Last Updated on: 27th September 2023, 01:09 pm
Worried about runaway video campaign costs? You’re not alone, thankfully there are ways to keep the costs under control.
This article explains:
- Why online video content is so important
- The reasons that advertisers are concerned about their online video advertising budget
- How advertisers can use Deep Learning to optimize their budgets, and maximize the impact of your online video campaign
- Why CPCV should be the metric that advertisers use moving forward
Table of Contents:
- Why are video ad budgets increasing?
- Cost per mille is not granular enough
- Deep Learning can improve CPCV by up to 47%
- Try a CPCV campaign today and find out why Deep Learning works so well
No matter how you cut it, video content is a key component of a good advertising campaign. More than a quarter of users spend more than ten hours a week consuming online videos, and this figure is only likely to grow. This is a challenge for many advertising agencies and brands. Video content is certainly a powerful tool, but opaque metrics and increasing competition mean that video ads budgets are at risk of becoming overinflated.
Why is this happening, and how can you keep your video ads budget under control?
Why are video ad budgets increasing?
A big part of it is the COVID-19 pandemic. With people confined to their homes, and many shops forced to close, businesses were rapidly forced to pivot their focus online. This is particularly true for retail companies, which often had to accelerate their eCommerce plans in order to remain competitive.
Video in particular has become a key way companies differentiate themselves. Ad overload means that 70-80% of users completely ignore sponsored search results (1), and 86% of people don’t remember even seeing a traditional banner ad (2). In contrast, video ads tend to receive higher engagement and are shared up to 1,200 times more than their text counterparts.
However, this means that there is now a lot of competition in the video advertising space. Brands can produce incredible content, but they need to find a way to ensure that people can see them. This is a service that they frequently turn to agencies for, but traditional metrics can be opaque and frustrating. This means that advertisers regularly feel like their video budget isn’t stretching as far as it could be, but there is a better way.
Cost per mille is not granular enough
The traditional way a campaign is run is via Cost Per Mille KPIs. This essentially means that an advertiser is paying for every thousand views that reach a certain completion rate. This is frustrating for a number of reasons, however, the primary one is uncertainty. An advertiser has no accurate way to measure the actual budget of their campaign. This is where Cost Per Completed View (CPCV) comes into play.
The advantage of CPCV measurements is that companies know exactly what they’re paying for, and are able to better manage their budgets by ensuring only truly engaged users are paid for. However, in the past, it was challenging for many agencies to accurately predict CPCV measurements, but new advances in Deep Learning technology have changed that.
Deep Learning can improve CPCV by up to 47%
Deep Learning technology is unique in that it is able to process complicated, unstructured, datasets. This enables far more precise targeting of content, ensuring that they are shown to users who are most likely to positively engage with the company’s advert. Deep Learning algorithms are intelligent enough to allow multiple solutions to be used in concert, to ensure maximized results.
Let’s take a look at how this might work in practice. A company wants to sell a new model of electric car. RTB House’s contextual targeting solution would be able to identify websites where users interested in a new electric vehicle are most likely to be. At the same time, it would be able to compare the cost of placing content on various channels, and determine an appropriate strategy that maximizes VCR, while minimizing cost. As more campaigns are run, the Deep Learning algorithm becomes more intelligent.
The key here is Deep Learning’s ability to work with multiple solutions and complicated data-sets. This means that RTB House is able to provide a premium service at a highly attractive price-point. It also makes it far easier to rapidly scale operations, as the Deep Learning algorithm handles much of the work that would have previously required many data analysts to achieve.
Try a CPCV campaign today and find out why Deep Learning works so well
With competition for video ads on the rise, smart brands and agencies need to optimize their campaigns any way they can. Why use uncertain metrics like the CPM model, when your agency can take advantage of the opportunities offered by CPCV campaigns, powered by cutting-edge Deep Learning solutions?
Change the way you run video ads today – feel free to contact us.
(1) https://www.smallbizgenius.net/by-the-numbers/advertising-statistics/
