Validation - what is it in simple words? How is validation different from verification? + PRACTICAL ADVICE

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What is validity? Description and definition of the concept.

Validity is

1) a measure of compliance, which shows how well the results obtained and the developed research methodology correspond to the objectives;

2) a fundamental concept in experimental psychology and psychodiagnostics. There are the following types of validity: content validity, construct validity, predictive validity, criterion validity. Only a theoretical impeccable experiment has impeccable validity: an experiment in which the resulting effect causes an independent variable corresponds completely to reality, and its results can be generalized without additional restrictions.

Validity (English validity, from Latin validus - “strong, healthy, worthy”) is the suitability and validity of using research results and methods in specific conditions. A more applied definition of the concept “validity” is a measure of compliance of the results and research methods with the assigned tasks. Validity is a fundamental concept of psychodiagnostics, organizational psychology, and experimental psychology.

In both statistics and psychology, a valid measurement is one that measures what it is supposed to measure (this narrow interpretation of “validity” is the most popular, it actually corresponds to the concept of “construct validity”). That is, for example, when validly measuring intelligence, it is intelligence that is measured, and not something else. An impeccable experiment (possible only in theory) will have impeccable validity: it will accurately show that the experimental effect is caused by a change in the independent variable, it will correspond completely to reality, and its results can be generalized without restrictions.

When talking about the degree of validity, they consider how well the results of the study correspond to the stated objectives (but validity is not measured in any conventional units).

An important feature of validity is that it cannot be established once and this evidence cannot be used as a final argument “for” the quality of a certain technique or experiment. Validity must be constantly substantiated by new data and rechecked in independent studies.

Difference between validation and verification [edit | edit code]

Verification - usually internal

a quality management process that ensures compliance with a rule, standard, or specification. A simple way to remember the difference between validation and verification is that validation confirms that “you created the right product”, while verification confirms that “you created the product the way you intended it to be” [2]. Another example of a typical verification: conducting equipment testing. With certain requirements in hand, we test the product and record whether the requirements are met. The result of verification is the answer to the question “Does the product meet the requirements?”

But not always a product that meets the established requirements can be used in a specific situation. For example, the medicine passed all the required tests and went on sale. Does this mean that it can be used by any specific patient? No, since each organism has its own characteristics and specifically for it, this medicine can be destructive, that is, someone (the doctor) must confirm: yes, this patient can take this medicine. That is, the doctor must perform validation: give legal validity to a specific application.

Another example: an enterprise produces pipes intended for laying in the ground, in accordance with certain specifications (Technical Specifications). The products comply with these specifications, but an order has been received that involves laying pipes along the seabed. Can pipes that comply with the existing specifications be used in this case? It is validation that provides the answer to this question.

You can see that another difference is that verification is always performed, but there may be no need for validation. It only appears when requirements arise related to a specific product application. If a pharmaceutical plant produces drugs, it will only check their compliance with the requirements, and will not deal with the problems of using specific drugs by specific patients.

Thus, the following can be stated:

  • verification - is almost always carried out, performed by checking (comparing) the characteristics of products with specified requirements, the result is a conclusion about the conformity (or non-conformity) of the product,
  • validation - carried out if necessary, performed by analyzing the specified conditions of use and assessing the compliance of product characteristics with these requirements, the result is a conclusion about the possibility of using the product for specific conditions [3].

Based on the above, validation should be defined as confirmation, based on the provision of objective evidence, that the requirements intended for a particular use or application are accurately and completely specified and the purpose is achieved.

Words such as “verification” and “validation” can be heard quite often in various television programs, but few people know what they mean. Their sound is quite similar, and those who pronounce these words often get confused by them themselves. From the context, the listener guesses that the matter in both cases is connected with checking something. What do these words really mean, what do they have in common, and how does validation differ from verification?

The validity of the methodology is

The validity of a technique determines the correspondence of what is studied by this technique to what exactly it is intended to study.

For example, if a psychological technique that is based on informed self-report is assigned to study a certain personality quality, a quality that cannot be truly assessed by the person himself, then such a technique will not be valid.

In most cases, the answers that the subject gives to questions about the presence or absence of development of this quality in him can express how the subject himself perceives himself, or how he would like to be in the eyes of other people.

