Best Practices for YouTube Bumper Ads

Best Practices for YouTube Bumper Ads

  03:03    Silver Push

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Bumper ads are 6 seconds or shorter YouTube video ads that enable marketers to reach more people and boost brand awareness by showing short but memorable messages. Bumper ads are unskippable, and are considered very effective, especially for smartphones when users are viewing videos on the go.

Although there is no known best recipe for creating perfect bumper ads, the following tips can help you make better bumper ads for your YouTube campaigns -

Be Focused

Bumper ads just provide 6 seconds to marketers to convey their messages. You cannot fit all of the elements of long-format video ads such as little story, service or product info, offer, tagline, branding, etc. into the 6 seconds format. So, rather than creating a mess, just focus on what you really want to communicate to consumers. Bumper ads perform well when they are a part of your YouTube contextual targeting strategy. This further strengthens the importance of creating a focused bumper ad.

Begin Ad with a Striking and Clear Signal

It is a good practice to begin your ad with a clear and striking visual signal. It will help viewers to orient themselves towards your ad and will clue them that they have entered into your brand’s space. This approach will also prevent users from getting confused.

Include Impactful and Memorable Elements

Whether you cut down an already created 30 seconds video ad into 6 seconds or create a new video, always include those elements that makes your ad powerful, impactful and memorable. Keep in your mind that your 6 seconds bumper ad can also act as an amplifier for your other advertising campaigns. You can even create great bumper ads by using simple approaches such as using a striking headline along with a captivating piece of music.

End Your Ad with a Final Thought or CTA

Ending your ads abruptly will not serve the purpose of your YouTube video campaign and will also leave your viewers confused. It is important to provide your viewers a clear-cut final thought or call to action (CTA). You can use around two seconds of your ad for this purpose.

Create a Series of Bumper Ads

Some of the highly successful YouTube campaigns go beyond a single bumper ad to a series of them. This help marketers present different facets of a brand’s message to viewers. Creating variations of a bumper ad reinforces the message it wants to convey and cast a high impact on viewers, while allowing the ad to keep fresh. Building in series not only allows pulling viewers fast, but also enables marketers to apply different ideas while using the same ad format.

Bumper ads offer a great way to marketers for accomplishing their YouTube ad targeting goals as they can be used singly, combined together to unfold a big story, or used with other video ad formats to amplify them.

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Effective Ways for Marketers for YouTube Targeting

Effective Ways for Marketers for YouTube Targeting

  06:05    Silver Push

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YouTube is the most popular video hosting website in the world with most extensive catalog of online videos. The number of monthly logged-in users on YouTube is about 2 billion. YouTube offers tremendous opportunities to advertisers.

YouTube provides a wide range of ad formats and varied targeting options to marketers, enabling them to effectively and easily reach their target audience. It is important for marketers to use the right YouTubetargeting options in order to drive success to their YouTube advertising campaigns. Using basic keyword and topic targeting at the start may not result in success. Below are discussed some of the hand-picked ways that you as a marketer can use for targeting on YouTube -

Custom Intent Audiences

This targeting option helps marketers in reaching new customers on YouTube on the basis of the keywords used by the users to search for products and services on Google.com. It is not necessary that these audiences have any previous interaction with your brand. These are built from users who have recently searched the keywords that were used by you for to creating your audience.

Some of the great custom intent audiences that you can test out for your video advertising campaigns on YouTube are -

·       Converting search queries - You can use your list of converting queries from your search campaigns to display video ads to users who have searched for these queries.

·       Converting keywords – These keywords are not the same as converting search queries. You can create a different audience based on these.

·       Competitor terms - These allow you to show your video ads to users that are actively searching for your competitors. 

·       Best-selling products - You can create an audience from your best-selling products. You can easily find these products from the sales report of your e-commerce platform. 

Life Events

Life Events can prove to be a great targeting option. It allows you to show ads to customers during life milestones such as starting a business, graduating from college, changing or starting a job, getting married, purchasing a house, retiring from job, etc.

