Sampling is undoubtedly a very important process in an investigation. Thanks to this process, the correct answers or the most actionable results can be obtained. That is why today we decided to learn more about river sampling so that you can evaluate if it is what you need for your project.

River sampling is a type of non-probability sampling that came to be incorporated into the already impressive set of available data collection methodologies.

And while researchers understand the importance of randomly selecting a sample from an entire population (whatever that population is), for others probability sampling is a tough challenge to overcome, especially in today’s Internet-centric world.

The difference between non-probability and probabilistic sampling is that the former does not involve random selection and the latter does. This does not imply that the non-probability samples are not representative of the population; it means, however, that non-probability samples cannot depend on the foundation of probability theory.

While using the internet only to obtain potential respondents means giving up some of the randomness itself, it does not mean that meaningful results cannot be obtained through river sampling.

What is River Sampling?

River sampling is an online survey sampling method that obtains survey respondents by requesting online visitors to take a survey by clicking on a link that routes them to the survey. It is entirely random and organic, with no website monitoring.

You might be thinking of softly trickling mountain streams. Or maybe rushing whitewater rapids. But “river sampling,” gets its name more from the life within the river, rather than the river itself. Consider this analogy: You’re a fisherman. You determine where the fish are gathering in a specific river. You stop and cast your line into that river. You don’t know what kind of fish you might catch. You don’t know its color or type.

You don’t know if it has any remarkable features. You don’t know where it has been or what it has done previously. You catch one, though. And once you catch it, you unhook it and throw it back in. You’ll probably never see it again. Such is the case for river sampling in the market research world.

River sampling invites respondents to take a survey via online banners, ads, promotions, offers, and invitations placed on a variety of websites. Once their attention is caught and they click on a link, they are asked several screening questions and are finally routed to a survey based on their answers. Surveyors have no idea who will respond. They don’t know any demographic or psychographic features of their survey takers, and they can’t contact them upon survey completion.

River sampling is an online sampling method that recruits respondents by inviting them to the survey while they are doing some other online activity.

The invitation to carry out a survey can be through online banners, advertisements, promotions, offers, and invitations placed on various websites.

Once their attention is captured and they click on a link, they are asked several screening questions and finally directed to a survey based on their responses.

Consider this analogy: You are a fisherman. You see where the fish gather in a particular river. You stop and cast your net in that river. You don’t know what kind of fish you can catch. You do not know its color or its type.

You don’t know if it has any remarkable features. You don’t know where he has been or what he has done before. However, you catch one. And once you catch it, you unhook it and throw it back. You probably won’t see it again. That’s what happens in river sampling in the world of market research.

Pollsters have no idea who is going to answer. They do not know the demographic or psychographic characteristics of the respondents and cannot contact them again after the survey is completed.

River sampling can serve as a way to complement other types of sampling.

River sampling is an online survey sampling method — the earliest and simplest of its kind. This non-probability sampling method obtains survey respondents by requesting online visitors to take a survey via clicking on a link that routes them to the survey.

The link is placed somewhere in a webpage, email or another area in the digital space. Typically, respondents are scouted through web elements such as banners, ads, promotions and offers.

When site or app users click on the link used in river sampling, they are first routed to the screener portion of the survey and if they fit the requirements set in the screener, they are then routed to the questionnaire portion.

River sampling derives its name from the metaphorical idea that researchers net their study subjects by catching them in the river that is the internet, specifically the flow of traffic in a website.

Also called intercept sampling and real‐time sampling, this method extracts respondents by engaging them while they take part in some other digital activity.

Why is River Sampling Important?

Here are a few reasons why river sampling is significant in non-probability research:

• Cost-effective: River sampling can be less expensive compared to other methods, as it leverages existing online traffic and does not require an extensive sampling frame or recruitment process.
• Quick data collection: Since river sampling relies on intercepting respondents during their regular online activities, data can be collected quickly, which is beneficial in situations where time is a constraint.
• Access to niche populations: River sampling can help researchers access hard-to-reach or niche populations who may not be easily found through traditional sampling methods. By targeting websites or platforms where these groups congregate, researchers can gather insights from specific segments of the population.
• Flexibility: River sampling can be easily adapted to different research objectives or target populations. By choosing the appropriate websites or platforms, researchers can tailor their sampling to meet their needs.
• Real-time insights: River sampling can provide real-time insights into the opinions, preferences, and behaviors of the online population. This information can be valuable for tracking trends or understanding the immediate impact of events or changes in the market.

