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MoEngage Unveils New Tools to Help Marketers Adapt to Consumer Trends
03Dec

MoEngage Unveils New Tools to Help Marketers Adapt to Consumer Trends

MoEngage, a leading cross-channel customer engagement platform, has launched new features designed to help marketers quickly adapt to shifting consumer behaviors. These updates, introduced at the bi-annual MoEngage NEXT event, include Connected Apps for seamless data integration, a Salesforce CRM integration for streamlined data exchange, and Coupons for managing single-use discounts. “Our new capabilities reinforce our commitment to empowering marketers with tools to understand and adapt to evolving consumer expectations,” said Raviteja Dodda, CEO and Co-Founder of MoEngage. “These innovations enable our clients to scale personalized engagement based on individual preferences and behaviors.” Tackling Fragmented Engagement Tools Marketers often struggle to deliver personalized experiences due to disconnected engagement tools and data silos. To bridge this gap, MoEngage introduced Connected Apps, a low-code framework that integrates data across messaging platforms, advertising channels, IVR systems, data warehouses, and chatbots. Enhanced Integration with Salesforce CRM The new bi-directional native integration with Salesforce CRM simplifies data exchange between the two platforms. Marketers can now trigger real-time personalized campaigns without needing costly custom integrations. This integration not only improves efficiency but also reduces operational costs. Streamlining Coupon Management To enhance customer engagement, MoEngage launched Coupons, a feature that helps marketers allocate and manage single-use discount codes from a centralized dashboard. The tool includes real-time updates on coupon status, alerts for shortages and expiration dates, and ingestion tracking, ensuring smooth campaign execution while optimizing costs. Driving Scalable and Personalized Engagement With these innovations, MoEngage continues to solidify its position as a go-to platform for marketers seeking to adapt quickly to consumer trends. By addressing common pain points like data fragmentation and inefficient tools, MoEngage enables marketers to deliver meaningful, personalized customer experiences at scale. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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December 3, 2024in Data, Salesforce, Third Party Apps0 Comments
Data Cloud Model
08Oct

Data Cloud Model

While many Salesforce products like Sales Cloud, Service Cloud, Education Cloud, Health Cloud, and various industry clouds are built on a common ‘core’ platform that shares the same datastore (an Oracle relational database), Salesforce Data Cloud operates on (Data Cloud Model) a distinct architecture and technology stack. This insight explores the data models and related concepts that underpin the platform. Data Cloud Architecture and Storage Starting with the storage layer, Salesforce Data Cloud integrates multiple services: This combination enables Data Cloud to provide a petabyte-scale data store, overcoming the scalability and performance constraints of traditional relational databases. The physical architecture of Data Cloud is represented as a set of data objects, which form the foundation for how data is ingested, harmonized, and activated within the platform. Key Data Cloud Objects Data Source A Data Source is the initial data layer in Data Cloud, representing an external platform or system from which your data originates. Data Sources can include: Data Stream A Data Stream is an entity extracted from a Data Source, such as ‘Orders’ from Commerce Cloud, ‘Contacts’ from Sales Cloud, or ‘Subscribers’ from Marketing Cloud. Once a Data Source is connected to Data Cloud, Data Streams provide access to these entities and require assignment to a category: Profile, Engagement, or Other. A single Data Source can contain multiple Data Streams. Data Source Object (DSO) Data Streams are ingested into Data Source Objects (DSOs), which serve as temporary staging stores containing data in its raw, native format (e.g., CSV files). Minor transformations can be applied to fields during data ingestion. Data Lake Object (DLO) The next step in the data flow is the Data Lake Object (DLO). DLOs are typed, schema-based, materialized views that reside in the data lake (Amazon S3) and are generally stored as Apache Parquet files. This format, along with Apache Iceberg’s abstraction layer, supports efficient data storage and retrieval. DLOs are the first objects available for inspection and preparation of data, including field mapping and additional transformations. Data Model Object (DMO) Unlike DSOs and DLOs, which use a physical data store, Data Model Objects (DMOs) provide a virtual, non-materialized view into the data lake. Queries against a DMO return results based on the current data snapshot in DLOs, without storing them. DMOs can aggregate attributes from different Data Streams, Calculated Insights, and other sources. DMOs inherit their category from the first DLO mapped to them, and only DLOs with the same category can be mapped to the DMO. Like Salesforce objects, DMOs offer a canonical data model with pre-defined attributes (standard objects), and you can also create custom DMOs (custom objects). DMOs can have one-to-one or many-to-one relationships with other DMOs. Currently, there are 89 standard DMOs in Data Cloud, and this number is growing to support more use cases. DMOs are organized into various subject areas, including: Data Spaces Data Spaces offer logical partitions, allowing data to be segregated between different brands, regions, or departments, without the need for multiple Data Cloud instances. They also align with a Software Development Lifecycle (SDLC), enabling you to stage and test Data Objects in separate environments without affecting production data. Data Sources, Data Streams, and DLOs can be shared across Data Spaces, while DMOs and other platform features are isolated based on user permissions. Final Thoughts With the drop in storage costs and advancements in technology, companies now have vast datasets at their disposal. Every customer interaction, whether it’s a purchase, an email open, or a web page view, can be captured and stored. When properly organized, this data allows businesses to understand customers better, predict their needs, personalize interactions, and much more. However, one of Salesforce’s challenges is that its original platform, built over 20 years ago, was designed for a different era and struggles with handling voluminous, “big” data. Salesforce Data Cloud addresses these limitations with a modern architecture that overcomes the constraints of relational databases. Data Cloud is poised to become the backbone of the Salesforce platform, supporting the data needs of customers and products for the next two decades. If you’re interested in learning how to implement and integrate Salesforce Data Cloud in your organization, following best practices, reach out today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 8, 2024in Salesforce Data Cloud, Unified Knowledge
Cortex Framework Integration with Salesforce (SFDC)
30Sep

