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Study: Which Link Metric Correlates Closest to Organic Visibility?



Link Relevance vs. Content Relevance in Link Building

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

Throughout my career, most of my teams’ digital PR strategies for clients have consisted of closing link gaps, creating new ones, and earning as many high-tier links as possible. The goal was always the same: get our clients’ websites to the top of the search engine result pages (SERPs) and outranking their competitors.

To that end, we’ve earned press coverage for clients on every top-tier publisher you can think of, including “dream publishers” like CNN, the New York Times, Washington Post, and Business Insider. We’ve even had dozens of campaigns go viral, earning thousands of links and hundreds of thousands of social shares, all resulting from sending a single outreach email to a journalist.

“What’s wrong with that?” you might be asking. “It sounds like a successful strategy.”

While “going viral” might not carry the same weight it once did, I’ll be the first to admit it – there is hardly a more exciting feeling when working in digital PR. And we all know that link volume combined with high authority links will help you rise in the ranks of the SERPs. So, actually, there’s nothing intrinsically wrong with that strategy.

But when all you care about is lots of links and going viral, sometimes you miss the mark on something that matters just as much, if not more: relevance.

Since 2019, Google has acknowledged that it uses Natural Language Understanding (NLU) when assessing the relevancy and intent of users’ search queries. So why is no one measuring relevance when it comes to link profiles?

The team at Journey Further sought to do just that — and in our latest study, we demonstrate why link relevance is more important than ever, and how a relevance-led approach can outperform larger and more authoritative websites time and time again.

What does it mean to be relevant in digital PR?

Like most things that catch fire in our industry, “relevance” has become a bit of a buzzword in digital PR. But what does it mean, really?

When you think about relevance, it’s simple. Ask yourself:

  • Does this campaign relate to the client’s product or service?

  • Does it have target keywords in it?

  • Does it talk about the main topics we want to target?

  • Does it answer the search intent?

  • Does it make sense for the client to be considered an authority and/or a trusted source on this topic?

If you answered no to most of these, you might want to go back to the drawing board.

For some clients, it can be difficult to come up with an idea that’s both relevant and newsworthy. The most relevant idea in the world will not earn links if it’s boring, and that’s the challenge we all face every day when creating digital PR campaigns for our clients.

Though it’s difficult, it’s in your clients’ best interest for you to think outside the box in ideation and come up with both relevant and link-worthy digital PR ideas — you’ll understand why after seeing the data from our latest study.

How do you measure content relevance?

Beyond manually determining relevance with those questions above, what if there was a data-driven way?

Steve Walker, the technology director at Journey Further, found this kind of analysis to be resource-intensive and prone to error. Humans aren’t as good at these tasks as machines are, so he created Salient, a free-to-use tool that measures the relevance of your content.

Steve thought, “If Google uses machine learning to measure the relevance of content, why aren’t we?”

1668152104 233 Study Which Link Metric Correlates Closest to Organic Visibility

Using this proprietary technology powered by Natural Language Understanding (NLU) technology is how we can measure the relevance of content, analyzing an entire website’s link profile rather than individual articles. Incorporating the IBM Watson Machine Learning API allows us to extract sentiment, recurring keywords and entities, and a relevancy and frequency score for each topic.

Off the back of this insight, we can understand what gaps exist in the relevancy of the link profile. This information then guides our PR and content strategies to drive organic visibility.

Study: Which link metric correlates closest to organic visibility?

So, how important is relevance compared with much-heralded metrics like Domain Authority (DA) and link volume?

In a data-driven attempt to learn which metric is statistically the best driver of organic visibility, our team at Journey Further analyzed the organic rankings of 6,000 commercially valuable keywords, calculating share of voice for a range of competing websites. From there, we measured the correlation of these scores against three link metrics:

  1. Number of unique linking domains

  2. Domain Authority

  3. Topical link profile relevance

In this study, we focused on the home retail sector, with the following focus areas:

1668152104 546 Study Which Link Metric Correlates Closest to Organic Visibility

Across all 15 sectors, topical link relevance was the only metric that had a positive correlation to organic visibility

The findings of our study show that topical link relevance has the strongest correlation in 10 out of 15 sectors.

Domain Authority had a stronger correlation in five sectors: outdoor/patio, office furniture, bedding, desks, and pillows.

Unique linking domains never had the strongest correlation to organic visibility and, in fact, showed a negative correlation in 6 out of 15 sectors.

However, across all 15 sectors, topical link relevance was the only metric that positively correlated to organic visibility every time.