Types of River Sampling

1. Stratified River Sampling: This kind of river sampling involves drawing samples in real-time from online promotions, those that are disseminated through banners, ads, pop-ups and hyperlinks. Market researchers would choose the websites for survey deployment based on statistics on such websites’ traffic.
2. Convenience River Sampling: This sub method of river sampling involves the placement of promotions and hyperlinks across websites without previously analyzing the websites’ traffic numbers and types of visitors. As such, market researchers deploy surveys in a completely blind manner. The point of this form of sampling is to derive maximum data at a minimum cost.
3. Layered River Sampling: Samples are created in real time from online promotions using methods such as banners, pop-ups and hyperlinks. The agency carefully selects the websites based on the statistics available on the website visits / visitors. By having the respondents, they are redirected to a portal, where they are selected to participate in a specific research project. Knowing the viewers of each site and the response patterns of your visitors is a key part of effective recruitment. Businesses wanting to conduct a river sampling survey rarely have access to the full range of sites they need or detailed demographic information on the visitors to those sites, so they are forced to work through carefully selected intermediaries.
4. River Sampling for Convenience: Links are placed on various websites without prior analysis of the background of your visits / visitors. The main objective is to collect the maximum data with a minimum cost. To increase participation rates, users are inclined to place banners on sites related to the subject.

Features:

• To some extent, “river sampling” recruitment can be compared to recruitment on the street: respondents on the digital highway have the opportunity to participate in the research project.
• The representativeness of recruitment on the street is reduced by the bias of no answer; the representativeness of recruitment in the river is biased by a self-selection bias, which can be considered a specific form of non-response.
• In the past, the origin of the people who would be part of a sample was highly questioned. If they came from social networks, for example, they were rejected, there were more restrictions.
• Today, given the shortage of panelists, many companies have chosen to acquire their samples from various sources, they are aware of the bias that may exist, and based on this they design their research.
• Respondents recruited by “river sampling” have less experience completing surveys, which means they take longer to answer.
• It must be said that the accuracy of the research results is compromised to a greater extent by the self-selection bias than by the non-response bias, so the use of river convenience sampling limits the scope of the research objectives. achievable and can only be used under strict conditions.

Do you Need a Research Sample?

A research sample is essential when conducting a study to gather insights and make informed decisions. It is a subset of a larger population that represents the target group of interest.

Choosing an appropriate sampling method is crucial to ensure the accuracy, reliability, and validity of your research findings.

Here’s a brief overview of convenience river sampling and layered river sampling, along with when to use each method:

Convenience River Sampling

This non-probability sampling method involves intercepting respondents during their regular online activities on various websites or platforms. The sample is composed of individuals who are readily accessible, making the data collection process faster and cost-effective.

When to Use Convenience River Sampling:

• When you have limited time or budget for data collection.
• When you need to access hard-to-reach or niche populations.
• When you’re conducting exploratory research or pilot studies to gather initial insights or generate hypotheses.
• When statistical representativeness is not a priority, and you need qualitative insights or real-time data.

However, it is essential to note that Convenience River Sampling can be subject to selection bias, as it does not guarantee a representative sample of the broader population.

Layered River Sampling 

Layered River Sampling is a variation of the river sampling method that involves segmenting or stratifying the sample based on specific characteristics or criteria (e.g., demographics, geographic location, or online behavior). This approach can help ensure better representation of different subgroups within the population.

When to Use Layered River Sampling:

• When you want to improve the representation of specific subgroups in your non-probability sample.
• When you’re conducting research on a diverse population with distinct characteristics or behaviors.
• When you need to compare or analyze the differences between subgroups within your target population.
• When you’re trying to minimize potential biases associated with convenience river sampling.

Although layered river sampling can provide more balanced insights, it still does not guarantee statistically representative results. Researchers should be cautious when generalizing findings and consider using other sampling methods or data sources to validate or complement their results.

River Sampling vs. Panel Sampling

What is River Sample?

A sample where “survey respondents are invited via the placement of ads, offers or invitations online. River sample may also be referred to as web intercept, real time sampling, and dynamically sourced sampling” (Source). Common providers of river traffic are affiliate networks and social-media-engaged marketing agencies. Incentives commonly take the form of virtual currency tied to online gaming and “content” provided on micro blog sites seeking specific audiences.