Cortex Framework Integration with Salesforce (SFDC)

Cortex Framework: Integration with Salesforce (SFDC) This insight outlines the process of integrating Salesforce (SFDC) operational workloads into the Cortex Framework Data Foundation. By integrating Salesforce data through Dataflow pipelines into BigQuery, Cloud Composer can schedule and monitor these pipelines, allowing you to gain insights from your Salesforce data. Cortex Framework Integration with Salesforce explained. Prerequisite: Before configuring any workload integration, ensure that the Cortex Framework Data Foundation is deployed. Configuration File The config.json file in the Cortex Framework Data Foundation repository manages settings for transferring data from various sources, including Salesforce. Below is an example of how Salesforce workloads are configured: jsonCopy code”SFDC”: { “deployCDC”: true, “createMappingViews”: true, “createPlaceholders”: true, “datasets”: { “cdc”: “”, “raw”: “”, “reporting”: “REPORTING_SFDC” } } Explanation of Parameters: Parameter Meaning Default Value Description SFDC.deployCDC Deploy CDC true Generates Change Data Capture (CDC) processing scripts to run as DAGs in Cloud Composer. SFDC.createMappingViews Create mapping views true Creates views in the CDC processed dataset to show the “latest version of the truth” from the raw dataset. SFDC.createPlaceholders Create placeholders true Creates empty placeholder tables if they aren’t generated during ingestion, ensuring smooth downstream reporting deployment. SFDC.datasets.raw Raw landing dataset (user-defined) The dataset where replication tools land data from Salesforce. SFDC.datasets.cdc CDC processed dataset (user-defined) Source for reporting views and target for records processed by DAGs. SFDC.datasets.reporting Reporting dataset for SFDC “REPORTING_SFDC” Name of the dataset accessible for end-user reporting, where views and user-facing tables are deployed. Salesforce Data Requirements Table Structure: Loading SFDC Data into BigQuery The Cortex Framework offers several methods for loading Salesforce data into BigQuery: CDC Processing The CDC scripts rely on two key fields: You can adjust the CDC processing to handle different field names or add custom fields to suit your data schema. Configuration of API Integration and CDC To configure Salesforce data integration into BigQuery, Cortex provides the following methods: Example Configuration (settings.yaml): yamlCopy codesalesforce_to_raw_tables: – base_table: accounts raw_table: Accounts api_name: Account load_frequency: “@daily” Data Mapping and Polymorphic Fields Cortex Framework supports mapping data fields to the expected format. For example, a field named unicornId in your source system would be mapped to AccountId in Cortex with the string data type. Polymorphic Fields: Fields whose names vary but have the same structure can be mapped in Cortex using [Field Name]_Type, such as Who_Type for the Who.Type field in the Task object. Modifying DAG Templates You can customize DAG templates as needed for CDC or raw data processing. To disable CDC or raw data processing from API calls, set deployCDC=false in the configuration file. Setting Up the Extraction Module Follow these steps to set up the Salesforce to BigQuery extraction module: Cloud Composer Setup To run Python scripts for replication, install the necessary Python packages depending on your Airflow version. For Airflow 2.x: bashCopy codegcloud composer environments update my-composer-instance –location us-central1 –update-pypi-package apache-airflow-providers-salesforce>=5.2.0 Security and Permissions Ensure Cloud Composer has access to Google Secret Manager for retrieving stored secrets, enhancing the security of sensitive data like passwords and API keys. Conclusion By following these steps, you can successfully integrate Salesforce workloads into Cortex Framework, ensuring a seamless data flow from Salesforce into BigQuery for reporting and analytics. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 30, 2024in Data, Google, Salesforce
Best Practices for Data Management
04Oct