Validity is also a basic requirement for psychological methods for studying psychological constructs. There are many different types of this criterion, and there is no single opinion yet on how to correctly name these types and it is not known which specific types the technique must comply with. If the technique turns out to be invalid externally or internally, it is not recommended to use it. There are two approaches to method validation.

The theoretical approach is revealed in showing how truly the methodology measures exactly the quality that the researcher came up with and is obliged to measure. This is proven through compilation with related indicators and those where connections could not exist. Therefore, to confirm a theoretically valid criterion, it is necessary to determine the degree of connections with a related technique, meaning a convergent criterion and the absence of such a connection with techniques that have a different theoretical basis (discriminant validity).

Assessing the validity of a technique can be quantitative or qualitative. The pragmatic approach evaluates the effectiveness and practical significance of the technique, and for its implementation an independent external criterion is used, as an indicator of the occurrence of this quality in everyday life. Such a criterion, for example, can be academic performance (for achievement methods, intelligence tests), subjective assessments (for personal methods), specific abilities, drawing, modeling (for special characteristics methods).

To prove the validity of external criteria, four types are distinguished: performance criteria - these are criteria such as the number of tasks completed, time spent on training; subjective criteria are obtained along with questionnaires, interviews or questionnaires; physiological – heart rate, blood pressure, physical symptoms; criteria of chance - are used when the goal is related or influenced by a certain case or circumstances.

When choosing a research methodology, it is of theoretical and practical importance to determine the scope of the characteristics being studied, as an important component of validity. The information contained in the name of the technique is almost always not sufficient to judge the scope of its application.

This is just the name of the technique, but there is always a lot more hidden under it. A good example would be the proofreading technique. Here, the scope of properties being studied includes concentration, stability and psychomotor speed of processes. This technique provides an assessment of the severity of these qualities in a person, correlates well with values ​​obtained from other methods and has good validity. At the same time, the values ​​obtained as a result of the correction test are subject to a greater influence of other factors, regarding which the technique will be nonspecific. If you use a proof test to measure them, the validity will be low. It turns out that by determining the scope of application of the methodology, a valid criterion reflects the level of validity of the research results. With a small number of accompanying factors that influence the results, the reliability of the estimates obtained in the methodology will be higher. The reliability of the results is also determined using a set of measured properties, their importance in diagnosing complex activities, and the importance of displaying the methodology of the subject of measurement in the material. For example, to meet the requirements of validity and reliability, the methodology assigned for professional selection must analyze a large range of different indicators that are most important in achieving success in the profession.

Verification in science

In science, verification is the testing of a scientific hypothesis (assumption) for compliance with objective criteria that are currently recognized as true. The method of scientific knowledge consists in putting forward hypotheses that explain any phenomenon in the world around us. Next, the author of the hypothesis collects evidence that its provisions do not contradict already known scientific facts and experimental data.

To do this, a series of natural or thought experiments are carried out, and if their results confirm the hypothesis, it is considered verified and becomes a scientific concept or even a theory.

What is validity in psychology

Validity is an important characteristic of psychological tests and techniques. It must be verified by experimenters along with the reliability of the technique. The validity criterion is most often used in psychodiagnostics. It reveals the problem of compliance of the data obtained during the study with the “ideal”. That is, those that are not distorted by any internal or external factors.

The problem of subjectivity is clearly expressed in psychology. No matter how accurate, in the opinion of the experimenter, the obtained data are, they are distorted. To check the level of reliability of the acquired knowledge, a validity criterion is used. Validity is not used in the exact sciences: physics, chemistry, mathematics.

This is a unique criterion of psychology that allows us to smooth out the difficulties of obtaining objective knowledge. The first reason for the appearance of this tool is the problem of accurately determining the characteristic or property being studied. Thus, when studying anxiety, it is impossible to unambiguously establish the phenomenon being diagnosed. Anxiety is fear, worry, and worry.

The second reason is the subjectivity of the parameter being studied using a psychodiagnostic technique. The developer puts his own meaning and meaning into the wording, but this does not mean that the subject thinks according to the same template. Interpretations of the same questions or statements can vary greatly.

In the exact sciences there is no problem of defining the object under study. The difficulty lies in the methods of study. For example, a physicist studying the parameters of an iron ball sees and touches it accurately. He set himself a goal: to study the radius of the ball. The parameter is objective and is found using measurements and formulas.

