Mimi An

table of contents (6  minute  read)

1. video around the globe
2. where consumers go to see video
3. popular content channels: google, facebook, and amazon factor
4. mobile first regions are a great testing ground for messaging
5. methodology 

our 2017 consumer trends survey was fielded in 3 major regions and explored the content preferences of consumers. our findings outlined that:

• facebook is now a major content channel.
• ready or not, video is here.
• when it comes to content, age matters. a lot.
• preference for video extends to brands.
• do invest in a mix of channels and content - don’t ditch any specific channels today.
• take demographics into consideration when staffing content teams.

this follow up report breaks down responses in the us, germany, and colombia and mexico, which we’ll be referring to as latin america in the report.

video around the globe

our previous report established a very strong preference for video, especially from a brand or business.

want this chart? click to download. 

geographically, latin american consumers were more enthusiastic about video and social compared to those in the us and uk. they’re also less likely to want email content compared to their peers.

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overall, branded video content is the most memorable type of branded content, but there are some striking differences in preference across regions. video is hugely memorable for latin american consumers, whereas german consumers indicate photo-based content is more memorable.

want this chart? click to download. 

when it comes to general advertising, most in the us and germany strongly prefer image based ads. strikingly, video is so popular in latin america that video based ads rank highest against image and text-based ads. this is a big difference compared to the us and germany, where video ads are reviled as a particularly annoying type of advertising. perhaps if online video ads follow the preferred formula of being entertaining, funny, or informative, the medium will win over more consumer viewers (just make sure they’re not autoplaying).

want this chart? click to download. 

where consumers go to see videos

unsurprisingly, youtube is the most popular channel for video overall. facebook makes a strong showing, especially amongst latin american and us-based respondents. facebook’s pivot to a multimedia company has made serious headway against youtube. however, facebook's recent announcement that puts the focus on content shared by friends and family over brands will make distribution and reach much harder for marketers. since brand pages will be de-emphasized, noteworthy branded videos may be one of the few types of branded content that has the potential to be shared en masse by users. but the video has to be worth sharing and commenting on.

want this chart? click to download. 

what types of video content are the most popular? people around world want entertaining, funny, and informative content. the education aspect is surprisingly popular -- 61% of consumers surveyed want to learn something from the videos they see on social media.

want this chart? click to download. 

popular content channels: google, facebook, and amazon factor

where do people catch up on stories online? google and facebook are now head to head for content discovery. as noted in the first report in this series, content discovery on facebook is very different from discovery on google. when one uses google for content, one has to have an idea of the topic or item they’re searching for. facebook’s feed allows for passive discovery of content, products, and brands. as a result, optimizing content for facebook is very different from optimizing content for search engines.

want this chart? click to download. 

mobile first regions are a great testing ground for messaging

finally, mobile devices dictate the type of content people seek out on a daily basis. as more use phones as their primary internet device, the preference for video, social content, and messaging based interactions will continue to grow. the majority of latin american respondents are mobile first, and their preferences can be leveraged by marketers looking to experiment.

want this chart? click to download. 

 

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research methodology

hubspot research ran an online survey leveraging a general population panel of adult online consumers via survey sampling international. 3,010 respondents from the us, germany, colombia, and mexico make up the sample. the survey was available in english, german, and spanish and fielded in june 2017. 

 this report contains links for hubspot content, products, and services.

originally published feb 7, 2018 8:00:00 am, updated december 11 2019

a hubspot digital consumer trends report

tl;dr: our recent survey of over 3,000 consumers explored the type of content and channels that best attracts people’s time and attention. the clear winner is video, with interactive articles and social content emerging as close contenders.

this trend toward video has been in the making for some time now. what’s different is that millennials, an age group which roughly spans 18 to 34, aren’t just buying sneakers and gadgets anymore. increasingly, millennials comprise a cohort of people purchasing homes, baby clothing, and b2b software. and their strong preference for video, social, and mobile-first content has implications for marketers working across an expanding array of industries. (click here to see our follow up report with the data broken out by geography if you're interested in regional variances.)

download now: the state of media & content
planning in 2022 [free data report]

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mobile phones are an integral part of modern life, with many admitting they use their phones before they sleep, after they wake up, and even in the bathroom throughout the day. 

