Discrepancies in Advertising Billing: Technology to the Rescue Business Landscape
With a potential worldwide spending of $335 billion by 2020, digital advertising continues to be an evolving industry as breakthrough technologies, ever-changing platforms, and different pricing methods continue to push its boundaries. This dynamic environment is compelling advertisers and publishers to adopt new strategies for revenue growth.
It is a well-known fact that advertisers and publishers maintain independent ad servers to manage their ad campaigns. The reason being that, advertisers who buy media across multiple publishers must speak to different publishers across multiple data sources to change, report and compile the data in creatives. This can be a cumbersome process. Similar reasons apply to the publishers as well. However, by using independent ad servers, both the parties can manage their own independent reporting.
Though, in using different ad servers, publishers count the impression at the ad request while advertisers do so when the ad is delivered. The two are never the same. This causes a variance between amount spent and amount billed during ad campaigns, which is referred to as Advertising Billing Discrepancy in the ad serving food chain. Using different ad servers also leads to discrepancies caused by large creatives; latency in ad request and ad display; network connection and server reliability, ad blocking; ad caching, etc.
Discrepancies usually fall in the range of 5-10%, but can often exceed this, especially in case of technical problem with the ad. It is common to see campaign variances of up to 20% (as per DoubleClick for publishers). These discrepancies affect both the parties - advertisers as well as publishers. Publishers are affected as they encounter revenue leakage due to inventory loss, while advertisers receive lower ROAS (Return on Advertising Spend).
Reconciling this variance manually is a time-consuming process and a huge administrative cost that both publishers and advertisers have been accepting so far as the cost of doing business. Further, manual scanning of insertion orders and invoices to detect billing discrepancies do not help media firms prevent these losses. Continuous improvements are made to minimize these discrepancies; however, they continue to shoot up to 20% or more in certain campaigns, leading to revenue loss.
As this industry continues to evolve, so do the solutions offered by firms focused on improving processes to achieve business outcomes. These solutions understand patterns in the underlying data to identify rare anomalies that cannot be pre-determined. With advanced digital technologies like Artificial Intelligence and Machine Learning, campaign reconciliation can be easily automated to report discrepancies between advertiser and publisher delivery data. This compares 'what was sold' to 'what was delivered' by centralizing third party reports and mapping them to granular levels such as flight dates, creatives, placements, etc.
These solutions help reduce invoice, contract, and fulfillment discrepancies in media spend. By offering machine created rules that adapt to changing business environment. Discrepancies between Insertion Order (IO) and Invoice is reduced by predicting impression count difference using past patterns of resolutions and potential technical problems. Thus, cognitive search on past patterns resolves discrepancies, thereby reducing the revenue leakage.
As the market gets more competitive, complexities are bound to increase. However, advertisers and publishers will increasingly look at automated solutions to reconcile third party discrepancies, as these are not only faster but also more accurate, scalable, and cost effective. Especially, ones that integrate seamlessly with an order management system.