Fundraising Event Registration Tools

If you use HubSpot and run events read this. There are three ways to track events in HS. One of them just got a lot better. Option 1: - Contact Lists For each event, create two lists. [Event Name - Registered] [Event Name - Attended] If you need to track registrations vs. attendance. Downside - HS restricts the number of lists you can create without upgrading. --- Option 2: - HubSpot Marketing Events HS launched this object in early 2021. At launch, you could only see how many people registered or attended. Not who. But that just changed. You can now see the attendance status for each registrant. Unfortunately - you can't test `HS Marketing Event` which would be a great way to track session registration. --- Option 3: - Deal Object Create a new pipleline for ‘Events’ When an attendee registers, create a Deal record in the Events Pipeline. You can map Event Tickets & Add-Ons from your reg platform to HS Products / Line Items for revenue reporting. Contact-level data like Session registration can flow into a HS TimeLine Event. For high-priced events with sales teams, this approach makes it easy to track commissions in HubSpot. --- All 3 options let you trigger workflows based on attendee activity, run reports, and easily inform your sales team for outreach. ...and the best part? The HubSpot Certified Accelevents integration supports all 3 options listed above! Now, there are some more complex approaches using Custom Behavior Events, Timeline Events, and Custom Objects. But we’ll save that for another day. P.S. Don’t forget to turn on non-HubSpot Form tracking and add your HS tracking code to your registration page to capture Origianl Source Drill-Down data. What’s your preferred approach for tracking event data in your CRM? #hubspot #eventmarketing #marketingops #events

As a lawyer who often dives deep into the world of data privacy, I want to delve into three critical aspects of data protection: A) Data Privacy This fundamental right has become increasingly crucial in our data-driven world. Key features include: -Consent and transparency: Organizations must clearly communicate how they collect, use, and share personal data. This often involves detailed privacy policies and consent mechanisms. -Data minimization: Companies should only collect data that's necessary for their stated purposes. This principle not only reduces risk but also simplifies compliance efforts. -Rights of data subjects: Under regulations like GDPR, individuals have rights such as access, rectification, erasure, and data portability. Organizations need robust processes to handle these requests. -Cross-border data transfers: With the invalidation of Privacy Shield and complexities around Standard Contractual Clauses, ensuring compliant data flows across borders requires careful legal navigation. B) Data Processing Agreements (DPAs) These contracts govern the relationship between data controllers and processors, ensuring regulatory compliance. They should include: -Scope of processing: DPAs must clearly define the types of data being processed and the specific purposes for which processing is allowed. -Subprocessor management: Controllers typically require the right to approve or object to any subprocessors, with processors obligated to flow down DPA requirements. -Data breach protocols: DPAs should specify timeframes for breach notification (often 24-72 hours) and outline the required content of such notifications, -Audit rights: Most DPAs now include provisions for audits and/or acceptance of third-party certifications like SOC II Type II or ISO 27001. C) Data Security These measures include: -Technical measures: This could involve encryption (both at rest and in transit), multi-factor authentication, and regular penetration testing. -Organizational measures: Beyond technical controls, this includes data protection impact assessments (DPIAs), appointing data protection officers where required, and maintaining records of processing activities. -Incident response plans: These should detail roles and responsibilities, communication protocols, and steps for containment, eradication, and recovery. -Regular assessments: This often involves annual security reviews, ongoing vulnerability scans, and updating security measures in response to evolving threats. These aren't just compliance checkboxes – they're the foundation of trust in the digital economy. They're the guardians of our digital identities, enabling the data-driven services we rely on while safeguarding our fundamental rights. Remember, in an era where data is often called the "new oil," knowledge of these concepts is critical for any organization handling personal data. #legaltech #innovation #law #business #learning

𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗔𝘁𝘁𝗲𝗻𝗱𝗮𝗻𝗰𝗲 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 Recently, I posted about a Google Sheets tool for tracking attendance and streamlining engagement monitoring. While it works well, it could be made even better especially for large classes or communities. 𝗟𝗲𝘁 𝗺𝗲 𝘀𝗵𝗮𝗿𝗲 𝗮 𝗿𝗲𝗮𝗹-𝗹𝗶𝗳𝗲 𝗲𝘅𝗮𝗺𝗽𝗹𝗲. I once volunteered with an organization that ran cohort-based accountability programs, each cohort with 100–200 participants. Participants logged attendance and daily activities via an app, which fed the data into a Google Sheet. However, the data wasn’t immediately useful for tracking consistency or engagement. Volunteers had to manually check and mark attendance daily on a Google Sheet template, a task that took hours and became overwhelming if left undone. When I joined, I completely automated the process, reducing hours of manual work to zero seconds. Here’s how I did it: ✅ Built a new attendance tracking template linked to the data sheet using IMPORTRANGE and QUERY functions. ✅ Used functions like IF. COUNTIF. etc to automatically mark checkboxes for attendance. ✅ Added formulas to calculate daily, weekly, and monthly attendance percentages for individuals and cohorts. ✅ Enabled real-time tracking of participation, helping the team identify participants needing extra attention or elimination based on engagement metrics. This is an example of how data analysis can optimize processes in fields like project management, monitoring, and evaluation, community management,etc. By leveraging simple tools and analytical thinking, I turned a manual, time-consuming task into an efficient automated system. 📽️ Check out the attached video to see the template in action. 𝗛𝗼𝘄 𝗵𝗮𝘃𝗲 𝘆𝗼𝘂 𝘂𝘀𝗲𝗱 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘁𝗼 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗼𝗿 𝘀𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝗮 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗶𝗻 𝘆𝗼𝘂𝗿 𝘄𝗼𝗿𝗸 𝗼𝗿 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻? 

🤖👾The Italian Data Protection Authority has issued guidance on protecting personal data published online from web scraping. Web scraping involves indiscriminately collecting individual data by third parties, often for training generative #AI models. 💡The DPA recommends several measures for data controllers, both public and private, to protect personal data. These measures include creating reserved areas accessible only upon registration, incorporating anti-scraping clauses in terms of service, monitoring web traffic for abnormal data flows, and implementing specific measures against bots, such as using robots.txt files. 📍Web scraping becomes a data protection issue when it involves collecting identifiable personal information. Compliance with the GDPR requires entities processing such data to identify a suitable legal basis under Article 6 of the GDPR. The legality of web scraping must be assessed case-by-case, considering the opposing rights involved. 📍Based on protocols like HTTP, the internet's open architecture allows for public data availability, which bots can systematically collect. Search engine crawlers are examples of bots that collect data for indexing. Web scraping combines data collection with storing and processing the data for various purposes, some of which may be malicious, such as DDoS attacks or digital fraud. The legality of web scraping for training GAI depends on multiple evaluations by the data collector and the data publisher. 📍Generative AI developers often use large datasets from web scraping or third-party data lakes like Common Crawl and Hugging Face. These datasets can also come from user data already held by developers. The DPA suggests several precautions to mitigate the impact of web scraping for training GAI models. Creating restricted areas accessible only by registration can reduce public data availability. This measure aligns with GDPR principles, ensuring data minimization and preventing unnecessary data processing. Including anti-scraping clauses in terms of service can provide legal grounds for action against violators. Monitoring network traffic can help detect and counter abnormal data flows. Implementing measures to limit bot access, such as CAPTCHA checks, periodic HTML markup modifications, and embedding data in media objects, can make scraping more difficult. Monitoring log files and using robots.txt files to control bot access are also recommended, although these measures have limitations. ‼️The DPA  acknowledges that none of these measures can completely prevent web scraping but emphasizes their importance in reducing unauthorized data use. Website and platform operators must evaluate and implement these precautions based on their accountability under the GDPR to protect personal data from scraping aimed at training GAI models. #gdpr #privacy #dataprotection