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table of contents (9  minute read)

1. facebook is now a major content channel.
2. ready or not, video is here.
3. milwhen it comes to content, age matters. a lot.
4. preference for video extends to brands.
5. do invest in a mix of channels and content - don’t ditch any specific channels today.
6. take demographics into consideration when staffing content teams.
7. methodology 

facebook is now a major content channel.

in july, google announced it’s overhauling its mobile homepage to feature content based on past searches. why the change?

google is adapting to the way people discover products and trends. many still rely on google to find content, but facebook is now nearly as influential as google. as more consumers passively discover content through their facebook feed, google is attempting to compete by encouraging mobile google users to browse suggested content through their feeds rather than actively search. 

want this chart? click to download.

google is shifting their mobile experience to cater to younger consumers, who are mobile first internet users. millennials now favor facebook almost as highly as google as a source for content. in contrast, gen x and boomer consumers have a stronger preference for going directly to a news site or receiving email content. 

want this chart? click to download.

what does this mean for marketers? seo will continue expanding to new channels beyond search engines. seo marketers will now need to contend with search algorithms on amazon or youtube in addition to google or bing. with the ubiquity of facebook, marketers will have to suffer the whims of facebook's algorithms in order to get discovered.

additionally, the type of 'enticing' content that needs to be developed for channels such as facebook is very different from that for google. it needs to be worth viewing to capture the attention of someone scrolling down a news feed. as a result, facebook’s goal to become an all video platform means their algorithm will favor and boost visual formatting in the future.

ready or not, video is here.

this year, many industry influencers have either bemoaned or advocated for a ‘pivot to video’. publishers such as mic, mtv, and even newsweek are increasingly shifting their resources to produce more video content while downsizing teams focused on written content. these changes, and resultant layoffs, sting.

as with any major change, many within the content industry are debating the merits of focusing on video. some say it’s a trendy blip, while others argue it’s an inevitable change caused by new consumer preferences. our data strongly reinforces the latter argument. video content is very much in demand, for a couple of reasons.

first, our respondents tell us they’re more likely to pay attention to video content, followed by news articles and in-depth multimedia articles. as long as the content is timely and engaging, people will focus and pay attention to both video and text-based content. there is a clear indication that people tend to skim most written and audio content. if you want someone’s full attention, video is a great bet. 

want this chart? click to download.

second, not only do consumers pay attention to video content the most, they want to see more video content in the future (see chart below). consumer preference for video is real, whether you’re on board or not.

want this chart? click to download

but does that mean all content teams need to abandon written content? not exactly; there is still an audience that wants more written content in the future.   

when it comes to content, age matters. a lot. 

different content preferences clearly reveal themselves when we cut our data by age (see chart below). millennial respondents show the strongest preference for video and social content. in contrast, gen x and boomers prefer more news articles, research reports, and email content, meaning most traditional content teams still have interested readers. want this chart? click to download.

the key is to balance content teams with the right ratio of traditional written content creators to video-based and social content creators. that ratio depends on the target audience of a brand or media site. those who cater to millennials will need to increase video investment, while those who target boomers should maintain their standard email and ebook-based content and experiment with video to gauge their audience’s demand. just keep in mind, millennials are aging, and just because your audience didn’t like video two years ago, doesn’t mean they won’t be interested in it today.

preference for video extends to brands.

why is video so popular with consumers? video content stands out the most, especially for younger consumers. perhaps it’s because few brands do video content well today, and consumers are more easily impressed. right now when it comes to video, most brands are working blind because quality is so subjective and difficult to measure. regardless, video content is consistently favored by consumers. the demand is there. 

admittedly, the barrier to entry for video is high: it's more expensive, it often means you're creating less content. but but across every age group, it's the most memorable content. investing in video content today will feel like what blogging was 10 years ago. video offers a blue ocean in terms of attention and content options. there's plenty of opportunity for those who choose invest and do it right. 

want this chart? click to download.

additionally, branded video is nearly 3x more popular than branded blogs or ebooks. though email is still a strong brand play today, different generational content preferences will eventually cause a shift away from email to video and social based content.  

want this chart? click to download.

when we cut the data above by age, we found consumers across age groups consistently wanted more branded video content. but there were stark differences for other types of content. just 22% of young consumers want emails from brands, compared to 68% of boomers. inversely, 60% half of younger respondents want to see social images from brands, compared to just 20% of boomers.

