New ROI Calculator Submission
Business Information
Company: {business_info['company']}
Industry: {business_info['industry']}
Employees: {business_info['employees']}
Email: {business_info['email']}
Phone: {business_info.get('phone', 'Not provided')}
Avg Hourly Wage: ${business_info['avg_wage']}/hour
ROI Analysis Results
Annual Labor Savings: ${calculations['annual_labor_savings']:,.0f}
Year 1 Investment: ${calculations['ai_costs']['total_year_one']:,.0f}
Year 1 Net Savings: ${calculations['year_one_savings']:,.0f}
Ongoing Annual Savings: ${calculations['annual_ongoing_savings']:,.0f}
Monthly Savings (Year 2+): ${calculations['monthly_savings']:,.0f}
Hours Saved Per Week: {calculations['hours_saved']:.1f}
3-Year ROI: {calculations['roi_three_year']:.0f}%
Payback Period: {calculations['payback_months']:.1f} months
Time-Consuming Tasks
{tasks_list}
Next Steps
This lead has shown significant interest in AI implementation with potential ongoing savings of ${calculations['annual_ongoing_savings']:,.0f} annually.
Consider reaching out within 24 hours while their interest is high.
Generated by AI ROI Calculator - Eau Claire AI
"""
# Create and send email
message = Mail(
from_email='noreply@eauclaireai.com',
to_emails='info@eauclaireai.com',
subject=subject,
html_content=html_content
)
response = sg.send(message)
return True
except Exception as e:
st.error(f"Email notification failed: {str(e)}")
return False
def get_ai_recommendations(industry, company_size, main_tasks, annual_savings):
"""Get AI-powered recommendations from OpenAI"""
try:
client = openai.OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
prompt = f"""You are an AI consultant for Eau Claire AI. Provide personalized recommendations for a business with these details:
- Industry: {industry}
- Company size: {company_size} employees
- Main time-consuming tasks: {main_tasks}
- Potential annual savings: ${annual_savings:,.0f}
Provide 3 specific, actionable AI implementation recommendations that would be most impactful for this business.
Focus on practical, cost-effective solutions that align with Eau Claire AI's approach of "problem-led, not tool-led" implementation.
IMPORTANT: Respond with ONLY valid JSON, no other text. Use this exact structure:
{{
"recommendations": [
{{
"title": "Clear, specific recommendation title",
"description": "2-3 sentence description of the solution",
"impact": "Expected time savings or business impact",
"implementation": "Brief overview of how this would be implemented",
"priority": "High"
}},
{{
"title": "Clear, specific recommendation title",
"description": "2-3 sentence description of the solution",
"impact": "Expected time savings or business impact",
"implementation": "Brief overview of how this would be implemented",
"priority": "Medium"
}},
{{
"title": "Clear, specific recommendation title",
"description": "2-3 sentence description of the solution",
"impact": "Expected time savings or business impact",
"implementation": "Brief overview of how this would be implemented",
"priority": "Low"
}}
],
"next_steps": "2-3 specific next steps they should take",
"timeline": "Realistic implementation timeline"
}}"""
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "user", "content": prompt}],
temperature=0.7,
max_tokens=1500
)
content = response.choices[0].message.content.strip()
# Clean up common JSON formatting issues
if content.startswith('```json'):
content = content[7:]
if content.endswith('```'):
content = content[:-3]
content = content.strip()
return json.loads(content)
except json.JSONDecodeError as e:
st.error(f"AI response format error. Please try again.")
return None
except Exception as e:
st.error(f"Error generating recommendations: {str(e)}")
return None
def generate_pdf_report(business_info, calculations, recommendations):
"""Generate PDF report"""
buffer = BytesIO()
doc = SimpleDocTemplate(buffer, pagesize=letter)
styles = getSampleStyleSheet()
story = []
# Header
title_style = ParagraphStyle(
'CustomTitle',
parent=styles['Heading1'],
fontSize=24,
spaceAfter=30,
textColor=colors.HexColor('#1f4e79'),
alignment=1
)
story.append(Paragraph("AI ROI Analysis Report", title_style))
story.append(Paragraph("Eau Claire AI - Your path to AI, made clear.", styles['Normal']))
story.append(Spacer(1, 20))
# Business Information
story.append(Paragraph("Business Information", styles['Heading2']))
business_data = [
['Company', business_info['company']],
['Industry', business_info['industry']],
['Employees', str(business_info['employees'])],
['Contact', business_info['email']]
]
business_table = Table(business_data, colWidths=[2*inch, 3*inch])
business_table.setStyle(TableStyle([
('BACKGROUND', (0, 0), (-1, 0), colors.HexColor('#f0f0f0')),
('TEXTCOLOR', (0, 0), (-1, 0), colors.black),
('ALIGN', (0, 0), (-1, -1), 'LEFT'),
('FONTNAME', (0, 0), (-1, 0), 'Helvetica-Bold'),
('FONTSIZE', (0, 0), (-1, 0), 12),
('BOTTOMPADDING', (0, 0), (-1, 0), 12),
('BACKGROUND', (0, 1), (-1, -1), colors.white),
('GRID', (0, 0), (-1, -1), 1, colors.black)
]))
story.append(business_table)
story.append(Spacer(1, 20))
# How AI Saves Money - Explanation Section
story.append(Paragraph("How AI Will Save Your Business Money", styles['Heading2']))
# Calculate key metrics for explanation
weekly_hours = calculations['annual_cost'] / 52 / business_info.get('avg_wage', 25)
hours_saved = calculations['hours_saved']
explanation_text = f"""
Based on your current operations, your team spends approximately {weekly_hours:.1f} hours per week on repetitive tasks
that can be significantly automated with AI. Here's how AI will generate savings:
AI ROI Calculator
Discover how much time and money AI can save your business
Your path to AI, made clear.
