We reduced email response time from 4 hours to 12 minutes

Diagnosis: 68% of customers did not wait for a quote

At Impuls Poznań Consulting, we start with hard data because only numbers count. We analyzed 412 email threads of Trans-Luboń Sp. z o.o. from the period of March to April 2023. The result was painful: the customer service office, consisting of two people, was flooded with freight inquiries, which they answered manually. Each email required checking driver availability, calculating mileage in Google Maps, and manually entering the rate into a Word template. This took employees an average of 26 minutes of pure work on one inquiry, not counting coffee breaks or phone calls.

The problem was that forwarders and logisticians send inquiries to five companies at once. First come, first served. At Trans-Luboń, 68% of potential customers gave up on the service before the employee managed to send the finished offer. The company was losing about 14,300 PLN in margin weekly just because the process was slow and based on manual data transcription. This is a classic example of waste that we encounter in many companies in Greater Poland. We checked this on 423 clients, and the scenario is almost always the same: people are drowning in papers, and money is slipping through their fingers.

Instead of hiring a third person for the office, which would cost the company about 6,500 PLN per month with overheads, the owner decided on automation. It simply works better and doesn't get sick. Our goal was to eliminate manual route checking and automatically assign priorities to emails. No more manual work that was killing the profitability of this company.

In the transport industry, 68% of customers give up if they don't get a quote within the first hour of the inquiry.

Phase one: Email segregation and spam rejection

We started the implementation on June 12, 2024, by cleaning the inbox. It turned out that 42% of incoming messages were not quote requests, but shipment statuses, invoices from subcontractors, and simple spam. Employees had to read each of these emails, which distracted them and pulled them away from key sales tasks. We configured an algorithm that automatically recognizes the type of message based on keywords and sender, and then directs them to the appropriate folders.

We applied simple rules: invoices end up in the 'Accounting' folder, statuses in 'Realization', and quote requests in the 'URGENT - QUOTE' folder. Thanks to this, an office worker coming to work at 8:00 AM did not see 150 unread messages, but only 12 specific sales opportunities. This allowed them to focus attention on what actually brings profit. The average initial reaction time dropped immediately by 45 minutes in the first week of the system's operation.

We also introduced a mechanism for verifying the customer's tax ID (NIP) in the database. If the inquiry came from a regular customer with a good payment history, the system automatically assigned them a 'VIP' tag and moved them to the top of the list. This isn't magic; it's pure business pragmatism. At Impuls Poznań Consulting, we know that not every inquiry is worth the same amount of an employee's time.

Automatic freight calculator: No more Word

The biggest breakthrough was creating a simple bot that extracts data from the email. If a customer wrote: 'I need transport from Poznań to Berlin, 22 pallets, tomorrow', the system automatically downloaded this data. Then, the bot connected to a maps API and calculated the distance (271 km). Based on rates defined by the business owner (e.g., 4.20 PLN per km for a refrigerated truck), the system generated a preliminary quote within 4 seconds. Previously, it took a human 15-20 minutes of searching and calculating.

The office employee received a ready draft of the response. They only had to click 'Approve' and the message went to the customer. We added personalization to this – the system inserted the name of the contact person and the license plate number of the car that is closest to the loading point. The customer had the impression that a very efficient forwarder was sitting on the other side, whereas in reality, 90% of the work was done by a script. It simply works and eliminates human errors in calculations.

Implementing the entire calculation mechanism took us exactly 11 business days. We didn't play around with unnecessary analyses, but got straight to the point. From June 28, 2024, the system was already running at full speed. The owner of Trans-Luboń, Mr. Andrzej, admitted that for the first time in three years, he could leave the office at 4:00 PM without worrying about unanswered emails. That's a specific result, not fluff.

We shortened the quote preparation time from 26 minutes to 4 seconds. The employee only approves the result.

Effect: 12 minutes and 22% sales growth

Results after 30 days of full implementation exceeded the expectations of the Trans-Luboń board. The average response time to an inquiry dropped from over 4 hours to 12 minutes and 14 seconds. Thanks to such a fast reaction, the company started 'grabbing' orders that previously went to competitors from Gądki or Komorniki. In July 2024, the number of completed freights increased by 34 compared to the average of the previous six months, which translated into a revenue increase of 89,200 PLN net.

Office workers regained an average of 3.2 hours a day each. They used this time to actively call former customers and care for relationships with current contractors. Automation did not replace people, but took the burden of boring, repetitive work off them. Only numbers count: the implementation cost paid for itself after 19 days of the system's operation. It's an investment that pays for itself faster than any new truck on a lease.

If your company in Poznań or the surrounding area is losing time manually transcribing data from emails to Excel or Word, you're doing it wrong. We checked this on 423 clients – automation is the only way to scale a business without drastically increasing employment costs. At Impuls Poznań Consulting, we don't promise miracles, we show results. No more manual work, time to start earning on data.