1668152104 545 Study Which Link Metric Correlates Closest to Organic Visibility

That’s the TL;DR of it, but read on for a deeper look at some individual topic areas and how we came to these figures. View the full study here.

Definitions and Limitations

To better understand the data, let’s detail some definitions first:

Correlation coefficient: A linear measure of the correlation between two variables. A value of 0 indicates no association between the two variables. A value greater than 0 indicates a positive association, and a value less than 0 indicates a negative association.

Organic share of voice (SOV): Organic SOV is a metric that represents how much organic traffic a site receives vs. the other sites in that sector for a set of high-traffic keywords. It considers keyword volumes, click-through rates, ranking position, and SERP features. The final SOV is expressed as a percentage of that keyword set’s total available search volume. So if your SOV is 25%, you’re winning 25% of the clicks for that set.

Topical link relevance: A score that shows the relevance of a keyword or topic to the entire document text or range of pages analyzed – in this case, the text on each page that links back to the sites we analyzed. The higher the number, the more relevant a topic. A score of 0 means that the topic was not relevant at all.

Unique linking domains: The total number of unique domains that link back to each site.

Domain Authority (DA): A ranking score developed by Moz that predicts how likely a website will rank on SERPs. A DA score ranges from 1 to 100, with higher scores corresponding to greater visibility.


This study relies on correlation and thus has limitations. Please note that correlation ≠ causation, and because Google historically does not comment on studies, or reveal precisely how the ranking algorithm works, we’ll likely never find causation. However, based on patents mentioning the use of topical relevance in combination with the findings of the correlation studies, we can be confident in the validity of the data.

Relevance vs. Link Volume

As an example, let’s look at the bathroom sector. When looking at hundreds of keywords related to bathrooms like bathroom mirrors and bathroom ideas, we found that this sector has over 1.8 million searches per month, with leading home brands competing for share of voice.

After analyzing the backlink profile and relevance score, we then calculate a correlation with that brand’s share of voice to determine if there is any connection between this metric and organic visibility.

  • Anything below zero has a negative correlation, so there is no connection.

  • Anything over zero has a positive correlation.

  • The higher the correlation, the stronger the relationship between the metrics and organic visibility.

1668152105 398 Study Which Link Metric Correlates Closest to Organic Visibility

With a correlation coefficient of .74, it’s clear that the metric that is most closely related to organic visibility for the bathroom sector is topical link relevance.

Unique linking domains, in this case, has a negative correlation. For example, IKEA has a backlink profile of more than 406K ULDs, but doesn’t have the biggest market share, which shows that there is no correlation to the link volume and market share.

Relevance vs. Domain Authority

When looking at hundreds of keywords related to dressers, we found that this sector has over 1.6 million searches per month.

Again, we did the same thing here and compared each brand’s backlink profile and relevance score to that brand’s share of voice.

1668152105 319 Study Which Link Metric Correlates Closest to Organic Visibility

With a correlation coefficient of .61, we see that topical link relevance is the metric most closely related to organic visibility for the dressers sector.

However, this example demonstrates that all three metrics (relevance, Domain Authority, and link volume) are critical to organic visibility. All three have a very high correlation, which suggests that not only are these metrics correlated, but perhaps they are integral for boosting organic visibility in this sector.

View the full study here. (And feel free to reach out to me directly if you want us to run a free relevance report for you).

In SEO, it’s not enough to be popular, you also need to be relevant

Historically, the SEO industry has relied on metrics like Domain Authority and link volume. These two metrics are important, but only provide a portion of the puzzle. Alone, they don’t answer Google’s primary question: which website is the most relevant for a query?

1668152105 29 Study Which Link Metric Correlates Closest to Organic Visibility

We’ve all seen campaigns out in the wild that make us scratch our heads, thinking, “what does this topic have to do with that client?” Think: why is a CBD company pushing out a study on anything but CBD? Why is a company that sells bathroom fixtures creating content about dogs?

When you fail to see the connection between the story and the client, you know they’re only thinking of one thing: links.

But, as my colleague Beth Nunnington likes to say, “in SEO, it’s not enough to be popular, you also need to be relevant.”

Don’t forget, most clients don’t want links for links’ sake. They want what links bring: increased traffic, better rankings for priority keywords, increased revenue, brand awareness, etc.

And links will only serve those goals when they’re relevant.

Don’t get me wrong – I still LOVE a CNN placement (and so do clients), but now, I’d also like it to be relevant.