Verification in the production of goods and provision of services

In contrast to scientific verification, which leaves a lot of room for interpretation of the results of full-scale, and especially thought experiments, the concept of verification in the production of products or provision of services is clearly formalized and recorded in the standards of the quality management system.

The process began to be most widely used in software production and the development of complex technical systems. From these industries, the method spread to other industries.

Confirmation, based on the provision of objective evidence, that specified requirements have been met. (ISO 9000:2000)

Manufacturing verification is the collection of documentary evidence that the designed and manufactured product (or service) meets all requirements of the technical specifications, manufacturing specifications and industry standards at each stage of the production cycle. In the case of complex and lengthy production processes, it is important not to delay the collection of such evidence until the night before shipping the product.

In the production of complex systems and software products, the following verification methods are used:

  • carrying out alternative calculations;
  • comparison of documentation for the current project with documentation for the accepted and tested project;
  • carrying out testing according to the approved program;
  • analysis of project documents at different stages of readiness.

Testing and document analysis are the most widely and frequently used approaches. Comparison of scientific, technical and design documentation is also very popular, but for many advanced developments it is difficult to find a similar project.

Carrying out alternative calculations using an independent algorithm allows you to obtain a basis for assessing the accuracy of calculations performed using the algorithm being tested. One of the most commonly used alternative calculation methods is a calculator.

Details

Findings are said to have internal validity if the cause-and-effect relationship between two variables is correctly demonstrated. A valid causal inference can be made if three criteria are met:

  1. “cause” precedes “effect” in time (priority in time),
  2. "cause" and "effect" tend to occur together (covariation), and
  3. there are no plausible alternative explanations for the observed covariation (unpredictability).

In scientific experimental settings, researchers often change the state of one variable (the independent variable) to see what effect it has on a second variable (the dependent variable). For example, a researcher might manipulate the dosage of a particular drug between different groups of people to see what effect it has on health. In this example, the researcher wants to make a causal inference, namely that different doses of a drug may be responsible

for observed changes or differences.
When a researcher can confidently attribute observed changes or differences in a dependent variable to an independent variable (that is, when the researcher observes a relationship between these variables and can rule out other explanations or competing hypotheses
), then the causal inference is said to be internally valid.

However, in many cases the size of the effects found on the dependent variable may depend on more than just

  • variations of the independent variable,
  • the power of the instruments and statistical procedures used to measure and detect effects, and
  • choice of statistical methods (see: Reliability of statistical inference).

Rather, a number of uncontrolled (or uncontrollable) variables or circumstances may lead to additional or alternative explanations for (a) the effects found and/or (b) the size of the effects found. Therefore, internal validity is more a matter of degree than of either-or, which is why research designs other than true experiments can also produce results with a high degree of internal validity.

To draw conclusions with a high degree of internal validity, precautions may be taken during study design. Experience has shown that inferences based on direct manipulation of an independent variable allow for greater internal validity than inferences based on associations observed without manipulation.

When considering internal validity alone, strictly controlled true experimental designs (i.e., with random selection, random assignment to control or experimental groups, reliable instruments, robust manipulation processes, and safeguards against confounding factors) may be the "gold standard" of scientific research. However, the very methods used to enhance internal validity may also limit the generalizability or external validity of the results. For example, studying the behavior of animals in a zoo may facilitate the development of robust causal inferences in this context, but these inferences may not generalize to the behavior of animals in the wild. In general, a typical laboratory experiment studying a particular process may not account for many variables that typically strongly influence that process in nature.

Verification of the service subject

In this case, the identity of the user or some network service, such as Twitter, is identified. In this case, this means authenticating the user and confirming his identity. Similar identifications are carried out by other social media, online trading platforms and payment systems.

Verification of the borrower at the bank consists not only of establishing his identity, but also of checking his compliance with the bank’s requirements for the user of this product, such as:

  • having a positive credit history;
  • confirmed income;
  • real estate used as collateral, etc.

In Russian-language media, the term is sometimes used to mean “checking published facts.” This is purely Russian newspeak; the whole world uses the simple term “fact checking”, or “fact checking”.