These life events provide a great opportunity to brands, which offer products or services needed in these moments, to emotionally connect with consumers. For effective targeting via life events, your video creative should clearly show consumers how your brand can help them go through these milestones smoothly.

TrueView Discovery Ads

TrueView discovery ads appear on the search results and watch pages on YouTube. YouTube is a huge search engine, next only to Google.com. It allows users to conduct search for specific videos that they are interested in. TrueView discovery ads campaign is unique as a video advertising campaign as it is the only one in Google Ads that allows marketers to target just the YouTube's search results page.

Combining keyword targeting with TrueView discovery campaigns offers a great way to capitalize on user intent. By running TrueView discovery ad campaigns, marketers can take over the top spot of the search results page on YouTube.

Computer Vision-Powered Contextual Targeting

This is a highly effective YouTube targeting method that enables marketers to dramatically boost the performance of their YouTube video advertising campaigns. Computer vision enables AI advertising platforms to detect and understand contexts in online videos. Faces, emotions, logos, objects, activities and scenes in online videos can be detected with high accuracy.

By using computer vision powered contextual targeting, you can place your ad against the video content that is highly relevant to the ad, i.e. your ad is fully in line with the content the user is actively engaging with. As the ad shown matches the current interest of the user, the chances of user viewing or clicking the ad are very high.

AI contextual targeting powered by computer vision offers a very high degree of contextual relevance unmatched by other methods of contextual advertising such as keyword targeting, which fail to fully reflect the user’s current state of mind and cannot understand nuances in context.

The above-mentioned, hand-picked ways for YouTube targeting will help marketers in effectively achieving their YouTube advertising goals.    

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Using Computer Vision for Effective Visual Content Strategy

Using Computer Vision for Effective Visual Content Strategy

  02:46    Silver Push

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Visual formats such as images and videos are embraced by people over just a plain piece of text. Images and video enable brands to bring life to their messages, making consumers better understand their products and services. For brands, an effective and strong visual content strategy drives engagement and sales.

Research shows that brands are using visual formats much more on their own platforms and their social media pages for conveying messages to consumers, but less frequently in display ads.

But what is causing marketers to give less preference to display ads when it comes to using highly effective content formats - images and videos - for communication with the consumers? Research shows that using their own platforms allow them to exercise more control over their visual content in comparison to putting it out on the uncontrolled internet in the form of ads. There is enormous competition and it is hard for marketers to ensure that they are reaching their targets and drawing user engagement.

Another reason that marketers cite is of brand safety. Enormous amount of content is uploaded on the internet on daily basis and marketers have no idea against what content their ads would get displayed. On their own platforms, whole content is under their control.

Research shows that when it comes to using visual content for increasing user engagement, raising brand awareness and generating revenue, marketers face the following issues – insufficient viewability, contextual irrelevance, and ineffective demographic targeting. Data privacy regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), along with the gradual phasing-out of third-party cookies in Chrome by Google, have made practices like demographic targeting all the more difficult. 

The problems that hinder the use of visual formats by marketers in display advertising, namely – insufficient control over ad placement, insufficient user engagement, brand unsafe environment and data privacy laws – can be resolved through contextual targeting.

Contextual targeting involves placement of an ad against the content that is relevant to the ad, i.e. the ad is in line with the content that the user is currently interested in. Contextually targeted ads readily capture the attention of users and increase their chances of viewing or clicking them, as it is likely that users are already interested in the products or services being advertised.

Keywords-based contextual advertising often delivers sub-optimal results as keywords fail to fully reflect the user’s current state of mind, while AI-powered solutions that utilize technologies such as NLP and semantic analysis fail to understand nuanced contexts and complex relationships that exist between words.

The true contextual targeting can only be achieved through computer vision. By leveraging computer vision, marketers can take control of their visual content strategy and use visual formats to run highly effective video advertising campaigns, without worrying about data privacy and brand safety issues.

Computer vision is an advanced technology that enables computers to understand images and videos. Computer vision uses deep learning to make computers learn how to detect patterns in images and streaming videos.