Assessing the privacy implications of 3rd-party processors is a crucial component of an org's overall data protection strategy. This assessment involves evaluating how these 3rd parties manage the data entrusted to them, especially personal data, and ensuring they comply with applicable privacy laws and best practices. Here’s a step-by-step approach: ✔ Identify Third-Party Processors: List all 3rd-party services and vendors that process data on your behalf. This includes cloud service providers, payment processors, CRM systems, marketing tools, etc. ✔ Understand the Data Processing Activities: Clarify what data is being processed by each 3rd party, how it is being processed, and for what purposes & determine if the data includes sensitive personal info, which may require additional safeguards. ✔ Review Legal Compliance: Ensure that the 3rd-party processors comply with relevant dp laws and regulations & check if they have the necessary cert or adhere to recognized stds. ✔ Assess Data Security Measures: Evaluate the security measures the 3rd party has in place to protect data. This includes phy, tech, and admn safeguards & consider aspects like encryption, access controls. ✔ Review Data Transfer Mechanisms: If data is transferred internationally, ensure that appropriate mechanisms (like SCC's, BCR's) are in place, especially when transferring data out of the EU. ✔ Evaluate Contractual Agreements: Review contracts and data processing agreements with 3rd parties to ensure they include strong dp clauses & ensure there are clear terms regarding data handling, breach notification, and liability. ✔ Conduct Regular Audits or Assessments: Periodically audit or assess the 3rd-party processors to ensure ongoing compliance. This might include questionnaires, 3rd-party audits, or reviews of compliance documentation. ✔ Understand Breach Notification Procedures: Ensure that the 3rd party has an effective incident response and breach notification process and that it aligns with your legal obligations. ✔ Review Data Minimization Practices: Check if the 3rd party applies data minimization principles, processing only the data necessary for the specified purpose. ✔ Monitor Changes and Updates: Stay informed about any changes in the third party’s data processing activities or policies that might affect privacy implications. ✔ Engage Stakeholders: Involve relevant internal stakeholders, such as legal, compliance, and IT teams, in the evaluation and decision-making process regarding 3rd-party processors. ✔ Plan for End-of-Contract Data Management: Have clear procedures for the return or destruction of data once the contract with the 3rd party ends. By thoroughly assessing the privacy practices of 3rd party processors, an org can significantly reduce the risk of data breaches and ensure compliance with dp regulations, thereby safeguarding not only the data but also its reputation and legal standing. https://lnkd.in/dHCJkmDm

Sharing with my fellow members about the key takeaways from the DSCI AISS 2023 Masterclass on "Safeguarding Data and Privacy Across the Lifecycle: An Enterprise Approach": A. Introduction to Data Protection in Enterprises: The journey of data protection starts when any type of data (financial, customer, employee, intellectual, biometric, etc.) enters the enterprise system. B. Key Triggers for Data Protection: 1. Regulatory compliance is the primary driver for data protection, underlining the importance of adhering to legal requirements. A maturing cybersecurity posture is also essential, highlighting the evolving nature of security needs in enterprises. 2. Data Subject Approach and Operations: The approach focuses on seamless operations and effective management through specific stages: a. Collection: Adherence to privacy norms while gathering data. b. Classification: Organizing data into categories like Confidential, Internal, and Public. c. Discovery: Identifying data locations and usage methods within the enterprise. d. Storage: Using robust security measures for safe data storage. e. Usage: Ensuring integrity and confidentiality during data utilization. f. Transfer: Securely transferring data, including interactions with third parties. g. Destruction: Properly disposing of data as required or when no longer needed. 3. Data Protection Technologies and Strategies: A. Data Loss Prevention (DLP): Implementing Endpoint and Network DLP to prevent unauthorized data access or misuse. B. Data Masking and Tokenization: Using dynamic data masking, tokenization (vault-based and vault-less), and database masking, integrated with applications for enhanced security. C. Data Encryption: Securing active data through data-in-use encryption. D. Governance: Establishing strong protocols to oversee data handling practices. 4. Maturity and Integration in Data Protection: The effectiveness of DLP and other measures largely depends on their maturity (like block mode) and integration with data classification systems. Understanding the nature of the data (structured or unstructured) is crucial for the effective functioning of these systems. Incident management and data discovery are key components of this strategy. 5. Business Integration: Effective data protection requires a collaborative effort between technology teams and various business units, emphasizing the need for strong integration within business operations. 6. Data Sanitization: Involves irreversible methods to remove or destroy data, ensuring it cannot be recovered. Summary: Safeguarding data and privacy in an enterprise is a complex task requiring a blend of technological solutions, and business integration. The goal is to protect sensitive information throughout its entire lifecycle, acknowledging the challenges in the digital landscape. Vinayak Godse Sukrit Ghosh Ajay C Bhayani Suresh Iyer Manish Sehgal Dr. Vivek Pandey Vikram Taneja Vimal Kurian #dsci #dataprotection #security