Example of a violation of internal validity

Let's say we want to test a drug that will make people taller. Let's say for our research we select 13-year-old teenagers as test subjects, measure their height, and give them medicine. Two years later, we return to the now 15-year-old children and record their current growth. There is no doubt that they became taller, but there is also no doubt that we cannot conclude from this that the growth effect was caused by the drug, since we did not take into account the natural processes of maturation in our theoretical experiment. Here, internal validity is violated in the following way: we did not take into account the influence of other (in this case obvious) factors that were incidental to our research, whereas they should have been taken into account.

Validation in transport

A validator (from the English valid - “valid, lawful”) is also a special device that is used to check electronic travel documents. In this way, the eligibility of a passenger to board public transport is determined. Often the validator is combined with a turnstile. This allows you to save significant amounts of money on organizing and monitoring passenger fares. Such devices are also used to control the passage of employees onto the territory of the enterprise.

The relationship between the reliability and validity of psychological tests

The reliability of a test reflects its quality as a diagnostic method, in terms of formal indicators. Without taking into account the meaningful analysis of the results.

Validity evaluates the content of the test results. To what extent do they correspond to real psychological phenomena?

A reliable test may not be valid. For example, a test of initiative may show high test-retest reliability and part consistency. However, from a content point of view, the test results reflect not so much initiative as willpower. That is, the reliability of this test is high, but the validity is low.

In the practice of psychological testing, the reliability of tests using retest. The validity of psychological tests is typically tested by analyzing relationships with scores on other tests that measure similar or similar psychological indicators.

Validation in a quality management system

The wording in the ISO standard is somewhat vague and too similar to the definition of “verification”.

“Validation is confirmation, by the provision of objective evidence, that the requirements intended for a particular use or application have been met.”

Too academic formulations and not entirely successful translation confuse the reader. To answer the question: “Validation – what is it?” in simple words, let us again turn to the process of producing a product or providing a service. Validation is carried out in relation to a finished product that has already passed verification and meets all pre-formulated requirements. Its meaning is that in the process of validating a finished product or service, they receive confirmation from the consumer that the product or service meets his expectations in specific conditions.

Other types of validity

In addition to the main ones, there are also other types that correspond to other stages of experimental research. There are more than a dozen types of validity, which in many ways, including threats, are similar to the main ones. Only the nature of their violation changes. Let's briefly look at some of them.

Ecological - shows how well the experimental conditions correspond to the reality being studied. A high degree of ecological validity is quite difficult to maintain in laboratory studies, and it is not always necessary. And in field experiments it naturally reaches a maximum.

Diagnostic (competitive) – reflects the correspondence of the test indicators to the state of the psychological characteristics of the subject at the time of the study.

Prognostic – characterizes the degree of statistical reliability and validity of the development of the psychological feature that is being studied in the future.

Empirical - this concept combines the previous 2. The general approach to their determination is emphasized, carried out by statistically correlating test scores (grades) and an indicator based on an external criterion.

Main difference

What is the main difference between verification and validation?

Verification is a mandatory internal process of checking a product or service for compliance with standards and specifications.

“Do you have any complaints about the buttons?

-Do you have any complaints about the lapels?

Do you have any complaints about the sleeves?

Validation is the process of checking the applicability to specific conditions of a finished product that has been verified to comply with standards and specifications.

“Can I wear a suit?

Checking the database for validity

Mailing to an unreliable database is a waste of money, the risk of being blacklisted by mailers, blocking in ESP platforms and simply ruining the sender’s reputation. You don't need all this, do you?

To check the list of contacts for validity, validators are used - special services (for example, mailvalidator.ru). They check mail in three stages:

  • address syntax and format;
  • domain and service verification;
  • confirmation of mailbox activity.

This is what a complete address check looks like:

And this is an express check of the database:

Of course, you can check the database manually, but this is not the most effective story: this way you can only correct obviously bad emails and delete duplicates. Therefore, it is better to check the database automatically in the mailing platform or through special services.

Verification and Validation Examples

A drug manufacturing plant will always check whether they comply with specifications and standards (verification), but will not check whether these drugs are suitable for a certain patient with a certain set of symptoms (validation).

The company produces boots designed for country walks. These boots are fully compliant with specifications and this is checked for each pair (verification). But whether these shoes are suitable for high-altitude ascents remains to be determined separately (validation).

Another example that applies to almost any enterprise. The technical control department carries out verification, and auditors carry out validation.

Hello, dear readers! Welcome to the blog!

Validation - what is it in simple words? How is validation different from verification? The answers to these questions are in the article.

