Cold Mailing in 2025
A comprehensive guide to cold mailing in 2025 – from infrastructure and targeting to effective messages and campaign optimization.
A comprehensive guide to cold mailing in 2025 – from infrastructure and targeting to effective messages and campaign optimization.
From this post, you will learn how to ensure delivery to the recipient's inbox at a level of >95% and receive specific instructions on what and how to prepare to give your campaign the best chance of success.
Start by preparing a generalized list of tasks to be performed:
The sending infrastructure is the foundation of the campaign. Remember that one of your campaign's effectiveness parameters is getting your message to the recipient's inbox in the inbox folder, and this is secured by a well-prepared sending infrastructure.
In cold mailing, ALWAYS use a substitute domain.
If your main domain is xyz.com, purchase a substitute domain named xyz.net, .co, .org, or use another variant of your domain name. Remember that tagging as SPAM can occur at the level of the mailbox, domain, and IP address from which the sending is conducted. Using your main domain for automated outbound purposes may expose it to being flagged as SPAM by systems monitoring the number of messages sent, their nature and repetition, the number of responses obtained, and the correctness of the addresses to which you send. Improperly conducting a cold email campaign can cause all messages sent by your organization to be marked as SPAM.
When you purchase a new domain for cold mailing purposes, you will need to set DNS records.
It depends on how many addresses you want to send a certain number of messages to in a given time interval.
The most important metric to follow is not exceeding 50 messages sent per day per mailbox.
REMEMBER, an alias is not a separate mailbox.
If you send 3 email messages to each prospect on your list, one mailbox will be enough to contact a maximum of ~16 people per day, which in 4 full weeks of campaign operation gives you 320 people possible to contact. If you send 4 messages to each prospect, you can contact ~13 people per day because at the peak sending moment, the system will send 4 * 13 = 52 messages per day.
It can be simply said that one mailbox is enough to sensibly contact about 300 people per month.
Depending on the designated number of mailboxes, I recommend having a maximum of 4 mailboxes on one domain.
You need to consider several variables:
To answer specific questions related to the sending schedule, you need to know data about at least a few of these variables.
For example:
How many mailboxes do I need if I want to contact 1000 people starting the campaign in 30 days on a Monday and finish it in a maximum of 10 days by sending a maximum of 3 messages to each person over 5 days. There are no pauses during sending due to, e.g., holidays.
The answer is: 12 is enough, and 13 will be a safe amount.
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If you think your services or products are very generalized because, for example, you can do marketing in any industry, try to think about how you can help a law firm, a manufacturing plant, and a software house.
I bet the set of services will differ significantly.
Who will the IT company come to?
To a company that says:
or
Although problems in companies of different sizes are similar, their scale, the possibility of implementing a solution, and the speed of action are not. In smaller companies, the problem is often the budget, in larger ones, the complexity of action and required experience. Choose your group accordingly and consider whether putting companies with 11-50 employees and 200-1000 in one basket is sensible and whether the value and message to them should be the same.
Your market is not Europe, but the countries or ethnic groups inhabiting it.
Country to country, language to language, society to society - we differ and look at the world differently.
In Europe, for example, we can find common features for countries in the DACH region, for the Baltic countries, i.e., Estonia, Latvia, Lithuania, for the Scandinavian countries, etc. Before you start looking for people to contact, think about the characteristic features of the language of a given community. For example, Project Manager in different European languages sounds like this: Projektijuht, Responsabile del progetto, Projektleder, Gerente de proyecto, Projektmanager, Projektipäällikkö. I will also save you a lot of time and energy by saying that when you search for companies and specific positions by keywords in the language of a given country, the number of records found in some industries will increase by 30-40%, but not only the language is important. The way of being, character, communication.
For example:
If you contact Mateusz Sekta from Poland, you will write to him:
If you contact Mateusz Sekta from Germany, you will write to him:
And this is important because it affects the conversion from the campaign or the sentiment of the response from country to country. A simple change from first name to last name conditioned by culture.
Location also matters from the perspective of contact time. A production hall director from Texas or Germany will probably not be happy with a message received in the middle of the night.
One of the simplest ways to define a target group is to analyze your old clients and projects for them. Consider whether you can find model-like clients. Consider evaluation criteria such as: industry, location, company size,
Choose the first contact group in such a way that it is as small as possible. For example, 500-1000 companies, in which there will be an adequate number of decision-makers for whom email addresses will be found. This is also an approach that allows validating a thesis on a small group, which can always be scaled instead of unnecessarily exploiting our target group with unnecessary communication. If something works, replicate it, if not, draw conclusions and “plow”.
The proposed sample size is not insignificant. Having a group of about 1000 companies, you probably won't find a person in all companies in a specific group of positions you're looking for, which gives a conversion from company to found decision-maker persona in this company ~60-80%.
Assuming the conversion will be lower (60%), your database will contain ~600 people, and you will need to find email addresses for them. The average conversion from found people to found, verified, corporate, personal email addresses for them is ~70%, which gives us a group prepared to contact about 420 people.
I will divide this list into three levels of advancement.
For beginners, Sales Navigator or similar tools that also rely on LinkedIn-based data will suffice. You will find a powerful database of people and companies there, relatively organized. The ease of this database comes from the coupling of people with companies. You know who works where. The biggest challenge is processing the amount of data and exporting it in a sensible form from the tool.
This is any data list you find online by entering, for example, the phrase: list of startups in the agrarian industry in Germany or participating in an industry event and having access to the list of event participants. The challenge is to find a source of sensible, quality data, scrape it, and link the list of companies with the appropriate people. There are 2 options: manual or automatic scraping, and then searching for email addresses.
Most countries maintain digitized company registers that categorize company data based on economic codes similar to PKD in Poland. Look for such registers, learn to use them and connect with them, and you will be among the top researchers in the world when it comes to finding specific companies. The challenge is the multitude of registers, but their data is relatively very organized and not often exploited by other companies because access is definitely more difficult. Also, registers of institutions of specific institutions associating organizations, for example, in the hotel or medical industry, are worth attention. The key in research is to use databases that are not exploited by others.
Example sources of message personalization are:
The data structure is important from the perspective of later data description, their completeness in the CRM system for the information of other involved and further processing for recycling sales processes.
My proposal for the structure of such data, which is always helpful for everyone involved in the sales process, is:
You can treat this list as columns for your sheet.
Remember to pay attention to when setting up a campaign: