s data. - A contact who doesn’t have enough data is part of the Pending Personalized Send Time group. A contact is categorized as not having enough data when there isn’t at least 1 open in the past 90 days. For these contacts, the model defaults to send one of two ways based on the Insufficient Data Option that the admin has selected in the STO Setup page. - The two options are Send at Einstein’s optimal default time and Send immediately. When you select Send at Einstein’s optimal default time, Einstein aggregates across all of your contacts that do have sufficient data to create a distribution of scores across every hour. Einstein then follows this distribution of scores to randomly assign scores to contacts who don’t have enough data. A contact without enough data is randomly assigned an optimal time, but it’s more likely that the contact gets a time with a higher score than one with a lower score. This randomization is added so that everyone in the Pending Personalized Send Time group doesn’t receive their email at the same time. Randomization helps avoid spikes and helps Einstein get better data. - Contacts in the Pending Personalized Send Time group are sent a push notification immediately when they reach the STO activity. ### Licenses Einstein Send Time Optimization for Mobile is available to Engagement customers with these editions. - Corporate Edition - Enterprise Edition - Enterprise+ Edition - Pro Edition with a Journey Builder for Pro Edition SKU - Einstein Send Time Optimization SKU ## Intended Use The Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement is intended for these use cases. ### Primary Intended Uses The Send Time Optimization model powers the Einstein Send Time Optimization activity in Journey Builder. Journey Builder is a tool that marketing professionals use to increase effectiveness in their mobile marketing campaigns. ### Out-of-Scope Use Cases Anything other than the primary use case is out of scope and not recommended. For example, reducing overall send latency for reservation booking mobile messages isn’t an intended use case. ## Relevant Factors These factors are associated with the Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement. ### Model Input Einstein Send Time Optimization for Mobile analyzes up to 90 days of historical engagement patterns per app. The engagement history includes these factors. - Push events and reactions, such as push notifications and taps on push notifications, and associated timestamps - Data and metadata about customer sending patterns and how campaigns are executed The engagement history that Einstein STO analyzes excludes these factors. - Data purchased or collected from third parties - Demographic Data, which is typically stored in SFMC as data extensions or subscriber or contact attributes - Specific content within the push template or rendered push message body ### Groups The model doesn’t include any demographic data or other data purchased from third-party data providers. The model uses mobile engagement data such as Push, TapOpen, AppOpen, or TimeInApp. ### Environment The model is trained and deployed in Marketing Cloud Engagement. ## Metrics Einstein evaluates and monitors model performance metrics to ensure and improve the quality of the model. These performance measures are associated with the Einstein Send Time Optimization model in Marketing Cloud Engagement. Customers are responsible for monitoring the accuracy of Einstein Send Time Optimization. ### Model Performance Measures Aggregated model performance metrics are gathered to monitor, ensure, and improve the quality of the model. Model performance metrics included the spread and sparsity of input metrics and the correlation of output scores to historical observations. All metrics are aggregated and anonymized. ## Training Data You have a customized version of the model that’s trained on your data alone. Data from one Salesforce customer doesn’t affect the behavior for another Salesforce customer. While model training happens for each customer on their data, the initial development of the model is validated with a representative set of pilot customers’ data. In general, to provide recommendations, Salesforce requires at least one engagement event, such as opens or clicks of a commercial email in the past 90 days. When you activate Einstein Send Time Optimization, existing data counts toward the 90 days. ## Ethical Considerations Review the ethical factors associated with the Einstein Send Time Optimization for Mobile model in Marketing Cloud Engagement. To avoid bias and other ethical risks, this model doesn’t include demographic data. However, biased use of Send Time Optimization (STO) for Mobile can still introduce bias to your marketing process. ![Example](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-mktg-mc_data_management_and_analytics-264-0-0-production-enus/7988f60d-cd94-4b42-8836-dc11773564b5/images/icon_example.png) Example A Salesforce customer could use STO for everyone except a vulnerable or disadvantaged segment of the population. Content sent to the vulnerable segment isn’t send-time optimized, while the rest of the population’s content is. This use can cause that segment to be further disadvantaged or miss critical marketing communication. ## Refresh Cadence Understand the refresh cadence associated with the Einstein Send Time Optimization for Mobile model. ### Scores and Models Einstein Engagement Scoring scores and models for email are updated approximately weekly. The refresh cadence varies by one to several days based on a customer's individual business unit.