Many words “validation” and “verification” are considered synonymous. But that's not true. There is a difference, but it is very subtle. Let's figure it out.

How else can you check the layout?

In addition to the classic validator, there is another type of tool - the so-called hinters. Typically, these are plugins for code editors that, when writing code, automatically highlight errors and indicate what needs to be fixed. One such plugin is HTMLHint for the VS Code editor.

Hinter works according to certain rules, which are quite similar to the rules of a validator. But ideally, you should check the layout with both a hinter and a validator to ensure everything is correct.

The list of hint rules can be found here.

Bulk check of html validity of site pages

You can massively check site pages for validity and other technical SEO problems using a free program (there are limitations): WebSite Auditor. We launch it, create a project, enter the site address - further - further. We are waiting for all pages to complete checking. We go to the item on the page with errors in the code and run a validation check. all pages of the site.

After which we get a list of pages where there are errors, with the ability to go to the validator.

Usually, if the site is on a CMS, then the errors are hidden in the templates and by correcting the template, we automatically close them. And sometimes because something was not filled out.

Validation and verification - what is it in simple words?

To be fair, it must be said that in different areas of activity (in banks, in payment systems, on the Internet), in different industries, these terms are used differently. I decided to present here the definition of validation and verification from the ISO 9000 standard.

How is validation different from verification?

So what is verification? You can learn more in detail from this article, but here we will briefly say that the word “verification” comes from the English word “verification” - check . And the word “validation” comes from the English “validation” - giving legal force .

Warming up the base

Warming up the database means sending letters in parts with a gradual increase in the number of one-time sends. It is important to start sending from active segments of the database that have previously received and opened letters. If there are none (email marketing is at the implementation stage), then simply send it to verified addresses.

An example of warming up a base of 100,000 subscribers: 5,000 - 10,000 - 15,000 - 30,000 - 50,000 - 80,000 - 100,000

It is necessary to warm up the database not only at the start, but also if mailings have not been launched on it for a long time. The first shipment will give the most clearance and may show a high percentage of delivery errors. This is fine.

Focus on statistics and monitor deliverability. If there are few errors, you can increase the number of one-time submissions. The normal rate of errors and complaints when sending newsletters is up to 1%. This means there are no problems with the database. If it is 2–5%, it means that some of the addresses are invalid and it is necessary to revive the contact database.

Practical advice

You may ask why you need to understand these terms? I will say that there are also practical benefits. The main purpose of verification and validation is security, so that your bank cards and accounts are protected. However, taking advantage of the fact that many do not understand these terms, attackers often use a method to steal personal data such as a message asking you to verify or validate your bank card, account, etc.

Practical advice: When a window appears asking you to verify or validate your data, check the site data in the address bar to see if there are any missing or extra characters. Or try logging into this program from another device and if such a message does not appear, then your computer needs to be treated for dangerous viruses.

Psychometric properties of psychodiagnostic methods

The psychometric basis of any technique is scales. The concept of “scale” is interpreted in a broad and narrow sense: in the first case, the scale is a specific technique, in the second case, it is a measurement scale that records the characteristics being studied. Each element of the technique corresponds to a certain score or index, which forms the severity of a particular mental phenomenon.

Measuring scales are divided into:

  • Metric: interval, ratio scales.

  • Non-metric: nominative, ordinal.
Scale nameExplanation, examples
Nominative (scale of names)Based on a common property or symbol, assigns an observed phenomenon to the appropriate class.
The naming scale is the most common in research psychodiagnostic methods.

This scale is used, for example, in test questionnaires. The subject's denial or affirmation is compared with the answers in the key. Also, a nominative scale may involve the selection of one or more characteristics from those proposed.

OrdinalDivides the sum of characteristics into elements based on the “more is less” principle.
Thus, it arranges the results in ascending or descending order. An ordinal scale is used in the color choice test. The subject is asked to choose one of the squares on a white background, after which the selected figure is put aside and the procedure is repeated. Result: arranged according to the degree of attractiveness for the tested color. Each figure is assigned its own serial number.
IntervalThe elements are ordered not only according to the principle of severity of the measured characteristic, but also on the basis of the distribution of characteristics by size, which is expressed by the intervals between the numbers assigned to the degree of expression of the measured characteristic.
Interval scales are often used when standardizing primary test scores.
RelationshipsArranges elements by numerical value, maintaining proportionality between them.
Objects are divided according to the property being measured. The numbers that are equated to object classes are proportional to the degree of expression of the properties being studied. Used, for example, to determine the sensitivity thresholds of analyzers. Often used in psychophysics.