the decline of email may be due to the fact that for mobile-first millennials, when presented with a constant barrage of phone notifications (texts from friends and family, social media notifications, news notifications, and so on), an email notification is much easier to ignore. as content continues to get delivered in more visual and engaging ways, it’s understandable that static emails can’t capture millennials’ attention.

the ‘death of email’ has long been predicted in the marketing industry, but our demographic data shows that it may actually happen in the near future. regardless of a brand’s target audience, marketers should prepare for the eventual decline of email as a top source of leads or new business. 

want this chart? click to download.

if we look to the future beyond video, as gen z and millennials increase their earning power, we expect brands to also focus on engagement on social social media. not only do younger consumers prefer to see more social media content, they use social media as a channel for product research as well.

younger consumers consistently shows the greatest preference for social and treats it as a valid research channel. the age of your customer should play a major role in how you shape your content strategy. as a result, marketers must provide informative content on social media to help consumers better understand their offerings. that means extending from useful written content to video and image-based content.

want this chart? click to download.

do invest in a mix of channels and content. don’t ditch any specific channels today.

consumers’ changing preferences does not mean that brands should abandon email, blogs and other written content, or their website today. these content assets are still valuable, especially since there’s a broad range of content preferences amongst consumers in the current state.

in fact, when we ask about what people do to proactively learn more about a brand, the top channel is still the brand’s website, across all age ranges. while offsite platforms such as social media are critical to gaining consumer awareness of a brand, when someone is ready to learn more, the company website is still an important source of information. 

want this chart? click to download.

however, while the website will continue to be critical in the future, echoes of our earlier data show up when we review the data by age. once again, we see higher propensity of younger consumers to seek videos and like a brand on facebook or instagram. older consumers are once again more likely to want email content. 

want this chart? click to download.

take demographics into consideration when staffing content teams.

as much as marketers might wish they could make their buyer preferences hold still why they catch up, this isn't the case. even as a marketing team shifts to accommodate millennial preference for video content, know that in another 5 to 10 years, they're going to see a new generation of buyers that looks to social media, or a channel that currently doesn’t exist, as a useful channel for discovery.

in the near term, we have to accept that the hype around video is real. people want more video content. throughout this report, we’ve seen an especially strong and consistent preference for video and social-based content by millennials. brands and media companies will need to staff video content creators to cater to their preferences and adjust their goals accordingly, without completely abandoning tried and true tactics that have generated success in the past. 

jami oetting, hubspot's content strategy manager, puts hubspot's approach to video this way: video is "about different kpis and ways of measuring [success]. it's also important to think about how video is used throughout the funnel. video isn't just a tofu (top of the funnel) tactic. it can be effective for sales, customer onboarding, driving loyalty, etc. so learning how to measure video's influence and how to create effective video is key. it's also a challenge from a skill perspective for teams." 

recent news has highlighted difficulties media organizations have experienced as they pivot to video. difficulties are to be expected when trying new channels and content types. but as more content teams change their focus, experimentation and tolerance for lower kpi numbers are necessary. long held metrics will need to change -- after all, why should businesses measure video views against pageviews? those who experiment early, learn fast, and recover from ‘failures’ will be best positioned to tap into a growing number of video watchers.

research methodology

hubspot research ran an online survey leveraging a general population panel of adult online consumers via survey sampling international. 3,010 respondents from the us, germany, colombia, and mexico make up the sample. the survey was available in english, german, and spanish and fielded in june 2017. 

 

originally published nov 6, 2017 12:15:00 pm, updated may 06 2022

table of contents (8 minute read)

1. introduction
2. an ai tool primer
3. the ai terms you need to know
4. making sense of ai technologies 
5. conclusion 

the concept of artificial intelligence (ai) has been tossed around in books, movies, and media for decades. from hal 9000 wreaking havoc (2001: a space odyssey) to marvin the paranoid android sadly going about its existence (the hitchhiker’s guide to the galaxy), we’ve been trained to expect ai-powered devices to have fully developed personalities who also can either fly or fly spaceships. so some people may be disappointed to hear from tech companies and the media about how we’re entering the age of ai -- despite not seeing a single adorable robot zooming around. granted, we are at the very beginning of the ai revolution, but this technology has the potential to change the way we live and work. even the obama administration drafted a report that outlines the future impact of ai developments.