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OpenAI’s Drama Should Teach Marketers These 2 Lessons



OpenAI’s Drama Should Teach Marketers These 2 Lessons

A week or so ago, the extraordinary drama happening at OpenAI filled news feeds.

No need to get into all the saga’s details, as every publication seems to have covered it. We’re just waiting for someone to put together a video montage scored to the Game of Thrones music.

But as Sam Altman takes back the reigns of the company he helped to found, the existing board begins to disintegrate before your very eyes, and everyone agrees something spooked everybody, a question arises: Should you care?

Does OpenAI’s drama have any demonstrable implications for marketers integrating generative AI into their marketing strategies?

Watch CMI’s chief strategy advisor Robert Rose explain (and give a shoutout to Sutton’s pants rage on The Real Housewives of Beverly Hills), or keep reading his thoughts:

For those who spent last week figuring out what to put on your holiday table and missed every AI headline, here’s a brief version of what happened. OpenAI – the huge startup and creator of ChatGPT – went through dramatic events. Its board fired the mercurial CEO Sam Altman. Then, the 38-year-old entrepreneur accepted a job at Microsoft but returned to OpenAI a day later.

We won’t give a hot take on what it means for the startup world, board governance, or the tension between AI safety and Silicon Valley capitalism. Rather, we see some interesting things for marketers to put into perspective about how AI should fit into your overall content and marketing plans in the new year.

Robert highlights two takeaways from the OpenAI debacle – a drama that has yet to reach its final chapter: 1. The right structure and governance matters, and 2. Big platforms don’t become antifragile just because they’re big.

Let’s have Robert explain.

The right structure and governance matters

OpenAI’s structure may be key to the drama. OpenAI has a bizarre corporate governance framework. The board of directors controls a nonprofit called OpenAI. That nonprofit created a capped for-profit subsidiary – OpenAI GP LLC. The majority owner of that for-profit is OpenAI Global LLC, another for-profit company. The nonprofit works for the benefit of the world with a for-profit arm.

That seems like an earnest approach, given AI tech’s big and disruptive power. But it provides so many weird governance issues, including that the nonprofit board, which controls everything, has no duty to maximize profit. What could go wrong?

That’s why marketers should know more about the organizations behind the generative AI tools they use or are considering.

First, know your providers of generative AI software and services are all exploring the topics of governance and safety. Microsoft, Google, Anthropic, and others won’t have their internal debates erupt in public fireworks. Still, governance and management of safety over profits remains a big topic for them. You should be aware of how they approach those topics as you license solutions from them.

Second, recognize the productive use of generative AI is a content strategy and governance challenge, not a technology challenge. If you don’t solve the governance and cross-functional uses of the generative AI platforms you buy, you will run into big problems with its cross-functional, cross-siloed use. 

Big platforms do not become antifragile just because they’re big

Nicholas Taleb wrote a wonderful book, Antifragile: Things That Gain From Disorder. It explores how an antifragile structure doesn’t just withstand a shock; it actually improves because of a disruption or shock. It doesn’t just survive a big disruptive event; it gets stronger because of it.

It’s hard to imagine a company the size and scale of OpenAI could self-correct or even disappear tomorrow. But it can and does happen. And unfortunately, too many businesses build their strategies on that rented land.

In OpenAI’s recent case, the for-profit software won the day. But make no bones about that victory; the event wasn’t good for the company. If it bounces back, it won’t be stronger because of the debacle.

With that win on the for-profit side, hundreds, if not thousands, of generative AI startups breathed an audible sigh of relief. But a few moments later, they screamed “pivot” (in their best imitation of Ross from Friends instructing Chandler and Rachel to move a couch.)

They now realize the fragility of their software because it relies on OpenAI’s existence or willingness to provide the software. Imagine what could have happened if the OpenAI board had won their fight and, in the name of safety, simply killed any paid access to the API or the ability to build business models on top of it.

The last two weeks have done nothing to clear the already muddy waters encountered by companies and their plans to integrate generative AI solutions. Going forward, though, think about the issues when acquiring new generative AI software. Ask about how the vendor’s infrastructure is housed and identify the risks involved. And, if OpenAI expands its enterprise capabilities, consider the implications. What extra features will the off-the-shelf solutions provide? Do you need them? Will OpenAI become the Microsoft Office of your AI infrastructure?

Why you should care

With the voluminous media coverage of Open AI’s drama, you likely will see pushback on generative AI. In my social feeds, many marketers say they’re tired of the corporate soap opera that is irrelevant to their work.