Best Practices for Data Management

Mastering Data Management in Salesforce Effective data management is crucial for maximizing success with Salesforce. Ensuring you have high-quality, useful data empowers your team to achieve business goals and identify growth opportunities. Below are learning resources, expert articles, and video guides designed by Salesforce professionals to help you take control of your data. Build a Data Management Strategy A solid data management strategy ensures that your team is aligned on how data is collected, analyzed, and used to drive success. These resources will guide you through creating a strategy and avoiding common pitfalls: Improve Data Quality Clean data is essential for tracking, reporting, and ensuring the success of your Salesforce implementation. Explore the following resources to improve your data quality: Import Data Seamlessly bring existing data into Salesforce to ensure you have a full record for reporting and tracking. These resources will guide you through importing data: Maintain and Clean Up Data To keep your data clean and reliable over time, follow these best practices for long-term data management: Go Further with Data Management Take your data management expertise to the next level with these additional resources: These curated resources empower you to master data management within Salesforce, ensuring your organization makes the most of its CRM data to drive growth and success. Content updated September 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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October 4, 2023in Data, Salesforce
Salesforce CDP
16Nov

CDP Salesforce

What is a CDP in Salesforce? A customer data platform (CDP) is an application that gathers, organizes and enriches data from multiple sources, while being marketer-centric, versus sales/service-centric like a CRM. It is a key enabler to organizations that want to maximize return on all the data they have collected and own around their customers. The CDP combines all the data from all the sources in real time so you can make hyper-personalized offers and experiences that feel like magic. This means connecting all the customer data back to email engines, demand-side platforms, and content management systems. What is the difference between Salesforce Genie and CDP? SFDC CDP follows the audience segmentation + data activation protocols. Salesforce Genie allows for data unification and identity resolution. Is CDP same as data cloud? Data Cloud shares the same purpose and benefits that CDPs deliver – however Data Cloud is not the same as the technology that was formerly Salesforce CDP. Data Cloud takes CDP’s capabilities, and extends the benefits right across the “Customer 360” (i.e. Salesforce’s product portfolio). What can a Customer Data Platform do for your brand? CDPs connect customer data so every team has insight into how a customer interacts with you on every platform. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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November 16, 2022in Data, Google, Salesforce, Salesforce Hospitality Travel and Transportation, Salesforce Implementation Services, Technology
Salesforce
10Jun

What is Salesforce?

Salesforce is cloud-based CRM software. It makes it easier for companies to find more prospects, close more deals, and connect with customers in a whole new way, so they can provide them with amazing service at scale. Salesforce, Inc. is an American cloud-based software company headquartered in San Francisco, California. It provides customer relationship management software and applications focused on sales, customer service, marketing automation, e-commerce, analytics, and application development. According to Wikipedia… Salesforce brings together all your data, from any source. Customer 360, the complete suite of products, unites your sales, service, marketing, commerce, and IT teams with a single, shared view of customer information. With artificial intelligence integrated across all products, SFDC helps everyone in your company work more productively and better deliver the personalized experiences customers love. To explore all Salesforce has to offer for your business, contact Tectonic today. Salesforce is cloud-based CRM software (What is CRM?). It makes it easier for companies to find more prospects, close more deals, and connect with customers in a whole new way, so they can provide them with amazing service at scale. Salesforce brings together all your data, from any source. Customer 360, our complete suite of products, unites your sales, service, marketing, commerce, and IT teams with a single, shared view of customer information. With artificial intelligence integrated across all products, SFDC helps everyone in your company work more productively and better deliver the personalized experiences customers love. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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June 10, 2019in Artificial Intelligence, Data, Marketing Automation, Salesforce

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