but if ai is here, where are all the big floofy robots?

source: disney

as we sit on the cusp of ai innovation, we thought it was necessary to break down ai in a practical way. what does the current product landscape look like, and what technologies are driving these tools? it can be a confusing mess to an interested observer without a deep technical background (i.e., most of us).

in general terms, artificial intelligence is technology that can do things humans can uniquely do, whether it’s talk, see, learn, socialize, and reason. that’s a very broad set of skills, and when most of us think of ai, we envision a human-like android that can do all of those things.

let’s set expectations: ai technology isn’t advanced enough to produce a terminator … at least not yet. most of today’s ai technologies aren’t even sentient. for example, many of us have heard the term “chatbot” thrown around but are chatbots technically artificial intelligence technologies? while chatbots have the ability to understand how humans communicate, they don’t “think” for themselves autonomously. some argue that chatbots aren’t really ai because it can only follow through with pre-loaded responses or actions, while others point out that a chatbots’ ability to understand the way we humans write and speak gives it an edge of artificial intelligence. in fact, technologists today often disagree about what falls under the ai umbrella -- and we’ll leave the ‘what qualifies as ai’ debate to the experts. this report focuses on giving our readers an outline of current, generally-recognized-as-ai technologies.

slackbot wants to remind you it’s “still just a bot”.

source: slack

an ai tool primer

let’s start by reviewing the ai landscape and the most well-known tools and products.

in the graphic below, the x-axis reflects the level of technical sophistication the ai tool has. the y-axis represents the mass appeal of the tool.

want this chart? click to download.

most chatbots have a narrow use case, which is why they’re placed on the “narrow ai” side in our chart. a key feature of a chatbot is its ability to understand text-based commands. think of chatbots as the evolution of the command line.instead of us learning how to ask a program to do something in their language (“c:\dos\run”), programs now understand our language (“hey bot, what’s the weather today?”).

although chatbots typically have only basic functionality, there is the potential for high adoption in the future, hence their high placement on the y-axis. whether they tells us they help us buy flowers (see below), tell us how many visitors our website received in the past day, or even help us register to vote, these applications are the perfect example of how ai-powered tools will help people to find information and complete tasks more efficiently.

buying flowers through a chatbot

source: facebook

chatbots are programs enabled by ai, which differentiates them from more sophisticated personal assistant programs such as amazon’s alexa assistant. here’s why: while chatbots can understand language, they can’t do a lot beyond their core use case. we can ask a chatbot like poncho, which is designed to tell us the weather, about the weather. however, if we ask poncho to tell us the cubs’ 2016 record, it won’t know the answer because it isn’t designed to handle requests for information out of its scope. in contrast, programs such as siri have the natural language capabilities of chatbots but also operate with more sophisticated functionalities that are driven by machine learning. for example, siri can act as a calculator, find the cubs’ record, and tell you the weather. that’s because programs like siri aren’t just ai-enabled like chatbots; they’re powered by ai.

on the other side of the ai sophistication spectrum are tools such as ibm’s watson. while watson might be famous for beating humans at jeopardy, it has many practical applications because of its deep learning capabilities, as we found when hubspot interviewed ari sheinkin, vp of marketing analytics at ibm. watson uses machine learning to process huge amounts of data on nearly any topic. unlike a weather chatbot that can only tell you today’s forecast, watson’s machine learning capabilities, when properly configured, can scan mris to spot tumors in humans, figure out what products to recommend people browsing on websites, and, yes, answer jeopardy questions on national tv. machine learning tools such as watson not only recognize patterns and commonalities in large datasets, it leverages its past learnings to become smarter over time. while the practical uses for watson appear endless, most individual consumers aren’t going to interact with it in the near future, so for now it’s relatively low on the mass adoption axis.