They are half right. What Sam said and how Ilya responded, heart emojis, and how much the Twitch guy got for three days of work are fodder for the Netflix series sure to emerge. (Robert’s money is on Michael Cera starring.)

They’re wrong about its relevance to marketing. They must be experiencing attentional bias – paying more attention to some elements of the big event and ignoring others. OpenAI’s struggle is entertaining, no doubt. You’re glued to the drama. But understanding what happened with the events directly relates to your ability to manage similar ones successfully. That’s the part you need to get right.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.


Cover image by Joseph Kalinowski/Content Marketing Institute

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The Complete Guide to Becoming an Authentic Thought Leader



The Complete Guide to Becoming an Authentic Thought Leader

Introduce your processes: If you’ve streamlined a particular process, share it. It could be the solution someone else is looking for.

Jump on trends and news: If there’s a hot topic or emerging trend, offer your unique perspective.

Share industry insights: Attended a webinar or podcast that offered valuable insights. Summarize the key takeaways and how they can be applied.

Share your successes: Write about strategies that have worked exceptionally well for you. Your audience will appreciate the proven advice. For example, I shared the process I used to help a former client rank for a keyword with over 2.2 million monthly searches.

Question outdated strategies: If you see a strategy that’s losing steam, suggest alternatives based on your experience and data.

5. Establish communication channels (How)

Once you know who your audience is and what they want to hear, the next step is figuring out how to reach them. Here’s how:

Choose the right platforms: You don’t need to have a presence on every social media platform. Pick two platforms where your audience hangs out and create content for that platform. For example, I’m active on LinkedIn and X because my target audience (SEOs, B2B SaaS, and marketers) is active on these platforms.

Repurpose content: Don’t limit yourself to just one type of content. Consider repurposing your content on Quora, Reddit, or even in webinars and podcasts. This increases your reach and reinforces your message.

Follow Your audience: Go where your audience goes. If they’re active on X, that’s where you should be posting. If they frequent industry webinars, consider becoming a guest on these webinars.

Daily vs. In-depth content: Balance is key. Use social media for daily tips and insights, and reserve your blog for more comprehensive guides and articles.

Network with influencers: Your audience is likely following other experts in the field. Engaging with these influencers puts your content in front of a like-minded audience. I try to spend 30 minutes to an hour daily engaging with content on X and LinkedIn. This is the best way to build a relationship so you’re not a complete stranger when you DM privately.

6. Think of thought leadership as part of your content marketing efforts

As with other content efforts, thought leadership doesn’t exist in a vacuum. It thrives when woven into a cohesive content marketing strategy. By aligning individual authority with your brand, you amplify the credibility of both.

Think of it as top-of-the-funnel content to:

  • Build awareness about your brand

  • Highlight the problems you solve

  • Demonstrate expertise by platforming experts within the company who deliver solutions

Consider the user journey. An individual enters at the top through a social media post, podcast, or blog post. Intrigued, they want to learn more about you and either search your name on Google or social media. If they like what they see, they might visit your website, and if the information fits their needs, they move from passive readers to active prospects in your sales pipeline.

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How to Increase Survey Completion Rate With 5 Top Tips



How to Increase Survey Completion Rate With 5 Top Tips

Collecting high-quality data is crucial to making strategic observations about your customers. Researchers have to consider the best ways to design their surveys and then how to increase survey completion, because it makes the data more reliable.

→ Free Download: 5 Customer Survey Templates [Access Now]

I’m going to explain how survey completion plays into the reliability of data. Then, we’ll get into how to calculate your survey completion rate versus the number of questions you ask. Finally, I’ll offer some tips to help you increase survey completion rates.

My goal is to make your data-driven decisions more accurate and effective. And just for fun, I’ll use cats in the examples because mine won’t stop walking across my keyboard.

Why Measure Survey Completion

Let’s set the scene: We’re inside a laboratory with a group of cat researchers. They’re wearing little white coats and goggles — and they desperately want to know what other cats think of various fish.

They’ve written up a 10-question survey and invited 100 cats from all socioeconomic rungs — rough and hungry alley cats all the way up to the ones that thrice daily enjoy their Fancy Feast from a crystal dish.

Now, survey completion rates are measured with two metrics: response rate and completion rate. Combining those metrics determines what percentage, out of all 100 cats, finished the entire survey. If all 100 give their full report on how delicious fish is, you’d achieve 100% survey completion and know that your information is as accurate as possible.

But the truth is, nobody achieves 100% survey completion, not even golden retrievers.

