{"id":296800,"date":"2019-05-08T04:00:00","date_gmt":"2019-05-08T04:00:00","guid":{"rendered":"https:\/\/integralads.com\/insider\/real-time-viewability-insights-for-real-time-optimization\/"},"modified":"2023-07-12T09:47:57","modified_gmt":"2023-07-12T09:47:57","slug":"real-time-viewability-insights-for-real-time-optimization","status":"publish","type":"post","link":"https:\/\/integralads.com\/apac\/insider\/real-time-viewability-insights-for-real-time-optimization\/","title":{"rendered":"Real-time viewability insights for real-time optimization"},"content":{"rendered":"

The emergence of programmatic advertising has created a huge opportunity for digital marketers to more effectively reach their ideal customers, enabling an advertiser to bid on placements within milliseconds. Although the automation and efficiency benefits are clear, programmatic can present new challenges when it comes to measuring whether an ad is creating its desired impact.<\/span><\/p>\n

Tackling core verification challenges<\/strong><\/h5>\n

Campaigns are often plagued with core verification challenges: invalid, non-human traffic, placements served on inappropriate or offensive content, or ads that are completely out of view from users. To increase transparency, IAS monitoring solutions analyze viewability, invalid traffic, and brand safety across ad campaigns. IAS Optimization takes transparency a step further, allowing advertisers to avoid these same risks before placing a bid programmatically. But demands have grown; advertisers now also seek mechanisms to guide demand-side platforms (DSPs) to approach viewability in a more nuanced way \u2014 and IAS has expanded capabilities to meet these needs. In addition to approaching viewability as a binary question of whether an ad is viewable (an effective way to handle viewability in many cases), IAS offers Real-Time Signals (RTS) as another way to tackle the challenge. RTS considers viewability as one piece of a more sophisticated algorithm, while expanding the variety of metrics an advertiser can reference.<\/span><\/p>\n

To maximize return on investment, DSPs need to assess the monetary value of each impression served, on behalf of the advertiser, allowing advertisers to bid on placements in real-time. When it comes to fraud and brand safety, it can seem obvious whether an impression is worth the spend or not. An impression served to non-human traffic \u2014 whether actually fraudulent or served to non-malicious bots \u2014 \u00a0is worth nothing to the advertiser (after all, it\u2019s difficult to convince a bot to buy products). Similarly, if the buyer serves an impression on content that is inappropriate, offensive, or inconsistent with brand values, brand reputation and consumer loyalty could be significantly impacted. Standards for viewability, however, are often not so black and white.<\/span><\/p>\n

Digital ads can be classified as out-of-view if the user has not scrolled all the way through the webpage to reach the ad, or if the ad was not on screen (time-in-view) long enough to qualify as in view. Once a bid is placed, neither the advertiser nor the DSP has any insight into how the end user will interact with the page. For many digital placements, it is impossible to say for certain if the ad will or will not be in view \u2014\u00a0only whether it is probable, based on historical data. \u00a0<\/span><\/p>\n

Traditional pre-bid filtering and other rule-based approaches are a good, straightforward way for advertisers to avoid buying impressions that are unlikely to be in view, or to focus on buying impressions with a good chance of being in view. But what if an impression has a 40% chance of being seen? Should they avoid bidding on that placement entirely \u2014 or simply bid less to account for this lower in-view probability? If viewability is one of many KPIs that you wish to optimize, taking these probabilities into account might be worthwhile. Rather than the binary, viewable-or-not approach of standard pre-bid solutions, a more robust product that considers the variability of viewability could be a better way to reach your campaign objectives.<\/span><\/p>\n

Use Real-Time Signals to inform bidding<\/b><\/h5>\n

Real-Time Signals (RTS) enables viewability measurements to inform bidding algorithms instantaneously while balancing them with other factors. Unlike the binary, buy-or-don\u2019t-buy approach, RTS offers a solution that takes into account the gradations between viewable and not viewable.<\/span><\/p>\n

For example, consider a campaign to help sell a 20-speed mountain bike with two options for targeting: <\/span><\/p>\n