""", unsafe_allow_html=True)
# Methodology explanation - clean and professional
st.subheader("How We Calculate Your ROI")
st.markdown("Our calculations are based on conservative, real-world data to give you accurate expectations:")
# Use Streamlit columns for clean layout
col1, col2 = st.columns(2)
with col1:
st.markdown("""
**📊 Your Current Costs**
We calculate your annual labor cost for repetitive tasks using your team size, hourly wages, and time spent on manual work.
**💰 Implementation Costs**
We estimate AI costs based on your business size: software subscriptions, setup, training, and ongoing support.
""")
with col2:
st.markdown("""
**🤖 AI Automation Potential**
Research shows AI can automate 40-70% of repetitive tasks. We use a conservative 60% estimate for reliable projections.
**📈 ROI Calculation**
Annual savings minus total AI costs, divided by investment cost. We include both one-time and recurring expenses.
""")
st.info("**Conservative Approach:** Our estimates err on the side of caution to ensure realistic expectations and successful implementations.")
st.markdown("---")
# Main form
with st.container():
col1, col2 = st.columns([2, 1])
with col1:
st.subheader("Tell us about your business")
# Business information
company_name = st.text_input("Company Name*", placeholder="Your Company Name")
col_a, col_b = st.columns(2)
with col_a:
industry = st.selectbox(
"Industry*",
["", "Real Estate", "Construction", "Healthcare", "Professional Services",
"Retail", "Food & Beverage", "Fitness", "Manufacturing", "Other"]
)
with col_b:
num_employees = st.number_input("Number of Employees*", min_value=1, max_value=10000, value=10)
# Task analysis
st.subheader("Current Operations")
col_c, col_d = st.columns(2)
with col_c:
avg_hourly_wage = st.number_input("Average Hourly Wage ($)*", min_value=10.0, max_value=200.0, value=25.0, step=1.0)
with col_d:
hours_on_repetitive = st.number_input("Hours/Week on Repetitive Tasks*", min_value=0.5, max_value=80.0, value=10.0, step=0.5)
# Task breakdown
st.subheader("What takes up most of your team's time?")
task_options = {
"Data entry and manual record keeping": False,
"Email management and responses": False,
"Scheduling and calendar management": False,
"Report generation and analysis": False,
"Customer service inquiries": False,
"Invoice processing and accounting": False,
"Content creation and writing": False,
"Research and information gathering": False,
"File organization and management": False,
"Quality control and reviewing": False
}
selected_tasks = []
for task, _ in task_options.items():
if st.checkbox(task):
selected_tasks.append(task)
other_tasks = st.text_area("Other time-consuming tasks", placeholder="Describe any other repetitive tasks...")
if other_tasks:
selected_tasks.append(other_tasks)
# Contact information
st.subheader("Get Your Personalized Results")
email = st.text_input("Email Address*", placeholder="your.email@company.com")
phone = st.text_input("Phone Number (Optional)", placeholder="(555) 123-4567")
# Calculate button
calculate_button = st.button("Calculate My AI ROI", use_container_width=True)
with col2:
st.info("""
### What you'll get:
✅ **Personalized ROI Analysis**
See exactly how much time and money AI could save your business
✅ **Custom Recommendations**
AI-powered suggestions specific to your industry and needs
✅ **Implementation Roadmap**
Clear next steps to get started
✅ **Detailed PDF Report**
Professional analysis you can share with your team
---
**Powered by Eau Claire AI**
*Your path to AI, made clear.*
""")
# Validation and calculations
if calculate_button:
# Validate required fields
errors = []
if not company_name.strip():
errors.append("Company name is required")
if not industry:
errors.append("Please select your industry")
if not email.strip():
errors.append("Email address is required")
elif not validate_email(email):
errors.append("Please enter a valid email address")
if not selected_tasks:
errors.append("Please select at least one time-consuming task")
if errors:
for error in errors:
st.error(error)
else:
with st.spinner("Calculating your AI ROI and generating personalized recommendations..."):
# Calculate current costs
annual_hours_repetitive = hours_on_repetitive * 52
annual_cost_repetitive = annual_hours_repetitive * avg_hourly_wage
# Conservative automation estimates
automation_percentage = 0.6 # 60% automation potential
annual_labor_savings = annual_cost_repetitive * automation_percentage
hours_saved_weekly = hours_on_repetitive * automation_percentage
# Realistic AI Implementation Costs based on business size
def calculate_ai_costs(num_employees, selected_tasks):
# Base costs by company size - realistic market rates
if num_employees <= 10:
setup_cost = 3000 # Small business setup - basic automation
monthly_software = 200 # Basic AI tools (ChatGPT, Zapier, etc.)
elif num_employees <= 50:
setup_cost = 6000 # Medium business setup
monthly_software = 500 # More comprehensive tools
elif num_employees <= 200:
setup_cost = 12000 # Large business setup
monthly_software = 1200 # Enterprise tools
else:
setup_cost = 20000 # Enterprise setup
monthly_software = 2500 # Full enterprise suite
# Adjust based on complexity (number of task types)
complexity_multiplier = min(1.5, 1 + (len(selected_tasks) * 0.1))
setup_cost *= complexity_multiplier
monthly_software *= complexity_multiplier
# Annual ongoing costs
annual_software = monthly_software * 12
annual_maintenance = setup_cost * 0.15 # 15% of setup for maintenance
return {
'setup': setup_cost,
'annual_software': annual_software,
'annual_maintenance': annual_maintenance,
'total_year_one': setup_cost + annual_software + annual_maintenance,
'annual_ongoing': annual_software + annual_maintenance
}
ai_costs = calculate_ai_costs(num_employees, selected_tasks)
# Calculate net benefits
year_one_savings = annual_labor_savings - ai_costs['total_year_one']
annual_ongoing_savings = annual_labor_savings - ai_costs['annual_ongoing']
monthly_savings = annual_ongoing_savings / 12
# ROI calculations - fixed logic
monthly_net_savings = annual_ongoing_savings / 12
payback_months = ai_costs['setup'] / monthly_net_savings if monthly_net_savings > 0 else 0
# More intuitive ROI: Total profit over 3 years divided by initial investment
three_year_total_profit = (annual_ongoing_savings * 2) + year_one_savings # Year 1 (may be negative) + Years 2&3
roi_three_year = (three_year_total_profit / ai_costs['setup']) * 100 if ai_costs['setup'] > 0 else 0
# Annual ROI based on ongoing savings vs ongoing costs
roi_ongoing = (annual_ongoing_savings / ai_costs['annual_ongoing']) * 100 if ai_costs['annual_ongoing'] > 0 else 0
calculations = {
'annual_cost': annual_cost_repetitive,
'annual_labor_savings': annual_labor_savings,
'annual_ongoing_savings': annual_ongoing_savings,
'monthly_savings': monthly_savings,
'hours_saved': hours_saved_weekly,
'ai_costs': ai_costs,
'payback_months': payback_months,
'roi_three_year': roi_three_year,
'roi_ongoing': roi_ongoing,
'year_one_savings': year_one_savings,
'three_year_total_profit': three_year_total_profit
}
# Get AI recommendations
main_tasks_text = ", ".join(selected_tasks[:3]) # Top 3 tasks
recommendations = get_ai_recommendations(industry, num_employees, main_tasks_text, annual_labor_savings)
st.session_state.calculations_done = True
st.session_state.calculations = calculations
st.session_state.ai_recommendations = recommendations
st.session_state.business_info = {
'company': company_name,
'industry': industry,
'employees': num_employees,
'email': email,
'phone': phone,
'tasks': selected_tasks,
'avg_wage': avg_hourly_wage
}
# Send email notification
send_lead_notification(st.session_state.business_info, st.session_state.calculations)
# Display results
if st.session_state.calculations_done:
st.success("Your AI ROI Analysis is Complete!")
calc = st.session_state.calculations
# Key Metrics
col1, col2, col3, col4 = st.columns(4)
with col1:
st.markdown(f"""
{i}. {rec['title']}
{rec['priority']}
Description: {rec['description']}
Expected Impact: {rec['impact']}
Implementation: {rec['implementation']}
""", unsafe_allow_html=True)
# Next steps
st.subheader("Recommended Next Steps")
st.info(st.session_state.ai_recommendations['next_steps'])
st.info(f"**Timeline:** {st.session_state.ai_recommendations['timeline']}")
# Download report
st.subheader("Download Your Report")
if st.button("Generate PDF Report", use_container_width=True):
with st.spinner("Generating your personalized PDF report..."):
pdf_buffer = generate_pdf_report(
st.session_state.business_info,
st.session_state.calculations,
st.session_state.ai_recommendations
)
st.download_button(
label="Download AI ROI Report",
data=pdf_buffer,
file_name=f"AI_ROI_Report_{st.session_state.business_info['company'].replace(' ', '_')}_{datetime.now().strftime('%Y%m%d')}.pdf",
mime="application/pdf",
use_container_width=True
)
# Call to action
st.markdown("""
""", unsafe_allow_html=True)
# Reset button
if st.session_state.calculations_done:
if st.button("Calculate for Another Business", use_container_width=True):
st.session_state.calculations_done = False
st.session_state.ai_recommendations = None
st.rerun()