With this in mind, here’s how it plays out:

  • Let’s say 10 cats never show up for the survey because they were sleeping.
  • Of the 90 cats that started the survey, only 25 got through a few questions. Then, they wandered off to knock over drinks.
  • Thus, 90 cats gave some level of response, and 65 completed the survey (90 – 25 = 65).
  • Unfortunately, those 25 cats who only partially completed the survey had important opinions — they like salmon way more than any other fish.

The cat researchers achieved 72% survey completion (65 divided by 90), but their survey will not reflect the 25% of cats — a full quarter! — that vastly prefer salmon. (The other 65 cats had no statistically significant preference, by the way. They just wanted to eat whatever fish they saw.)

Now, the Kitty Committee reviews the research and decides, well, if they like any old fish they see, then offer the least expensive ones so they get the highest profit margin.

CatCorp, their competitors, ran the same survey; however, they offered all 100 participants their own glass of water to knock over — with a fish inside, even!

Only 10 of their 100 cats started, but did not finish the survey. And the same 10 lazy cats from the other survey didn’t show up to this one, either.

So, there were 90 respondents and 80 completed surveys. CatCorp achieved an 88% completion rate (80 divided by 90), which recorded that most cats don’t care, but some really want salmon. CatCorp made salmon available and enjoyed higher profits than the Kitty Committee.

So you see, the higher your survey completion rates, the more reliable your data is. From there, you can make solid, data-driven decisions that are more accurate and effective. That’s the goal.

We measure the completion rates to be able to say, “Here’s how sure we can feel that this information is accurate.”

And if there’s a Maine Coon tycoon looking to invest, will they be more likely to do business with a cat food company whose decision-making metrics are 72% accurate or 88%? I suppose it could depend on who’s serving salmon.

While math was not my strongest subject in school, I had the great opportunity to take several college-level research and statistics classes, and the software we used did the math for us. That’s why I used 100 cats — to keep the math easy so we could focus on the importance of building reliable data.

Now, we’re going to talk equations and use more realistic numbers. Here’s the formula:

Completion rate equals the # of completed surveys divided by the # of survey respondents.

So, we need to take the number of completed surveys and divide that by the number of people who responded to at least one of your survey questions. Even just one question answered qualifies them as a respondent (versus nonrespondent, i.e., the 10 lazy cats who never show up).

Now, you’re running an email survey for, let’s say, Patton Avenue Pet Company. We’ll guess that the email list has 5,000 unique addresses to contact. You send out your survey to all of them.

Your analytics data reports that 3,000 people responded to one or more of your survey questions. Then, 1,200 of those respondents actually completed the entire survey.

3,000/5000 = 0.6 = 60% — that’s your pool of survey respondents who answered at least one question. That sounds pretty good! But some of them didn’t finish the survey. You need to know the percentage of people who completed the entire survey. So here we go:

Completion rate equals the # of completed surveys divided by the # of survey respondents.

Completion rate = (1,200/3,000) = 0.40 = 40%

Voila, 40% of your respondents did the entire survey.

Response Rate vs. Completion Rate

Okay, so we know why the completion rate matters and how we find the right number. But did you also hear the term response rate? They are completely different figures based on separate equations, and I’ll show them side by side to highlight the differences.

  • Completion Rate = # of Completed Surveys divided by # of Respondents
  • Response Rate = # of Respondents divided by Total # of surveys sent out

Here are examples using the same numbers from above:

Completion Rate = (1200/3,000) = 0.40 = 40%

Response Rate = (3,000/5000) = 0.60 = 60%

So, they are different figures that describe different things:

  • Completion rate: The percentage of your respondents that completed the entire survey. As a result, it indicates how sure we are that the information we have is accurate.
  • Response rate: The percentage of people who responded in any way to our survey questions.

The follow-up question is: How can we make this number as high as possible in order to be closer to a truer and more complete data set from the population we surveyed?

There’s more to learn about response rates and how to bump them up as high as you can, but we’re going to keep trucking with completion rates!

What’s a good survey completion rate?

That is a heavily loaded question. People in our industry have to say, “It depends,” far more than anybody wants to hear it, but it depends. Sorry about that.

There are lots of factors at play, such as what kind of survey you’re doing, what industry you’re doing it in, if it’s an internal or external survey, the population or sample size, the confidence level you’d like to hit, the margin of error you’re willing to accept, etc.

But you can’t really get a high completion rate unless you increase response rates first.

