Ashley|Rountree and Associates的动态

Founders: Fundraising is about relationships. Build them before you need them.

2 tips for fundraising: - Master the art of the "follow up" - Build trust and have patience because long term relationships are worth it You can do it! ??

Fundraising can be brutal, but if you're doing it, remember to read Fundraising Field Guide by Carlos Eduardo Espinal MBE. Personally, my least favourite part of fundraising is the need to generate FOMO by creating competitive tension. Yet, to get good terms, founders need both good metrics and FOMO. Learning to create FOMO is simply part of the job. - fundraisingfieldguide.com

Start making your fundraising efforts smoother, simpler and stress-free.

?? Transforming Challenges into Opportunities ?? Great leaders and organizations inspire us with their ability to innovate, adapt, and prioritize value creation. It’s a powerful reminder of the impact of combining strategic foresight with operational excellence. In my journey, I’ve focused on building frameworks that drive efficiency, resilience, and transformation. Watching others embrace agility and create unique customer experiences reaffirms the importance of staying adaptable and visionary in today’s fast-paced world. Let’s continue to push boundaries, learn, and grow as we shape the future of business together. ?? #Leadership #Innovation #BusinessExcellence #ProcessImprovement #StrategicGrowth

Three Easy Steps for Planning Your Fundraising Focus for the New Year!

I suggest that you approach your short-term fundraising activities as a step in laying the groundwork for your longer term fundraising efforts.

To integrate Sharia-compliant features into Tabby while minimizing disruptions to the global economy, we'll leverage AI and augmentation to create a comprehensive plan with actionable items and timelines. Phase 1: Research and Analysis (Weeks 1-4) AI-powered Market Analysis: Utilize machine learning algorithms to analyze market trends, user behavior, and competitor strategies. Sharia Compliance Expertise: Collaborate with Islamic finance experts to understand regulatory requirements and ensure compliance. Risk Assessment: Conduct thorough risk assessments using predictive analytics tools to identify potential challenges. Phase 2: Feature Development (Weeks 5-12) Feature Prioritization: Use data-driven decision-making processes to prioritize feature development based on user needs, market demand, and regulatory requirements. Agile Development Methodology: Employ agile development methodologies like Scrum or Kanban to facilitate iterative development and continuous improvement. Augmented Reality Testing: Leverage AR testing tools to simulate real-world scenarios, ensuring seamless integration of new features. Phase 3: Regulatory Approvals (Weeks 13-16) Regulatory Submissions: Submit applications for necessary licenses and approvals from relevant authorities. Compliance Audits: Conduct regular audits using AI-powered compliance tools to ensure ongoing adherence to Sharia principles. Phase 4: User Education and Onboarding (Weeks 17-20) User Education Campaigns: Develop targeted education campaigns using AI-driven content creation tools to inform users about Sharia-compliant features. Onboarding Process Optimization: Implement an optimized onboarding process leveraging AI-powered chatbots for efficient user support. Phase 5: Continuous Improvement (After Week 20) Code Implementation: Here's an example code implementation in Python for the developer: # Import necessary libraries import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score # Load data from database or CSV file df = pd.read_csv('data.csv') # Preprocess data by handling missing values, encoding categorical variables etc. df = df.dropna() # Drop rows with missing values df['categorical_variable'] = df['categorical_variable'].astype('category') # Encode categorical variable as category type # Split data into training set & test set train_data , test_data , train_labels , test_labels = train_test_split(df.drop('target',axis=1),df['target'],test_size=0.2) # Initialize logistic regression model model = LogisticRegression() # Train model using training set model.fit(train_data.values.tolist(),train_labels) # Make predictions on test set predictions=model.predict(test_data.values.tolist()) # Evaluate model performance by calculating accuracy score accuracy=accuracy_score(test_labels,predictions) print(f'Model Accuracy:{accuracy}')

? Ready to start or supercharge your sustainer program? ? Take a gander at our blog post, where we break down why sustainer programs are the unsung heroes of fundraising, what common pitfalls to avoid, and how you can cultivate a flourishing program. Check it out here ?? https://hubs.la/Q033J-HF0

If you are thinking about scaling your business or starting a new one, here are the fundamental strategies for successful fundraising. #BFLGroup #BrandsForLess #Businesstips