I’m currently working on a project called "Smart Attendance System" an idea that came from the challenges I face as a student in my class every day. As a class representative, I’ve seen firsthand the issues students have with attendance. We use the traditional method of signing attendance on paper, but this has many problems. Sometimes, the attendance sheet gets lost or damaged, leading to missing records for an entire class or course. Another challenge is that department heads want to monitor students' attendance but struggle to do so. To check attendance, they need to collect sheets from lecturers, making it difficult to track attendance performance in real time. Students also face a problem—they can’t check their attendance records easily unless they meet the person holding the attendance sheet, which isn’t always convenient. To solve these problems, I decided to build the Smart Attendance System, a digital solution that makes attendance tracking easier for students, lecturers, and department heads. ↳ How It Works ▪Lecturers will be the only ones who can sign up and access the admin dashboard. ▪The admin will register students with their name, registration number, year of admission, and current level. ▪For each course, lecturers will create an attendance list. ▪During class, the lecturer simply activates the attendance and marks students present. ↳ How This Solves the Problem ▪Easy Access: Both students and lecturers can view attendance records anytime, anywhere. ▪Real-Time Monitoring: Department heads can track attendance from their office without needing paper records. ▪Permanent Storage: Attendance data is stored online, so it can’t be lost or damaged. ▪ End-of-Semester Reports: Lecturers can print attendance records when needed. This project is my initiative, inspired by real problems I’ve faced as a student. I’m building it in public and sharing my journey. If this is your first time seeing my profile, feel free to check out my updates on this project! #WebDevelopment #NodeJS #MongoDB #Mongoose #SmartAttendance #AcademicSession #BackendDevelopment #problemsolving #tech #attendance

             𝗪𝗲𝗯𝗵𝗼𝗼𝗸𝘀 𝗶𝗻 𝗗𝘆𝗻𝗮𝗺𝗶𝗰𝘀 𝟯𝟲𝟱 Webhooks is a lightweight HTTP pattern for connecting Web APIs and services with a 𝗽𝘂𝗯𝗹𝗶𝘀𝗵/𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲 model. Webhook senders notify receivers about events by making requests to receiver endpoints with some information about the events. Webhooks allow to subscribe specific events and receive HTTP POST requests to a specified URL whenever those events occur. This enables real-time integration with external systems, such as 𝘀𝗲𝗻𝗱𝗶𝗻𝗴 𝗻𝗼𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀, 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝗶𝗻𝗴 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀, 𝗼𝗿 𝘂𝗽𝗱𝗮𝘁𝗶𝗻𝗴 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀. When using an Azure Function as a webhook endpoint for Dynamics 365, typically receive the data in the request body. Azure Function's context can be used to handle this data and perform necessary operations. 𝗛𝗼𝘄 𝗪𝗲𝗯𝗵𝗼𝗼𝗸𝘀 𝘄𝗼𝗿𝗸 Webhooks work by allowing one application to register a URL endpoint with another application or service. When a specific event occurs in the source application, it sends an HTTP request containing relevant data to the registered URL endpoint. The source application act as a 𝗽𝘂𝗯𝗹𝗶𝘀𝗵𝗲𝗿 and receiver application acts as 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲𝗿. The receiving application, or webhook handler, processes the incoming data and performs any necessary actions based on the received information. 𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗪𝗲𝗯𝗵𝗼𝗼𝗸𝘀 Webhooks provide instant notifications when specific events occur, allowing systems to react immediately to changes. By eliminating the need for constant 𝗽𝗼𝗹𝗹𝗶𝗻𝗴 𝗼𝗿 𝗺𝗮𝗻𝘂𝗮𝗹 𝗰𝗵𝗲𝗰𝗸𝘀 𝗳𝗼𝗿 𝘂𝗽𝗱𝗮𝘁𝗲𝘀, webhooks reduce unnecessary network traffic and processing overhead. With webhooks, updates are pushed to subscribers in real time, minimizing the latency between event occurrence and action execution. 𝗛𝗼𝘄 𝘁𝗼 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗲 𝗪𝗲𝗯𝗵𝗼𝗼𝗸𝘀 •   Creating or configuring a service to consume webhook requests. •   Registering webhook step on the Dynamics 365 service using plugin registration tool providing: Name of webhook  Endpoint URL (subscriber), Authentication key Register new step describe event on create, update or other actions on record 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: I have entity name as 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 on CRM, 𝗦𝗤𝗟 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 and 𝗔𝘇𝘂𝗿𝗲 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻 hosted on azure. I want when a new record is created on CRM it will sync with external SQL database. When a new record is created on CRM it call registered endpoint Azure function. I get context from Request body and entity related information then insert new record in SQL database. In this way CRM and external database are synchronous with each others

