Creative Best Practices Across the Fashion, Travel and Tech Verticals

Creative Best Practices Across the Fashion, Travel and Tech Verticals

Each quarter we provide a high-level overview of the Native Advertising ecosystem so that marketers can have a deeper understanding of their content distribution strategies. This quarter, in addition to trends in Standard Native, we are taking a look creative best practices across devices, ad formats, multiple verticals and KPIs.

One of the biggest benefits of Native Advertising is the opportunity for brands to engage their audiences with high-quality creative and content. Native ads are not offer-driven or intrusive like banner ads, but value-driven content provided for consumers in organic, immersive environments. But for this to be effective, brands need to understand how to best create and deliver smart, engaging content to consumers.

Bidtellect’s in-house creative services team, [b]+studio, has a deep knowledge and expertise in developing high-performing creatives across devices, ad formats, campaign objectives and verticals. Based on experience and performance, we created multiple best practices to follow, for example: Educate, entertain and bring value, Use Compelling Headlines that are Value driven vs. Offer Driven, Facilitate concern, doubt or worry, Offer to educate or solve problems, Ask questions, Choose authentic, emotional images, Use bright colorful images etc.

For the Q3 2017 Native Intelligence report, we took a deep dive into the best practices for creating and executing premium creative that drives results for brands. [b]+studio analyzed over 100 campaign creatives in Q3 2017 across the fashion, travel and tech industries to reveal important creative best practices and insights.

For Successful Fashion Creative, Ask Questions and Be Educational:

 

  1. Creatives that ask questions drove high Engagement Score results on all devices
  2. Headlines that ask questions had very high performance.  For example:
  3. Using questions creates intrigue. They immediately draw the reader in, driving engagement.
  4. Headlines that are compelling, educational and value-driven also performed very well across all units.
  5. Campaigns performed best when the product is showcased.
  6. Use bright colorful images to attract consumers.
  7. In-feed and In-ad on mobile drove high Engagement Scores for both clothing and shoe campaigns

Across the Bidtellect platform, we found that within the fashion category CTR is typically higher on mobile than desktop, but Engagement Score is higher on desktop than mobile. In terms of specific Native ad types, Engagement score for fashion brands’ content is highest on In-Feed formats but CTR is highest on Recommendation Widgets.

Travel Content Performs With Call to Actions and Bright Images:

  1. Call to action performs best for the Travel vertical both in headline or description. For example:

  2. The most popular ad format was In-Feed.
  3. Using the call to action creative best practice drove the highest CTR.
  4. The Listicle, Call to action and “How to” best practices delivered the best performance for Engagement Score
  5. Using bright colorful images and having people in relevant settings performed best

Taking a closer look at the travel category we found similar trends by device. CTR is typically higher on mobile than desktop, but Engagement Score is higher on desktop than mobile. In terms of specific Native ad types, travel brands’ content Engagement score is highest on In-Feed formats but CTR is highest on Recommendation Widgets.

With Tech Content, Consumers Will React by Facilitating Worry or Doubt:

  1. Headline and Descriptions that facilitate worry or doubt had an average Engagement Score of 7.5 and a CTR average of .52%.
  2. Asking questions and offering to educate and inform performed best in this vertical. For example:
  3. Desktop In-feed drove the most conversions.
  4. Tablets drove the highest CTR with an average of .51%.
  5. Creatives that display products in the creative had an average Engagement Score of 8.3 and a CTR of .14%

More specifically for the tech category, we found that CTR is significantly on mobile than desktop. Similarly, Engagement Score is significantly higher on desktop than mobile. In terms of Native ad types, travel brands’ content Engagement score is highest on In-Feed formats but CTR is highest on In-Ad.

Key Native Trends from Q3 2017

Mobile CTR was higher than desktop by nearly 30%.

Conversions were the primary campaign objective this quarter. Engagement continues to be an important indicator of success for marketers in their Native campaigns and Video (including cost per completed view and play rate) is on the rise.
Goal Type Utilization Q1 2017: CTR: 36% Engagement: 17% Conversions: 42% Video 5%

In Q3 2017 Shopping related content was the most engaging. The third quarter includes back to school, shopping for new fall styles, fall season sales and the holidays on the horizon. The second most engaging type of content was travel.

