According to various estimates, internet users today attract an overwhelming number of advertisements (ads) as per their browsing behavior. Advertisements disrupt the users’ browsing experience by appearing on desktop and mobile devices in the form of pop-ups, banners, auto-play videos and full-screen images. Ad blocking tools have sprung up as a natural response for neutralizing them. Over 200 million users of such tools bear testimony to the fact that internet users dislike online ads.
Ad blockers are giving advertisers a run for their money by ensuring that ads never reach their intended audience. As a result, they have dented the revenues of online business entities that rely on them to sustain themselves. A 2016 estimate pegs global losses due to ad blockers at a whopping $40 billion.
Are Advertisers and Publishers Effectively Dealing with Ad Blockers?
Several websites block access to their content unless users deactivate ad blockers or pay to access content. It is an attempt to counter the revenue crunching effects of ad blockers.
Research shows that such measures are counter-productive. A huge chunk of internet users would rather stop visiting such sites than being arm-twisted into paying up or disabling these tools. Nonetheless, the majority of users are not averse to watching ads as long as they are not annoying. It sets a clear mandate for advertisers and publishers to serve ads that enrich users’ browsing experience.
Is There a Way to Enrich Users’ Viewing Experience?
Yes, advertisers and publishers can start by identifying non-performing ads. An ideal way of identifying non-performing ads is to map the browsing behavior of users with multiple ads. However, it is impossible to accomplish this task manually when you take browsing behavior of millions of users into account.
Our client who is a media conglomerate was facing a similar problem. One of their biggest advertisers wanted their ads to appear only in certain premium slots. Our client carried out a manual inspection and discovered that the advertiser’s ads appeared randomly in viewer streams. They were aware of the problem and had huge volumes of data at their disposal to affirm the veracity of the issue. In spite of this, they were unable to fix it. The reason behind this was the huge time and effort required for extracting insights from data rendered it un-actionable. They were in need of an automated solution to achieve efficiency and address the issue.
How Our Solution helps in Enhancing Viewing Experience
We wanted to make efficient use of the huge ad server data our client had at their disposal. We, therefore, built an automated BI mechanism that analyzes and reports ad server data in a meaningful way. Our solution addresses three major concerns –
1. Repeated ads
When users see the same ad multiple times in quick succession, it leads to Ad Fatigue. Repeated ads become less effective as viewers learn to ignore them. Our solution helps in this regard by identifying ads that do not adhere to frequency limits set by ad publishers. Non-adherence with pre-set frequency limits indicates an issue with the ad server. Also, our solution helps account executives to serve advertisers better by highlighting ads pushed in the ad server without a frequency limit.
2. Repeat ads of same industry category
Competitive ad separation is an essential requirement for online ad publishers. It dictates that two ads belonging to the same industry category should not appear during the same ad break. For instance, a McDonald’s ad should not immediately follow a KFC or Burger King ad during a viewer’s scheduled ad break. Our solution helps in avoiding such situations and helps publishers in drafting better ad media plans.
3. Ad Load Latency
Ad Load Latency is the time it takes to load an ad at the start of an ad break or after a previous ad ends. While the latency is too small for most users to notice, it may become noticeable while rendering ads of heavier file size on networks with slow bandwidths. This issue has a significant impact on users’ viewing experience, and publishers strive to keep the latency as low as possible. Our solution tracks the latency of every ad with details about the resolution at which the rendering took place. It allows ad publishers to address the issue holistically.
The Impact of Our Solution
The following numbers give a statistical account of the impact made by our solution –
- 99% Reduction in offending ad views: An offending ad view occurs when the same user views a particular ad multiple times in the same viewing session on a particular site under analysis. Offending views dropped by 99% as compared to earlier, e., before implementation of a fix to the ad server based on our solution
- 85% improvement in problematic viewing sessions: A viewing session is a unique viewer’s single continuous viewing session. A problematic viewing session is one which has at least one offending Ad view as per the definition above
- Saved millions of dollars: A fix to the ad server based on suggestions from this solution’s implementation has saved millions of dollars in lost ad revenues on a yearly basis
Our solution has helped in demonstrating to our customer that effortless exploratory analysis of their ad server data is possible. It has helped them in discovering ad view patterns and identifying areas of revenue leakage. Apart from saving millions of dollars for our client and enhancing their users’ viewing experience, our solution has armed them with insights to create a formidable media brand.
As our client’s understanding of the possibilities unearthed by the solution continues to grow, so does our capability to guide them through the advanced stages of business intelligence.
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