Computer vision powered contextual advertising technology works by accurately detecting contexts in streaming videos in order to display in-video ads that are in line with what the user is actively engaging with. Any content that is unsafe or unsuitable is contextually filtered out to provide true brand suitability.

Computer vision enables marketers to embrace contextual targeting and fully utilize their visual content for achieving their marketing goals.

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Using Computer Vision for Effective Visual Content Strategy

Using Computer Vision for Effective Visual Content Strategy

  04:04    Silver Push

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Visual formats such as images and videos are embraced by people over just a plain piece of text. Images and video enable brands to bring life to their messages, making consumers better understand their products and services. For brands, an effective and strong visual content strategy drives engagement and sales.

Research shows that brands are using visual formats much more on their own platforms and their social media pages for conveying messages to consumers, but less frequently in display ads.

But what is causing marketers to give less preference to display ads when it comes to using highly effective content formats - images and videos - for communication with the consumers? Research shows that using their own platforms allow them to exercise more control over their visual content in comparison to putting it out on the uncontrolled internet in the form of ads. There is enormous competition and it is hard for marketers to ensure that they are reaching their targets and drawing user engagement.

Another reason that marketers cite is of brand safety. Enormous amount of content is uploaded on the internet on daily basis and marketers have no idea against what content their ads would get displayed. On their own platforms, whole content is under their control.

Research shows that when it comes to using visual content for increasing user engagement, raising brand awareness and generating revenue, marketers face the following issues – insufficient viewability, contextual irrelevance, and ineffective demographic targeting. Data privacy regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), along with the gradual phasing-out of third-party cookies in Chrome by Google, have made practices like demographic targeting all the more difficult. 

The problems that hinder the use of visual formats by marketers in display advertising, namely – insufficient control over ad placement, insufficient user engagement, brand unsafe environment and data privacy laws – can be resolved through contextual targeting.

Contextual targeting involves placement of an ad against the content that is relevant to the ad, i.e. the ad is in line with the content that the user is currently interested in. Contextually targeted ads readily capture the attention of users and increase their chances of viewing or clicking them, as it is likely that users are already interested in the products or services being advertised.

Keywords-based contextual advertising often delivers sub-optimal results as keywords fail to fully reflect the user’s current state of mind, while AI-powered solutions that utilize technologies such as NLP and semantic analysis fail to understand nuanced contexts and complex relationships that exist between words.

The true contextual targeting can only be achieved through computer vision. By leveraging computer vision, marketers can take control of their visual content strategy and use visual formats to run highly effective video advertising campaigns, without worrying about data privacy and brand safety issues.

Computer vision is an advanced technology that enables computers to understand images and videos. Computer vision uses deep learning to make computers learn how to detect patterns in images and streaming videos.

Computer vision powered contextual advertising technology works by accurately detecting contexts in streaming videos in order to display in-video ads that are in line with what the user is actively engaging with. Any content that is unsafe or unsuitable is contextually filtered out to provide true brand suitability.

Computer vision enables marketers to embrace contextual targeting and fully utilize their visual content for achieving their marketing goals.

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New Research Highlights the Importance of Brand Safety

New Research Highlights the Importance of Brand Safety

  02:13    Silver Push

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Placement of ads in a brand unsafe environment tarnishes a brand’s image, weakens consumer trust, and results in decrease in revenue. Ensuring brand safety is very important for brands, whether small or big. Like previous research, new research also fully backs this statement.

A recent survey conducted by GroupM, which included fourteen-thousand consumers in twenty-three countries, has shed light on the concerns that consumers have about digital marketing and advised important considerations for digital marketers. According to the survey, more than six in ten (64%) consumers would have a negative opinion of a brand displaying ads against inappropriate content. 37% respondents, i.e. over one-third of respondents, found digital ads to be highly intrusive.

75% of the survey respondents believed that the responsibility to stop harmful or inappropriate content from appearing rests with the digital platforms. They said that proactive steps should be taken by the marketers in order to make sure that parameters are set around ad placements for creating marketing effectiveness and affording protection to brand value.