If you use Hubspot and need to track in-person events chances are you struggle to know how to report on them effectively. It’s just not great out of the box. It’s hard to see these offline events in attribution reports. It’s hard to know what event someone was a part of. It’s hard to know who came by your booth or not. It’s hard to know what info happened during the conversation at the event. Here are some ideas to help out: 1) Create lists that follow a naming convention like: Event - Engage 23 - Pre Event List - August 2023. This will ensure that it shows up in the Marketing Details field at the very least so you know what event a lead was associated with. 2) Create a workflow that marks your custom attribution fields with Event for those that come in this way. (No way to track with native source fields since not editable). This will be your roll-up field to quickly see what source is leading to Opps and Closed Won business. 3) Get a tool like Mobly that can scan seamlessly into Hubspot with custom tags that let you know if a person is a hot lead and with all the context notes you could ask for. While not easy it is possible to track events better in Hubspot. If you want to chat more about this feel free to book some time on my calendar. ________________________________ Find this interesting? Follow me. I write weekday mornings about how marketing leaders can show impact without sacrificing their weekends. #marketingleaders #marketingevents #b2bmarketing

Enhancing the RTO Registration System with Advanced SQL Previously, my team and I worked on an RTO Registration System to streamline vehicle registration, insurance, and payment tracking using SQL and relational database management. Now, I have continued this project and implemented Advanced SQL queries to improve functionality, optimize data retrieval, and automate key processes. Project Overview The system is designed to manage essential RTO operations efficiently by structuring data into interconnected tables: Customer – Stores user information Vehicle – Tracks vehicle details Registration – Records vehicle registration data Insurance – Manages insurance policies and renewals Payment – Handles transaction details Enhancements with Advanced SQL Building on the foundation, I implemented the following Advanced SQL features: ✅ Functions – Created a function to calculate total insurance amount based on type. ✅ Procedures – Designed stored procedures to insert new customers and handle errors. ✅ Cursors – Implemented both implicit and explicit cursors for efficient data processing. ✅ Triggers – Developed triggers to track changes in payment amounts and validate insurance amounts. ✅ Exception Handling – Integrated both system-defined and user-defined exception handling to manage errors efficiently. ✅ Packages – Created a package to encapsulate customer-related operations for better modularity. Key Benefits Automated Data Updates – Ensures real-time tracking of payments and registrations. Error Handling & Validation – Prevents invalid transactions and maintains data integrity. Optimized Query Performance – Faster retrieval of pending payments, active registrations, and insurance details. Scalability – The system is now more robust and adaptable for future enhancements. Next Steps Moving forward, I plan to integrate Advanced SQL analytics for predictive insights and develop a web-based interface for better user experience. Technologies Used SQL | Oracle Live SQL | Database Management | SQL Developer | Advanced Querying | Stored Procedures | Triggers | PL/SQL This project reinforced my belief in the power of structured data and automation in optimizing real-world applications. Open to discussions on database management, process automation, and best practices in SQL optimization! #SQL #AdvancedSQL #DatabaseManagement #PLSQL #RTO #DataAutomation #OracleSQL #TechForGood #SQLDeveloper