ADOTAS – Many of the world’s leading online players are struggling with ad-funded business models. Social networks are still suffering from low ad yields, while paid content is dominating internal newspaper discussions following recent pay wall announcements by The New York Times and Le Figaro.
The issue here is relevance. The ads are not relevant, so the audience is not engaged and the performance of the ad is weak. Yet, brands and media agencies are grappling with the opportunities presented by social media and the proliferation of user-generated reviews, ratings, recommendations and other forms of online expression.
Online opinion has turned into virtual currency for businesses looking to market their products, identify new opportunities and manage their online reputations. As a result, social media pages have driven the volume of ad inventory through the roof. Irrelevant ads + tons of inventory and pageviews = the conundrum that online publishers are facing.
These major issues have generated a fresh wave of semantic technology. For display advertising, it solves the pitfalls of contextual targeting. Rather than crude delivery of ads based on keywords and frequency, semantic targeting delivers ads based upon a full appreciation of all the topics, actions and emotions in text. It can automatically identify highly relevant advertising opportunities, across trusted news sites as well as social networks, while protecting businesses from brand safety issues.
Consider the statement, “Although unhealthy diner food like IHOP is currently in vogue, sushi remains the healthier choice.” This is clearly an opportunity for sushi and an unfavorable context for IHOP or diner food in general. Knowing the difference is the key to conversion; only semantic technology can advance the one and protect the other.
The benefits, however, must be implementable at scale. The good news is, unlike previous incarnations of natural language processing technology that were painfully slow, various related offerings are readily available for commercial deployment.
Agencies and ad networks are being tasked to rapidly deliver rich contextual and semantic analysis — fast enough to support dynamic ad targeting and scalable enough to pull this data across thousands of sites and millions of pieces of content. They need to do this in such a way that does not require significant outlay or implementation costs, with the data output easily incorporated into campaign planning, execution and measurement.
Having worked in natural language processing for almost a decade, I was extremely encouraged to see the rising level of engagement in semantics in 2009. Publishers, ad networks and media agencies now recognize the pitfalls of keyword targeting and the role that semantics has to play in monetizing the growth in online opinion.
While the advertising community was very focused on its core business in 2009, as the market picks up and online advertising budgets grow, so will the budgets for innovation in campaign delivery. We’re hearing more and more from companies that are now shifting from wanting to talk about semantics to wanting to implement it into their advertising campaigns.
However, even though semantic technology has become easier to deploy commercially now, a barrier still exists in the lack of deeper understanding of how to run and measure campaigns. This is what we’re hopeful about in 2010. In the coming weeks and months, I expect to see more companies — agencies and ad networks — implement and create value from semantics.
The industry will start to look distinctly different — with much improved ad performance and completely new value created through ad-user-engagement on multiple levels. I predict that previous valuations of social networks that may have looked ambitious or even foolhardy will start to look conservative in light of these new engagement opportunities.
As implementation becomes painless and the metrics for measuring ROI mature, 2010 could be the year that Web semantics begin to transform the digital marketing landscape.