The survey report found that the trust of consumers in digital marketing is less than expected. The trust factor is very important as brand value is directly correlated with the consumer trust. For brands, it means they should work on building a responsible digital marketing ecosystem that does not dampen consumer trust in brands. For keeping consumer trust intact, a brand should take measures to prevent ad placement against any type of harmful or unsuitable content.

The findings of the above survey are consistent with those of the survey conducted by the Trustworthy Accountability Group (TAG) and Brand Safety Institute (BSI) in 2019. The survey was conducted among the US consumers and included over one-thousand respondents. 90% of the respondents said that ensuring non-placement of ads against unsafe or inappropriate content is very or somewhat important for advertisers.

Over 80 percent said that they would reduce buying or would entirely stop purchasing a product, which they buy regularly, if in case, it is advertised against extreme or dangerous content. 90% respondents said that they would decrease their spending on the product advertised next to the content involving terrorist recruiting videos, while 67% said they would completely stop purchasing it. 70% respondents held advertisers responsible for ensuring ads do not run against unsafe or inappropriate content, while 68 percent held ad agency responsible.

To prevent placement of ads against unsafe content, majority of brands make use of traditional brand safety solutions such as keyword blocking and whitelisted channels. These solutions often limit the reach of the campaigns and hampers monetization.

AI-powered brand safety solutions have appeared in the market, but those dependent on machine learning, NLP and semantic analysis fall flat when it comes to comprehending the sub-text, nuanced contexts and complex relationships words have in written or spoken language.

The innovative AI-powered brand safety solutions that make use of computer vision offer unparalleled context relevance and overcome the limitations of other brand safety methods such as content under and over-blocking. Computer vision enables accurate detection of contexts in online videos such as faces, on-screen text, emotions, logos, objects, scenes and activities. Computer vision powered brand safety solutions contextually filter out harmful or unsuitable content, providing a truly suitable environment to brands for video advertising.

With research continuously backing the importance of brand safety, adopting an effective brand safety strategy is a must for brands.

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  01:56    Silver Push

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How are brands responding to COVID-19? A brand marketer survey across SEA market

Brands have been profoundly affected by the coronavirus pandemic. Brands’ response to the coronavirus pandemic not only impacts consumers’ trust today, but it will also significantly impact future purchasing decisions. Moreover, brands could face irreparable damage to their reputation due to brand safety risks associated with COVID-19 related content.

To gain insight into how brands are responding to COVID-19 pandemic, Silverpush conducted a survey of 150+ agency heads, business leads in media, and brand marketers in the SEA region in April 2020.

The survey aimed to understand how brands are adapting their marketing strategies to the impact of the COVID-19 outbreak and how they are mitigating the very real brand safety risks the rapidly growing coronavirus related content consumption poses.

How are brands re-imaging and engaging consumers in light of the pandemic?

The survey found that in the light of the pandemic, brands are reimaging by adapting their marketing tone and initiatives to consumer expectations. Only 5% respondents reported no change in brand positioning pre and post COVID-19, whereas 95% reported a distinct shift that resonates with government policies, and responds to the new consumer expectation.

Ad spending poised to decline

The industries heavily impacted by coronavirus outbreak such as travel, hospitality, physical retail and more have and will continue to paused marketing initiatives. Only 16% respondents said these industries will protect marketing budgets for a stronger comeback later.

Moreover, the survey indicates that it is unlikely that the industries such as health and FMCG that are currently experiencing higher demand will increase marketing spend to capture the demand more aggressively. Even though past recessions have shown that aggressive cuts in ad spends can lead to longer recovery cycles.

Ad Spends are shifting to digital channels

Even with significantly increased TV viewership across SEA, boosted due to government-imposed lockdowns across the region, and various studies indicating curtailed TV ad spends can adversely affect brand health measures - only 2% respondents said brands are spending more on TV and mainstream media, and a large percentage indicated rapid shift to various digital channels.

