Bidtellect’s Native Video Suite Empowers Marketers to Scale Quality Video Content

Bidtellect’s Native Video Suite Empowers Marketers to Scale Quality Video Content

Bidtellect is excited to announce the expansion of our Native video suite, now the most comprehensive offering in the market. Marketers can choose from three distinct video products when delivering high-performing, targeted video content to consumers: Native In-Feed, Native Autoplay Preview and Outstream Video Autoplay.

Bidtellect’s Native video suite will help marketers drive ROI on video content and achieve real results from their audience. With Bidtellect’s platform, buyers are able to utilize all three formats in one advertising program, and with assistance from Bidtellect performance analytics professionals, managed service and optimization algorithms, can allocate budget based on the highest performing formats for each campaign’s KPI.

“We have invested significant time and resources into developing a market-leading suite of Native video products in response to consumers spending an increasing amount of time with online video content, particularly on their mobile devices,” said Lon Otremba, CEO of Bidtellect. “In the age of ad blocking, it is critical that marketers have the tools to create high-quality Native video experiences that the consumer can control. Bidtellect is an innovator and pioneer in the Native market, and we’re excited to expand marketers’ Native capabilities with the most robust Native video product set available in the marketplace.”
Bidtellect’s comprehensive Native video suite enables marketers to deliver highly targeted campaigns at scale across multiple differentiated formats:

  1. Native In-Feed is ideal for marketers that want to distribute long-form content (90 seconds or longer) across the web.  The click-to-play format is user-initiated and pre-qualifies consumer interest in the content. These are premium In-Feed placements on both desktop and mobile.
  2. Native Autoplay Preview allows users to preview short-form content before deciding to engage with the video. Users preview short-form content before deciding to engage and must click to expand the video, enabling marketers to identify audiences who chose to engage with their video.
  3. Outstream Video Autoplay positions video assets within sections of a site where consumers are actively consuming content, enabling marketers to align their message with consumer interest. The video will start playing when it is 50% in view and stop playing when it is 50% out of view,  providing cost-efficient video completion rates.

“Bidtellect has quickly become a key strategic partner for us when delivering video content for our clients,” said Sarah North at Empower MediaMarketing. “Their optimization technology coupled with premium scale always delivers results against our clients’ KPIs. In addition, their world-class account services team consistently helps us identify challenges and create innovative solutions to ensure maximum ROI on every campaign. High-quality video has been a major challenge for the industry, but Bidtellect’s solution has proven to be extremely successful.”
To learn more about Bidtellect’s Native video campaigns, register for our next webinar, or reach out to our team at sales@bidtellect.com.

Why You Should be Using Engagement, Not CTR, to Measure Awareness

Why You Should be Using Engagement, Not CTR, to Measure Awareness

By Clark Cooper and Andrew Sugrue
Creatives that attract a user’s attention and compel them to click on your ad are vital, but an even more accurate measure of awareness is how that user interacts with the promoted content. Many brands are still focused on CTR as a primary KPI, but drawing in a user is only part of the KPI. Knowing what a user does after the click is arguably more important than the click-through rate itself. Having a way to measure these post-click actions is fundamental to brand awareness, conversion tracking, or any kind of Native advertising campaign.
Engagement, i.e. how engaged your audience is with promoted content, is measured using multiple metrics. Bidtellect has trademarked a feature that we call the Engagement ScoreTM, which is a numerical value that shows how well a campaign is performing from an engagement standpoint. The Engagement ScoreTM is a single, unified and easy metric that quickly deciphers how engaged an audience is in real-time without having to dig through days’ worth of data. It uses weighted percentages of the campaign’s bounce rate, time on site, page visits and page views in order to give you a simple score from 0-10. The higher the engagement score the better. [Engagement Score Whitepaper

Bounce Rate

Bounce rate, one of the components that factor into engagement, is the measure of how long a user stays on an advertiser’s page after clicking the initial ad.  Bidtellect defines a “bounce” as a user who has stayed on the advertiser’s page for less than 5 seconds before leaving. Bounce rate provides great insight into the type of traffic coming to your site and also a clue to what users think of the promoted content. If you see a landing page that has extremely high bounce rates relative to others, it is a great indicator that the clicks are not yielding the desired outcome; the users are backing out quickly because they possibly inadvertently clicked on the ad or the ad is simply not reaching the correct audience. Additionally, users may bounce if your creative’s message or promise does not match the content of the landing page. Bounce rate is great to measure into not only the traffic sites are providing you but also how effective your content is.

Time On-Site

Another component of the engagement score is time on site, which provides insight into the quality of traffic sites are providing an advertiser. For example, if the average time on the advertiser’s landing page is low from traffic from a particular source, it is likely that those users are not the advertiser’s target audience, a strong indicator to block traffic from that specific site. Time on site also shows how long a user is reading and engaging with an advertiser’s content. The higher the average time on site is for a campaign, the more engaged a user is with the content. If the average time on site is consistently low the advertiser should consider additional content for users to interact with. It is important to have content that is going to engage the user and want to make them take further action by clicking to other pages, making a purchase or other engaged actions.

Page Views

The final component of the Engagement Score is page views.  A page view begins with a site visit, which is defined as the act of a user reaching the landing page after clicking an ad. There can only be one visit per click. If a user clicks an ad and then views multiple pages within the site, only one site visit is recorded. That does not mean, however, that all clicks lead to visits. If a user mistakenly clicks an ad and closes the browser or hits the back button, the user never reached the landing page (where the Engagement Code is placed) and therefore a visit will not be counted. Each time there is a site visit, there is also a corresponding page view. There can only be one site visit per click, but there can be multiple page views per click. Generally speaking, the more page views, the better. Here is an example of how page views are calculated: A user clicks an ad and then views two additional pages once he/she reaches the landing page  This will be represented by 1 visit and 3 page views (1 for the landing page and 1 for each of the additional pages). We see a lot of advertisers optimize towards this metric, also known as Page Views per Visit (PVV) calculated as page views/visits. It is one of the most useful metrics for determining post-click engagement with content. The higher the PVV numbers, the more engaged the audience is.  

When implementing the Engagement Code on a website and corresponding pages, it is very important to 1) make sure it is placed in the header of the page and 2) place it on every page that is accessible from the landing page. Bidtellect’s optimizations are made based on the information received via the engagement code so it is pivotal that we receive the most accurate and comprehensive data available.