After determining the scale used to form the test, it is necessary to determine the coefficient of the psychometric properties of the technique.

These include:

  • Representativeness.
  • Standard.
  • Reliability.
  • Validity.

Representativeness is a property that extends to a sample of subjects. It can characterize both a population and a general population. Representativeness has two parameters: qualitative and quantitative. The qualitative parameter characterizes the choice of subjects and methods of constructing the sample.

A quantitative parameter is the sample size expressed in numbers.

In psychological research, this property determines the extent to which results can be generalized. For example, relationships between men and women are studied. If we take subjects of different ages (schoolchildren, students, adults, pensioners), then the representativeness of such a sample will be low.

However, if the subjects are approximately the same age and field of activity (only schoolchildren, students, adults, pensioners of both sexes), then the representativeness will be high. In psychodiagnostics, representativeness is used to indicate the possibility of applying a technique to the entire population.

Standardization is a simplification of the methodology, bringing parts of the roadmap and application procedures to uniform standards. PDM should be universal and applicable by different specialists in different situations. If the structure of the PDM deviates from the standards, its results will not be comparable with the results of other studies. Non-standardized methods are used mainly for scientific research.

With their help, new mental phenomena are studied. But this technique cannot be used for psychodiagnostic purposes. Another important parameter of the LDM is reliability. It characterizes the accuracy, stability and stability of the results obtained using a specific technique.

The high reliability of the technique eliminates the influence of extraneous factors and significantly brings the experiment closer to a “pure” one. The criterion of reliability and validity are different concepts. Moreover, reliability is interpreted more broadly than validity: reliability > validity.

For example, on a day off a person gets the opportunity to spend time either fishing or hunting. If he decides to go hunting, but takes a fishing rod with him, then his choice will not be valid. However, if a person went hunting with a gun and it misfired, then the chosen method is unreliable.

Services for checking addresses

There are free sites for checking one mailbox. For mass verification, both individual independent verification services and PC software (ePochta Verifier) ​​or tools built directly into the mailing service are used. We recommend several online validators that will help you work with the database.

Mailvalidator

Online platform for quality control of contact database. A list of emails can be loaded into it as a file, and it is also possible to connect directly to the service via the API. Diagnostics includes:

  • syntax;
  • duplicates;
  • spam traps and contacts from which complaints are often received;
  • non-existent and inactive domains;
  • bounces for each address.

What's good: two types of verification. Express for email addresses with available mail history and full verification for all others. Visualized reports in the form of graphs, personal recommendations for improving the quality of the contact database, Russian-language interface.

ESP platforms themselves use Mailvalidator as a built-in tool. For example, Mailganer.

The price for one check depends on the number of emails. The more there are, the more profitable.

Zero Bounce

Online verifier that accepts files in TXT and CSV format.

  • Removing addresses with delivery errors (hard/soft bounce)
  • Cleaning up spam traps and contacts that generate a lot of complaints
  • Find more information

What's good: the service finds missing information by email (first name, last name, gender, city, country, IP), 24/7 support.

There is a free plan if there are few addresses. Further - already by subscription + you can customize it depending on the needs of the business (up to Enterprise with unlimited testing for $999).

Snov.io

Offers secure real-time cleaning of email lists and helps remove all catch-all and invalid addresses. You can upload a list of addresses as a file, use a web application, or connect Email Verifier to CRM via API. In addition, you can add and verify addresses using the Email Verifier extension for Chrome.

  • Checking the address and domain for catch-all
  • Syntax checking
  • Checking the address for a random set of characters
  • Checking the existence of a domain
  • Checking MX records
  • SMTP authentication
  • Freemail check
  • Removing duplicates

What’s good: individual verification, import of lists of addresses for verification and export of verification results in a convenient format, integration via API with CRM platforms, large selection of tariffs.

Pricing varies: five tariffs to choose from, as well as two months free when you sign up for an annual subscription.

Check your contact databases before sending, and then your emails will only end up in your inbox. Yes, at the end the number of addresses will be reduced, but these will be active subscribers who are interested in your newsletter.

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