Skip to content Skip to sidebar Skip to footer

Our Projects and Real Case Studies

Automation for Customer Support with ChatGPT, ManyChat, SimplyBook

Overview: In an effort to enhance customer support efficiency and reduce operational costs, we replaced a real administrator with a sophisticated chat-bot capable of handling customer inquiries regarding services and prices. This chat-bot, integrated with our social media platforms, operates 24/7, ensuring constant availability to our customers.

Project Implementation:

  • Initial Setup: We uploaded all relevant information from our website into a structured database. This included detailed descriptions of our services and a comprehensive list of prices.
  • Chat-Bot Training: The chat-bot was trained using this data to provide accurate and prompt responses to customer inquiries. It was also programmed to understand and correct grammatical errors to improve communication clarity.
  • Cost and Timeline: The project involved a one-time implementation cost of €2,000, with ongoing monthly maintenance costs of €150.

Challenges:

  • Limited Administrator Availability: The real administrator was available only from 10 AM to 6 PM, leaving customer queries unanswered outside these hours. This limited availability often led to delayed responses and potential loss of business opportunities.
  • Manual Workload: The administrator’s manual handling of inquiries was time-consuming, leading to inefficiencies and a higher likelihood of human error.

Benefits of Automation:

  1. 24/7 Availability: The chat-bot operates round the clock, ensuring that customer inquiries are addressed promptly at any time of the day or night. This has significantly improved customer satisfaction and engagement.
  2. Cost Efficiency: With a monthly cost of €150 for maintaining the chat-bot, the automation has proven to be cost-effective compared to the expense of a full-time administrator. Assuming an administrator’s salary is around €1,500 per month, the annual savings amount to approximately €16,200 (€1,500 x 12 months – €150 x 12 months).
  3. Increased Efficiency: The chat-bot’s ability to handle repetitive inquiries has reduced the manual workload by 50%, allowing the remaining administrative staff to focus on more complex tasks.
  4. Enhanced Customer Experience: By providing instant responses and reducing wait times, the chat-bot has improved the overall customer experience. According to feedback, 78% of our clients have rated the new system as very positive.
  5. Higher Conversion Rates: Since implementing the chat-bot, our conversion rates from social media inquiries have tripled, showcasing a direct impact on our sales and customer acquisition.

Value Calculation:

  • Cost Savings: The monthly cost of employing an administrator is approximately €1,500. Over a year, this amounts to €18,000. By replacing the administrator with a chat-bot, which costs €150 per month, the annual cost is reduced to €1,800 (€150 x 12 months).
  • Implementation Cost: The one-time project realization cost was €2,000.
  • Total Annual Savings: The total annual savings from this automation project is calculated as follows:
    • Annual Administrator Cost: €18,000
    • Annual Chat-Bot Cost: €1,800
    • Annual Savings: €18,000 – €1,800 = €16,200
    • Initial Project Cost Recovery: (€16,200 – €2,000) = €14,200 in net savings within the first year.

Conclusion: The implementation of a chat-bot for customer support has not only streamlined our operations but also resulted in substantial cost savings and enhanced customer satisfaction. By automating the process, we have been able to provide continuous support, increase our conversion rates, and significantly reduce the manual workload of our administrative staff.

Complex Solution for Real Estate and automated outrech Custom Python Script + Telegram + MAKE + SMS API

Project Overview: The project aimed to enhance the lead generation process for real estate deals by automating the retrieval and processing of potential customer data from SS.LV. This was achieved by developing a custom scraping tool with advanced capabilities, including CAPTCHA bypass and automated messaging.

Project Cost: €5,000

Challenges:

  1. Initial Customer Contact: SS.LV’s real estate listings do not display phone numbers, making it difficult for agents to initiate contact with potential buyers.
  2. Content Filtering: There was no efficient method to check and filter the content of the listings to identify and prioritize genuine leads.

Solution Provided: We developed an individual scraping tool designed to:

  • Scan SS.LV listings with an integrated anti-CAPTCHA system to decode phone numbers.
  • Send the extracted data (post description, price, date, and phone number) to a Telegram channel for immediate access.
  • Filter mobile numbers to identify whether they belong to real estate agents.
  • Send an introductory message via SMS API with a link to a registration contact form.

Implementation Details:

  • Initial Setup Cost: €5,000
  • Monthly Maintenance Cost: €200

Financial Analysis:

  • Commission Rate: 3-5% from each real estate deal.
  • Average Sale Price: Between €50,000 and €400,000.
  • Conversion Rate for SMS: 6%.

Calculation of Payback Period:

  1. Expected Revenue from Conversions:

    • Assuming an average deal size of €100,000 (midpoint of the average sale price range).
    • Minimum Commission: 3% of €100,000 = €3,000
    • Maximum Commission: 5% of €100,000 = €5,000
  2. Monthly Conversions Needed to Break Even:

    • Let’s assume a conservative approach with the minimum commission rate of 3%.
    • Monthly Maintenance Cost: €200
    • Break-even revenue per month: €200
    • Number of deals needed per month to break even: €200 / €3,000 = 0.067 deals per month (approximately 1 deal every 15 months).
  3. Calculation of Positive Cash Flow Period:

    • Initial Investment: €5,000
    • Monthly Positive Cash Flow Post-Break-even:
      • Minimum per deal: €3,000 – €200 = €2,800
      • Maximum per deal: €5,000 – €200 = €4,800
    • Number of deals needed to cover initial investment:
      • At minimum commission: €5,000 / €2,800 ≈ 1.79 deals
      • At maximum commission: €5,000 / €4,800 ≈ 1.04 deals
  4. Expected Time to Positive Cash Flow:

    • With a 6% conversion rate, let’s assume the tool processes 100 potential leads per month, yielding 6 deals.
    • Time to achieve 1.79 deals (minimum commission): 1.79 / 6 ≈ 0.3 months (approximately 1 month)
    • Time to achieve 1.04 deals (maximum commission): 1.04 / 6 ≈ 0.17 months (approximately 1-2 weeks)

Conclusion: The implementation of the scraping tool and automated messaging system significantly improves the efficiency of initial customer contact and lead generation in the real estate sector. Given the average deal size and conversion rates, the project is expected to break even and start generating positive cash flow within approximately 1 month of operation. The automation provides a scalable and cost-effective solution, potentially leading to substantial revenue increases with minimal ongoing costs.

This case study illustrates the value and effectiveness of using technology to optimize business processes and improve lead conversion rates in the real estate industry

Esi pirmais pie klienta Custom Python Script + ChatGPT + MANYCHAT
Slide 1 Heading
Lorem ipsum dolor sit amet consectetur adipiscing elit dolor
Click Here
Slide 2 Heading
Lorem ipsum dolor sit amet consectetur adipiscing elit dolor
Click Here
Slide 3 Heading
Lorem ipsum dolor sit amet consectetur adipiscing elit dolor
Click Here
Previous slide
Next slide

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.