See below for previous quarterly reports:
Q2 2017
Q1 2017
Q4 2016
Q3 2016

Optimization Technology Focuses on Conversions to Drive Performance for Advertisers

Optimization Technology Focuses on Conversions to Drive Performance for Advertisers

Arthur Hainline, Director of Analytics & Optimization, Bidtellect

Bidtellect’s optimization algorithms are built on machine learning, using the billions of data points running through our platform to create predictive models and algorithms. The technology is designed to simplify the complexity of digital advertising, make smart buying decisions and ultimately drive conversions for advertisers.

Performance will always be a top priority for advertisers when evaluating their digital investments. Trusting that there is automated technology in place to ensure spend is consistently optimizing toward desired performance metrics is really important for advertisers’ confidence in their digital marketing efforts. As with all of our technology innovations and enhancements, we are always evaluating the needs of our clients and enhancing our technology to exceed these expectations.

Focus on Conversions and Performance

Many of the new capabilities in this latest iteration of our optimization technology have a primary focus on conversion based optimizations and post-click activity. This focus improves scaled performance for marketers across multiple campaign metrics. In addition, we made enhancements to existing algorithms to ensure the smartest buying decisions for advertisers.

Multiple KPI optimization, or the ability to optimize toward one or more KPIs in a given campaign, has proven to be highly valuable for advertisers. These latest advancements expand upon this capability, changing the methodology. Beforehand, advertisers were able to optimize toward each goal for a percentage of the campaign. For example, 20% of the campaign optimized toward CTR and 80% of the campaign optimized toward conversions. With these latest changes, advertisers can now optimize toward multiple goals and in concert throughout the campaign.  

In addition, we introduced the ability to enter KPI targets. When the user enters a specific target that is what the campaign will optimize toward, leading to stronger performance.  If the target is left blank, the campaign will optimize against the average established by the campaign, striving to continually improve that average.

View through conversions is a new metric to report against and optimize towards with unique optimization algorithms. With this conversion type, the user has the ability to change the view through attribution window, ranging between 1-30 days. The combination of the new flexible multiple goal methodology, the ability to change view through and click through attribution windows and the ability to enter target CPA goals, we can accommodate clients that have different standards for measuring attribution.  

Optimizing toward post-click activity is really important for advertisers to understand how consumers engage with their content. We developed a new type of optimization, Quality Optimization, designed to enable advertisers to optimize toward this post-click activity when they are unable to implement code on the content. Quality optimization is a unique way for advertisers with engagement or conversion goals to optimize toward high-quality post-click activity.

Video is an integral piece of marketers’ strategies. Recognizing this growth, we introduced two new video goal types, Play Rate and Cost per Completed View (CPCV), providing marketers with multiple options for their video campaigns, depending on objective and type of content.

With these most recent changes, Bidtellect’s platform now offers 11 unique goal types with 66 possible goal combinations.  Every client has their own set of unique goals. Bidtellect recognizes that a major part of client performance is offering unique optimization goals that exactly match their needs.

Additional Enhancements

Additionally, advertisers have four new pricing options to choose from.  flat Cost per Play (CPP) and flat Cost Per Completed View (CPCV).   

Flexible bidding strategies in line with real-time performance have always been a crucial part of how Bidtellect approaches media buying. To support this, we added two new bid types that enhance our ability to buy ads at a price that reflects their value – Dynamic CPC and Dynamic CPM.

Our objective is always to deliver successful campaigns for advertisers and often times this means considering the end user experience. User-level CTR estimates which monitor an individual’s ad exposure and interaction (clicks, engagements etc.) and adjusts delivery based on these insights to avoid ad fatigue and to not inundate consumers with repetitive messaging.

Importance of a Smooth Pacer

Underlying Bidtellect’s optimization technology is the power of a smooth pacer. A smooth pacer enables advertisers to reach their widest audience by pacing out the spend of budget. A built-in, automated pacer is more effective and efficient than frequency capping. This makes planning and budgeting easier for advertisers because the pacer, backed by a real-time data pipeline, ensures smooth and effective pacing to the make the most of the ad spend.

We are now bidding more frequently when inventory has driven optimal KPIs in addition to modifying the actual bid amount. Our pacing algorithm drives smooth and consistent delivery, considering time of day and volume levels in its predictive algorithm.