“[ai] is helping doctors make better diagnoses. it is helping ... film editors make better films. it's helping musicians make better music. it's helping marketers make better bids on paid media.” - ari sheinkin, vp of marketing analytics, ibm

the ai terms you need to know

there are three major disciplines within ai today: natural language processing, machine learning, and an offshoot of machine learning, neural networks. the descriptions below are simple guides to each technology. (technologists, please put away your pitchforks.)

natural language processing enables a technology to understand text- or voice-based commands. understanding the complexities of human language and sentence structure has typically been touted as a key trait of artificial intelligence. tools like siri can hear you ask a question through speech recognition, translate your words into a text-based query using natural language processing, and then execute the query to find the answer to your question or request. once siri finds your answer, it constructs an understandable sentence that includes the answer, and it reads it aloud to you.

want this chart? click to download.

machine learning is a broad category that most of today’s sophisticated ai programs fall under. the basic definition of machine learning is as “clear as mud”: it “gives computers the ability to learn without being explicitly programmed.” essentially, someone can dump a bunch of data into a machine learning program, and the program will be able to sort through the information, form conclusions, and generate predictions based on those conclusions.

want this chart? click to download.

the data could be anything: a marketer’s email open rates from the past year, the top shared facebook posts in brazil, or the buying history of a retailer’s customers. a machine learning program can take that data and predict the best times to send out an email, identify the topics that will perform best on facebook, or provide purchase recommendations to customers based on what they’ve bought in the past. an ai program can be “supervised,” where it's programmed to solve for a concrete goal: “find me the best time to send emails based on past open rates.” or the program can be “unsupervised” and left to find any patterns on its own: “here’s a mess of data. tell me what patterns they have.”

neural networks are a type of machine learning that’s difficult to grasp. basically, neural networks are built to replicate the way the human brain works -- with neuron’s firing and sending information back and forth, creating layers of context and associations as a result. neural networks are the means to achieving artificial intelligence: by creating a program that mimics human intelligence, the program will eventually become intelligent on its own.

want this chart? click to download.

right now, the most well-known neural network is google’s deep dream, which is currently combing all the images on the internet. as deep dream learns to recognize objects and places, it generates some very odd and sometimes creepy images in its wake (see the example below). deep dream actually produces the images it sees when it inspects a picture. the weird psychedelic flourishes found are actually patterns that the software has observed and enhanced. it’s not entirely clear what google will do with deep dream, but it’s safe to expect that it’ll follow ibm’s watson playbook and productize deepmind, its master ai product, after it matures as a program. google’s ai programs already feed into its maps, personal assistant, home, google translate, and advertising services.

an image generated by deep dream

source: deepdream generator

making sense of ai technologies

the table belows provides more context to the technologies we’ve profiled. it’s not meant to be exhaustive, but it highlights the outcomes generated by each technology category and their increasing sophistication. once niche example is google deepmind’s alphago, a deep learning program that learned to play the ancient board game go. alphago only does one thing, but the technology behind is notable because the program can organically learn anything.want this chart? click to download.

another, more disastrous example is microsoft’s tay chatbot, which is designed to learn and then mimic how teenagers text and tweet. the goal was for tay to learn to write like a “cool” teenager by analyzing tweets sent its way so it could generate original content. the problem was … the internet. after only one day, tay began tweeting inappropriate content after twitter trolls sent it racist, sexist, and offensive content. microsoft suffered a huge pr embarrassment and very quickly put tay back in beta. tay’s misadventures prove it’s still early days for ai.

conclusion

artificial intelligence has already started to impact all of our lives, so hopefully this report has made today’s ai technology landscape a little clearer. as artificial intelligence capabilities advance, there will be many exciting innovations that we’ll continue to track here at hubspot. for all of us as individual consumers, ai will change how we obtain information, interact with loved ones, and buy from businesses. as professionals, ai has the potential to augment the way we work and make us much more efficient by taking care of the busywork we all hate doing. on a societal level, ai can help us discover cures to diseases, facilitate the education of millions of people, and yes, even generate heated debates on ethics.

interested in learning more about how people have adopted ai technologies today? subscribe to hubspot research and we’ll update you when our second data-backed report on ai is published in early 2017. we will review how 1,400+ consumers are using ai technologies and their interest in using chatbots for ecommerce and customer service requests. the early data suggests that people have quickly embraced ai-enabled technologies such as voice search and personal assistants, even though many don’t even realize they’re using ai. in the near future, we see huge potential for ai in areas such as ecommerce and customer service.

this report contains links for hubspot content, products, and services.