A potential survey respondent basically clicks on an ad, promotion or “offer”, is brought into a router, answers several pre-screening questions and then is routed to a survey based on their responses to the pre-screening questions. As researchers we don’t have any information about these people prior to hitting the survey. This is basically “raw traffic”. In other words, we don’t know who they are demographically or behaviorally.

River Sample is best used for the following types of studies:

• Mobile-friendly studies due to in the moment engagement
• Younger demographic targets due to recruitment techniques
• High volume studies with ample field time
• Studies with minimal quotas
• Lead generation type activities like community building, etc.

You should never use River Sample for the following types of studies:

• Small market geographically targeted studies
• Studies where screening statistics are needed for weighting purposes
• Studies with complex quota requirements
• Research where you may need to reinitiate contact the respondent
• Niche targets with quick turnaround schedules

What is Panel Sample?

A sample where respondents have gone through an industry-regulated double opt-in registration process to specifically join a research panel. Double opt-in means the respondent signed up for the panel, received an email to confirm the registration, and then click on a link back to the panel site to complete registration. With panel sample, the demographic profile of the respondents is consistently collected and maintained/updated in a master database. We know who these people are and we can target them for specific types of research studies. Panels also have a defined periodic panel cleansing/refresh process that infuses “fresh” respondents while also removing respondents who demonstrate a pattern of poor quality response behaviors.

The table below details the key differences between River and River sample.

Panel sampling, on the other hand, involves recruiting members from an affiliate site, where they are asked to register and confirm their interest in taking multiple surveys over an extended period of time. Panel participants are then invited by email to take those surveys based on qualifying demographic and psychographic characteristics. Information on panel participants is kept in a database, which can be vetted for multiple member qualities, including caliber of survey response, length of time on the panel, shopping habits, vacation preferences and innumerable other attributes. Members of the list are easily trackable and can be reached at any point.

Market researchers typically use river sampling as a complement to ongoing panel sampling. Panel sampling provides a dedicated and reliable source of information, but it can sometimes eventually provide stale or over-processed data. River sampling compliments many of those deficiencies by infusing new blood into the mix. While businesses are unable to pinpoint exact characteristics of a product’s user (or non-user), they can determine general attitudes shaping perceptions and opinions from river sample respondents.

What are Some Pros and Cons of River Sampling?

The Advantages 

1. Serves as a powerful replacement for survey panels by providing new respondents, those that have not been influenced or conditioned to take part in a survey.
2. Engages users in their natural digital environments.
3. Its survey callouts/ links exist in easily noticeable digital properties.
4. Creates a faster alternative to the focus group, which involves a group discussion where dominant participants can take charge and make it difficult for more demure participants.
5. Ensures complete anonymity of respondents.
6. Exists as a simple method of data gathering, since all researchers need to do is wait for the data to be aggregated.
7. An inexpensive source of sampling.
8. A flexible method that collects respondents in the moment, rather than being profiled prior to the survey and recruited manually.

The Disadvantages 

1. The devices used by potential and opted-in respondents are completely unknown.
2. There is no access to an advertisement’s ID.
3. Fraudsters can therefore take the same survey twice or more to increase their incentives or the chance to win a prize.
4. No degree of demographic, geographic or individual targeting is possible.
5. Banner ads generally have insufficient response rates.
6. Banners are pushed through ad networks, diminishing the user experience.
7. Ad-networks optimize their delivery by fighting against random sampling.
8. As such, users are picked due to a higher likelihood of responding, from unobserved variables (to the researcher) correlated with how they will respond. At any rate, none of the data is shared, so it is impossible to correct.
9. It is difficult to reach an acceptable level of representation, as respondents are not tracked.
10. Surveyors have no inkling of who will participate in the surveys due to the lack of tracking and profiling.
11. This method is prone to receive straight-lining from the respondents.

Examples of River Sampling

Random sampling is a statistical technique used in selecting people or items for research. There are many techniques that can be used. Each technique makes sure that each person or item considered for the research has an equal opportunity to be chosen as part of the group to be studied.

Methodology is vital to getting a truly random sample. Use an imperfect method and you risk getting biased or nonsensical results. The following are commonly used random sampling methods:

• Simple random sampling
• Stratified random sampling
• Cluster sampling
• Multistage sampling

Each of these random sampling techniques are explained more fully below, along with examples of each type.