Brand safety is a key concern, and is driving ad spend cuts

Industries, except few such as health, hygiene, pharma, etc., are stringently avoiding advertising across COVID-19 related content. Publisher news sites and news channels on platforms like YouTube are facing advertisers’ block-lists due to coronavirus-related coverage.

A measure of advertisers’ confidence on brand safety tools is depicted by how despite using third party tools to ensure safe ad placements, brands are reducing marketing budgets and pausing advertising specifically to avoid association with Coronavirus related content.

71% respondents reported brands are reducing marketing budgets ranging from complete halt of marketing spends leading to up-to 80% budget cuts, in order to avoid running ads across coronavirus related content

Can context relevance be the answer?  

Emerging AI powered solutions are increasingly focusing on providing context relevance, and are fast becoming an answer to brand safety woes. AI enables processing of large volumes of data at speed, with better context, at higher scale and improved targeting efficiencies.

However, most of these contextual targeting solutions still depend on the use of NLP and semantic analysis, not truly understanding the sub-text, nuanced contexts, and complex relationship words have in written or spoken language.

AI and computer vision-powered video advertising solutions can detect in-video contexts, offering a higher degree of context relevance that surpasses limitations of traditional keyword targeting and NLP based technologies. They offer unparalleled insight for advertisers to place context-relevant in video ads and exclude unsafe content in a highly structured manner, and at the scale programmatic has traditionally offered.

You can access the full report ‘Brand Response to COVID-19 in SEA’ for detailed insights from the survey. 

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Consumer Focused Marketing and Efficient Advertising with AI

Consumer Focused Marketing and Efficient Advertising with AI

  01:23    Silver Push

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Advertising has been made easier and efficient with Artificial Intelligence. Our lives are now encircled around internet, smartphones and social media. Our means to interact with each other and consume information has been transformed to a great extent and majority of it takes place through the above mentioned factors. As the machine-human interaction has been changed (thanks to the new technologies), the advertising method has to adopt a new framework of engagement, and AI is the one key solution for Digital contextual advertising.

AI is changing the dynamics of the modern advertising industry. It plays a key role in optimizing advertising campaigns and programmatic advertising by analyzing audience data, for better understanding and catering to what an individual customer needs. But the biggest question that comes up now and then is if AI really is the way for marketers and advertisers to increase maximum consumer reach and engagement and is it feasible only for the companies that can afford this technology.

Contextual In-Video Advertising

Up until this point, the dominant medium for advertisers in Asia was- Television. Advertisers spent a lot of money on TV ads to capture uninterrupted attention of consumers, who spent most of their free time in front of a TV at home. But now, since most of the customer engagement has shifted from TVs to smartphones, and more content is being obtained from across multiple platforms, advertisers need to be aligned with contextual advertising. But the shift across these dimensions can be very tricky and challenging for the advertisers, as they need to keep a balance between the quantity and the quality of content and creating effective marketing strategies. This is where AI steps in!

The prime focus of advertisers today is delivering the right content to the right audience, and since today’s internet driven eco-system is being dominated majorly by Facebook, YouTube and Google, more and more advertisers to are try to sneak into the complex algorithms of targeting the ‘right’ audience.

Contextual targeting is the prime focus of brands, so that the right and optimized content can reach the selected segment of the audience for maximum impact. AI focuses on specific range of outreach solutions, helping brands to build their contextual advertising platform, especially in today’s time where consumers expect to be served with what they need, rather than what the ‘may’ want.

AI Machine Learning

In today’s time, Artificial Intelligence is a necessity to run quality ads and reaching out to focused consumer. Even if emerging brands are looking forward to capturing a large scale of market, AI driven marketing solutions can drive wide-reaching campaigns, helping these brands to shift their focus from quantity to quality.

AI is here to create advertising campaigns in real time and its algorithms help in reaching the right audience. It has been elevated from just being savvy to necessity. There is going to be a big shift in the field of advertising from the old methods to an entirely new dimension, and that would be- Context. 

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