originally published dec 13, 2016 7:00:00 am, updated december 11 2019

people have long faced nuisances from marketers and advertisers in their lives: telemarketing calls during dinner, purposely loud and obnoxious commercials interrupting tv shows, or piles of mailers that usually go straight into the recycling bin. these types of advertisements, which push products and services onto unwilling consumers, have been joined by a new breed of ads that exist solely in the digital marketplace. think pop up ads, distracting banner ads, or the dreaded auto-playing video ad.

at hubspot, we wondered: what type of customer experience do these online ads create? how do they affect a brand’s reputation? and most importantly, how should marketers engage consumers with ads in the future?

given today’s rapidly changing advertising landscape, the ramifications for marketers are clear: as more consumers ignore or even remove themselves from receiving interruptive ads, advertising needs to evolve. ads will never disappear. but as consumer behavior changes, marketers need to get smart about their digital ad spend. in the near future, marketers who want to connect with potential customers must supplement their target’s online experience, not interrupt it.

table of contents (7 min read)

1. ads are everywhere, but it doesn’t mean people like them
2. consumers are actively avoiding ads
3. conclusion: is this the age of native advertising?

ads are everywhere, but it doesn’t mean people like them

ads are ubiquitous. regardless of format, saturation of ads in the consumer experience is clear in our research (see figure 1)

figure 1

that’s great for the marketers behind the ads, right? not exactly.

yes, ads are getting a lot of eyeballs, but what type of experience do they generate? let’s break down the experience ratings for each type of ad.

figure 2

consumers really hate telemarketing calls; pop up ads; and autoplaying video ads. if you’ve encountered these in the past, it hardly needs to be explained why people react so negatively to them.

let’s focus on the best-rated types of ads instead (see figure 3). no ads received a positive response, but when you look at the neutral responses a common theme emerged: ads with neutral experience scores are either expected or do not disrupt a consumer’s browsing experience.

email newsletters and email ads are unique forms of advertising that consumers have opted into. they’re promotional assets that a consumer can choose to read or ignore. they include the option to unsubscribe from mailings completely. the control is all in the consumer’s hands.

figure 3

the next set of ‘neutral’ ads is sponsored content that appear in linkedin, facebook, and twitter, which fall into the broader category of native advertising. defining native advertising is tough, but native ads typically match the look and feel of the platform it appears in and provides *useful* content rather than a typical cta to purchase something. considering the behavior the previously mentioned social networks encourage -- fast consumption of information through a scroll down gesture -- it’s easy to see how a sponsored ad appearing natively in-platform creates an unobtrusive experience. in fact, viewers often don’t notice the difference between a well crafted native ad and a standard post or listing in the platform.

there is also less risk of damaging a brand’s reputation if marketers choose to go native (see figure 4). opting for telemarketing calls, pop up ads, or autoplaying ads can do real damage to your brand’s reputation, with 72% of respondents indicating they would have a lower opinion of a brand if they subjected the consumer to a pop up ad. consider: for every successful conversion you may get via a pop up ad, how many potential customers did you put off?

figure 4

consumers are actively avoiding ads

inbound marketers have long known that power has shifted to consumers. the same is becoming true of ads as well. consumers today are taking charge of their experience and avoiding interruptive advertising. they are unsubscribing from emails, skipping commercials, ignoring phone calls and direct mail, closing webpages, and, most troubling to the ad industry, blocking online ads.

email unsubscribes

in our study, 96% of consumers have unsubscribed from receiving emails (see figure 5). the top reason was the sheer volume of emails being they were receiving from a company. a worrying 52% also indicated they didn’t sign up for emails to begin with. with can-spam laws long in effect, it’s more likely that the respondents 1) forgot that they signed up for emails or 2) didn’t realize they were going to receive emails when they submitted personal information to a website.

figure 5

marketers have long used email sign up as a key metric for marketing success. but if email recipients (who don’t even remember signing up for emails to being with) just end up becoming inactive or unsubscribing, is that metric really meaningful? email may produce a neutral experience but that doesn’t mean marketers should send irrelevant emails to inactive email addresses. most consumers have reached a saturation point on the emails they’re willing to open, much less receive.

email nurturing should evolve so that marketers focus on getting targeted content to engaged leads and delighting your customers, not on the sheer size of their email database. to drive real engagement, marketers can send contextual emails to their database using more granular segmentation, personalize their messages, and of course, make sure the content of the email is stellar enough to warrant a open or a click.