Random sampling uses specific words for certain things. “Population” means every possible choice. Whether you’re choosing numbers, things or people, “population” means “all the possible things I could choose.” “Sample,” logically enough, means the thing or things you choose from the population to study.

Simple Random Sampling

As you’d guess by the name, this is the most common approach to random sampling. Simple random sampling means simply to put every member of the population into one big group, and then choosing who or what to include at random. As long as every possible choice is equally likely, you will produce a simple random sample.

Real world examples of simple random sampling include:

• At a birthday party, teams for a game are chosen by putting everyone’s name into a jar, and then choosing the names at random for each team.
• On an assembly line, each employee is assigned a random number using computer software. The same software is used periodically to choose a number of one of the employees to be observed to ensure they are employing best practices.
• A restaurant leaves a fishbowl on the counter for diners to drop their business cards. Once a month, a business card is pulled out to award one lucky diner with a free meal.
• At a bingo game, balls with every possible number are placed inside a mechanical cage. The caller rotates the cage, tumbling around the balls inside. Then, she selects one of the balls at random to be called, like B-12 or O-65.
• A pharmaceutical company wants to test the effectiveness of a new drug. Volunteers are assigned randomly to one of two groups. The first group will receive the new drug; the second group will receive a placebo.

Stratified Random Sampling

In stratified random sampling, the population is divided into groups based on a shared characteristic. Each group is called a stratum; the plural is strata. Then, one or more choices are made at random from each stratum.

• A survey about timekeeping might divide the population by time zone, then take 100 random samples per zone.
• A test addressing physical development over time could use the student body of a school as a population, stratify it by grade, and then take random samples from each grade.
• A study on tax reform might stratify a population according to income, then take random samples from each stratum.
• Opinion surveys on specific political issues commonly stratify according to respondents’ party affiliation (or lack thereof), then take samples from each.
• A market survey by a company interested in branching into a new market might choose a population of people using similar products, stratify it by brand, and sampling from each stratum.

Cluster Sampling

Cluster sampling is similar to stratified random sampling in that both begin by dividing the population into groups based on a particular characteristic. But, while a stratified survey takes one or more samples from each of the strata, a cluster sampling survey chooses clusters at random, then takes samples from them. Some clusters aren’t sampled; data is only collected from the chosen clusters. Cluster sampling is often used in market research.

• A study in the wake of a natural disaster might divide a population into clusters according to region, then choose a random cluster or clusters to begin establishing the disaster’s overall effect.
• A company interested in brand penetration may lack the resources to survey an entire city. Instead, they could divide the city into clusters based on area, choose clusters at random, and test the popularity of their brand. This is also how some mail campaigns are conducted.
• A test of the effectiveness of a new curriculum could begin by dividing an area by school district, then choosing a school or set number of schools at random and sampling students from each.
• Data relating to universal phenomena is often obtained by cluster sampling. Take the example of a statewide survey testing the average resting heart rate. The state could divide into clusters based on counties, then choose counties at random to test.
• A survey assessing customer satisfaction with a product might establish clusters based on place of purchase, then choose a number of those clusters at random.

Multistage Sampling

Multistage sampling is exactly what it says on the label: a sampling process that uses more than one kind of sampling.

• The same business referenced above, the one that used cluster sampling to study brand penetration, might break down the neighborhood clusters into strata according to income and take a simple random sample from each subgroup.
• Likewise, after establishing clusters based on area, the natural disaster survey might stratify each according to age before selecting samples in order to determine any disproportionate effect based on age.
• A test tracking physical development in students over time might begin with cluster sampling by district, selecting one specific school at random. They might then stratify according to age and gender before taking simple random samples.
• Local government testing a possible new policy might divide its jurisdiction into random clusters based on area, then stratify those clusters by party affiliation.
• A charity tracking the occurrence of a particular illness might create random clusters that cover all affected areas, then choose one and stratify it by percentage of affected people, testing only those strata above a certain percentage.

The importance of random sampling is hard to overstate. Scientific testing relies on it. Governments, businesses and charities depend on it. Anyone who systematically collects information about how the world works is likely to need a truly random sample at some point.
To continue improving your mathematical and scientific rigor, take a look at our examples of control groups.

Conclusion

It is essential to remember that river sampling, like other non-probability sampling methods, has limitations. The primary concern is the potential for selection bias, as the sample may not be representative of the broader population.

Researchers using river sampling should be cautious about generalizing their findings and should consider using other sampling methods or data sources to validate or complement their results.