So instead of focusing on what’s a good completion rate, I think it’s more important to understand what makes a good response rate. Aim high enough, and survey completions should follow.

I checked in with the Qualtrics community and found this discussion about survey response rates:

“Just wondering what are the average response rates we see for online B2B CX surveys? […]

Current response rates: 6%–8%… We are looking at boosting the response rates but would first like to understand what is the average.”

The best answer came from a government service provider that works with businesses. The poster notes that their service is free to use, so they get very high response rates.

“I would say around 30–40% response rates to transactional surveys,” they write. “Our annual pulse survey usually sits closer to 12%. I think the type of survey and how long it has been since you rendered services is a huge factor.”

Since this conversation, “Delighted” (the Qualtrics blog) reported some fresher data:

survey completion rate vs number of questions new data, qualtrics data

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The takeaway here is that response rates vary widely depending on the channel you use to reach respondents. On the upper end, the Qualtrics blog reports that customers had 85% response rates for employee email NPS surveys and 33% for email NPS surveys.

A good response rate, the blog writes, “ranges between 5% and 30%. An excellent response rate is 50% or higher.”

This echoes reports from Customer Thermometer, which marks a response rate of 50% or higher as excellent. Response rates between 5%-30% are much more typical, the report notes. High response rates are driven by a strong motivation to complete the survey or a personal relationship between the brand and the customer.

If your business does little person-to-person contact, you’re out of luck. Customer Thermometer says you should expect responses on the lower end of the scale. The same goes for surveys distributed from unknown senders, which typically yield the lowest level of responses.

According to SurveyMonkey, surveys where the sender has no prior relationship have response rates of 20% to 30% on the high end.

Whatever numbers you do get, keep making those efforts to bring response rates up. That way, you have a better chance of increasing your survey completion rate. How, you ask?

Tips to Increase Survey Completion

If you want to boost survey completions among your customers, try the following tips.

1. Keep your survey brief.

We shouldn’t cram lots of questions into one survey, even if it’s tempting. Sure, it’d be nice to have more data points, but random people will probably not hunker down for 100 questions when we catch them during their half-hour lunch break.

Keep it short. Pare it down in any way you can.

Survey completion rate versus number of questions is a correlative relationship — the more questions you ask, the fewer people will answer them all. If you have the budget to pay the respondents, it’s a different story — to a degree.

“If you’re paying for survey responses, you’re more likely to get completions of a decently-sized survey. You’ll just want to avoid survey lengths that might tire, confuse, or frustrate the user. You’ll want to aim for quality over quantity,” says Pamela Bump, Head of Content Growth at HubSpot.

2. Give your customers an incentive.

For instance, if they’re cats, you could give them a glass of water with a fish inside.

Offer incentives that make sense for your target audience. If they feel like they are being rewarded for giving their time, they will have more motivation to complete the survey.

This can even accomplish two things at once — if you offer promo codes, discounts on products, or free shipping, it encourages them to shop with you again.

3. Keep it smooth and easy.

Keep your survey easy to read. Simplifying your questions has at least two benefits: People will understand the question better and give you the information you need, and people won’t get confused or frustrated and just leave the survey.

4. Know your customers and how to meet them where they are.

Here’s an anecdote about understanding your customers and learning how best to meet them where they are.

Early on in her role, Pamela Bump, HubSpot’s Head of Content Growth, conducted a survey of HubSpot Blog readers to learn more about their expertise levels, interests, challenges, and opportunities. Once published, she shared the survey with the blog’s email subscribers and a top reader list she had developed, aiming to receive 150+ responses.

“When the 20-question survey was getting a low response rate, I realized that blog readers were on the blog to read — not to give feedback. I removed questions that wouldn’t serve actionable insights. When I reshared a shorter, 10-question survey, it passed 200 responses in one week,” Bump shares.

Tip 5. Gamify your survey.

Make it fun! Brands have started turning surveys into eye candy with entertaining interfaces so they’re enjoyable to interact with.

Your respondents could unlock micro incentives as they answer more questions. You can word your questions in a fun and exciting way so it feels more like a BuzzFeed quiz. Someone saw the opportunity to make surveys into entertainment, and your imagination — well, and your budget — is the limit!

Your Turn to Boost Survey Completion Rates

Now, it’s time to start surveying. Remember to keep your user at the heart of the experience. Value your respondents’ time, and they’re more likely to give you compelling information. Creating short, fun-to-take surveys can also boost your completion rates.

Editor’s note: This post was originally published in December 2010 and has been updated for comprehensiveness.

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