If you want to give away your online consumer news content to readers for free, there's one metric you'll be watching very closely: the health of the display advertising market.
According to NMA's Top 100 Interactive Agencies 2010 guide (registration required), display ad spend will grow by 9.3 percent in 2011. But many publishers report that yields for display advertising have been falling faster than 10 percent year on year. IPA/BDO's quarterly Bellwether report found that 22 percent of companies lowered their marketing spend in Q4 last year.
So if you're hoping to monetise your online free content with ads, that's a bit of a problem.
But that doesn't deter some people: Paul Hood, digital marketing director at newspaper group Trinity Mirror, has encouraged his ad teams to target their efforts towards readers' habits and profiles - and he says it's working. Here's a Q&A we did with Hood just after he'd taken part in NMA's Future of Online Advertising event at the tail end of last year.
TheMediaBriefing: You're of the opinion that sheer volume of ad impressions isn't sufficient to generate meaningful revenue from display advertising. Why is that?
Paul Hood: The volume of online ad inventory available is almost unlimited. It's great that demand is growing, but it's a reality that supply is growing even faster, so the average yields that publishers of premium content have been able to command has fallen in recent years. That's the bad news.
The good news for traditional publishers is that because their content is of a high standard and their brands are authoritative and trusted, readers pay close attention to it - they're engaged by it.
If the publisher has taken the trouble to gather insight into their audience (demographic & behavioural data), understand the context of the content they're consuming and target a message at the right time, that's a strong value proposition. That's where the publisher advantage lies over sites like Facebook.
Sure, social media sites are able to provide a lot of demographic data about their audiences, but if you're trying to target, let's say, potential buyers of a new Ford Focus - would you rather target the reader when they're on Facebook "poking" a friend or organising their next night out, or when they're on the Daily Mirror site reading a Richard Hammond review of a Ford Focus? Content is still key.
TMB: OK, but what if an ad planner/buyer simply buys huge volumes of display ad inventory at a vastly discounted rate from an ad network or a social media site and rely on post-campaign analytics to understand their target audience?
PH: That's a reasonable approach, but it falls down if the advertiser's goal is to build a meaningful relationship with their target customers in order to convince them to buy something. Our readers - like the customers of any premium content brand - have built a relationship with the brand; they have an affinity to the content, they trust it, they consume it frequently.
The content defines the context of their visit. With social networking sites, the context of the visit varies wildly, making any purchase intent extremely difficult to identify. A potential customer who can be identified by demographic information, context and behaviour is surely more valuable worth more than one identified by demographic alone.
TMB: In your presentation, you mentioned you're using Visual DNA's picture-based personality test technology to understand readers better. Does it work?
PH: To get our readers to engage positively and provide data about themselves, we created some fun image-based quizzes that are contextually relevant to the site that they're on, using Visual DNA technology.
Within a few weeks, more than 100,000 people had completed them, providing a wealth of demographic information about themselves. Crucially, the vast majority of these people (86 percent so far) actively opted in to enable cookie tracking for future visits to the site so that content recommendations could be made based on their preferences.
This means that we're also able to build up a very accurate behavioural profile too. Once the sample size is sufficient, the technology then uses algorithms to profile our audience according to 13 main life categories, within which there are 120 audience groups, encompassing different needs, interests, taste and intent.
The early results at targeting ad campaigns based on this rich audience data are really compelling. In a recent example - using Visual DNA targeting - we delivered an average click through rate (CTR) of 2.36 percent for a standard ad creative for Panasonic's Lumix TZ10 camera, up 76 percent on the campaign average CTR (run across 45 sites).