pop up and autoplaying ads = goodbye visitor

four out of five consumers have closed a browser or exited a website because of an autoplaying ad or a pop up (see figure 6). so not only does the marketer’s paid advertisement not connect with a consumer, the web host of the advertisement also loses a visitor. coupled with the generally negative reaction consumers have for these types of interruptive online ads, it really seems like a lose-lose option to pursue.

figure 6

the rise of adblockers: the display advertiser’s nightmare

ad blockers are applications (like plugins or browser extensions) that remove or alter advertising content on a webpage -- when a user loads a web page, the ad blocker application compares the scripts that load against its own database of scripts that it is designed to block (see figure 7 for a simplified diagram). if there’s a match, the ad on the page gets blocked. the majority of ad blockers target banner ads and pop up ads, and many block native and search ads as well. some completely remove all advertising from a page while others focus on ads that compromise privacy by blocking tracking codes. 

figure 7

over half of our respondents have installed an ad blocker or plan to install one within 6 months (see figure 8). generationally, adoption is highest amongst millennials. adblocker plus, the most popular ad blocking app, has reached 300 million downloads worldwide, causing traditional advertisers to reach near hysterical levels of panic. the reaction is understandable, given that ad blocking has cost publishers nearly $22 billion in 2015 alone.

people now spend 51% of their time accessing the internet via mobile devices. ad block tools have been available on android and ios mobile devices, but this year, apple announced that ios 9 will allow ads to be blocked in its safari browser and within apps. the implications are huge: 20% of all web browsing happen in safari. people spend 85% of their mobile time in apps. apple’s ios announcement means advertiser’s access to both safari and apps will be cut.

display ads have long been the bread and butter of most online advertisers. now that millions of consumers are blocking them, marketers who still want to use paid advertising online must be smarter about the content they create and the channels they use to distribute it.

figure 8

is this the age of native advertising?

platforms are aggressively pushing out content. consumers are sick of interruptive ads. what does this mean for the future of advertising? hubspot found that there is a clear preference for native advertising amongst digital consumers while ads that interrupt (pop ups, auto-playing videos, etc) are the lowest rated. to make your ads less interruptive, use unobtrusive formats like native ads. while traditional advertising channels will never disappear, marketers must begin factoring in native into their overall marketing strategy.

native ads can be sponsored tweets on twitter, promoted listings on amazon, or ‘advertorial’ content published on sites like buzzfeed. the content can be written by the publisher’s staff or by the sponsor company (see figure 9 for a breakdown of all the types of native).

figure 9

for years, many industry analysts have been heralding the rise of native advertising. the shift to native appears to be accelerating as platforms have amped up their focus on advertising in-platform. besides the social networks mentioned previously, publishers like buzzfeed, snapchat, and even netflix have placed bets on ads within their platform this year. facebook, beyond their business line of targeted advertising, even announced intentions to co-opt traditional news media. as various platforms demand the ability to host an advertiser’s content natively rather than linking to a separate web property, there are huge ramifications on how marketers do their work.

marketers interested in targeting ads to specific consumers in an unobtrusive fashion should seriously consider spending some time on native. there are downsides: in exchange for delivering a better ad experience, hosting content on a third party platform -- usually in the ‘advertorial’ use case -- means a marketer will have spotty access to metrics that prove an ad campaign’s success. after spending years figuring out how to tie together metrics from content marketing via tracking click-throughs, it will be disheartening for marketers to face the loss of control over data when switching over to native.

however uncomfortable this shift to platform hosted content may be for marketers and advertisers, our sentiment data clearly show that these platforms have a good reason to bet on native advertising--people don’t hate it. it’s in the marketer’s best interest to pursue advertising that is not disruptive to their intended target, even better, caters to the content needs of users. ensure your targeting is focused. most importantly, your ad’s creative content must be relevant and remarkable to your audience.

research methodology

 hubspot fielded a global online survey from december 2015 through january 2016. the survey was translated into spanish and portuguese. the responses were sourced through via email invitations, blog promotion, and social sharing. no personal information was collected and no incentives were offered.

this report contains links for hubspot content, products, and services.

originally published feb 8, 2016 6:00:00 am, updated december 11 2019