With changing models, buying has become increasingly complex. Allocation strategies must be constantly redeveloped based on ever-changing consumer patterns and media offerings. To simplify the process, look for publishers who can provide multiple offerings under one roof.
Ask about duplication of audience among techniques. Keep an eye on the overall reach they can provide against your target, relative to the size of your market. Find out what research and insights will come along with increased spends to a single vendor. Many publishers now offer these layers and can provide you with the help you need to build models for your product in their environment.
Today, Sunday morning is no longer a mad rush to check out the coupons for my dad. He manages everything online.
It's striking to think that anything about online has become traditional. Using techniques already tried and tested offline -- contextual-based buying -- marketers have built a traditional model for reaching their consumers. Contextual buying has three huge benefits. First, it allows you to associate your brand with a media brand that is valued by your audience. Next, it ensures (with some stomach churning exceptions) that you are reaching people who care about your product's category. Finally, it can ensure that your brand is seen as a serious option because you are running right alongside your competition in context.
The major downside is that your consumer may be so enthralled with the content or your competitor's ads that you get lost. That is why many successful contextual marketers choose one major site to develop unique creative ownership opportunities, like sponsorships or content integrations, to get the benefits of contextual placement while making sure their brand stands out.
Let's look at the case of a new mainstream video game launch. According to the Entertainment Software Association, 69 percent of American heads of household play computer and video games.
The largest publisher of game info online is IGN.com, which reaches about 24 percent of all online gamers. Even if you bought a contextual sponsorship on every page of the best website in the category, you would miss three-fourths of the people who are interested in games. If you expand your plan and take massive sponsorships of the top three sites that reach gamers (IGN.com, gamespot.com and AOL Games), you can reach about 42 percent of all people online who visit game information. In order to reach all the people who visit game information, you lose the ability to do sponsorships on every page. But with some creative rich media and a big enough budget, you can add massive reach against your target. For example, by adding Advertising.com's Games channel to the plan above, you would now reach 96 percent of all people who read gaming content online.
This layered approach definitely reaches almost all the gamers online. However, it doesn't do anything about the people who buy games but don't visit gaming websites.
Demographic buying has also been effective online thus far and is similarly based on successful offline buying models. The main benefit of demographic targeting is that is allows you to reach people who are similar to your consumers and who may like your product even if they have not yet shown an interest (we call this prospecting).
When ads are shown outside of context, they also have the benefit of not having to compete for attention with competitor's ads. The major downside to this type of planning is that it can miss people who don't fit the profile and waste dollars on those who have no interest. Let's see how this works in our example.
There are 44.6 million people online who visit gaming information websites. There are 115 million households, according to the last census. Sixty-nine percent would be 79 million game playing heads of household. That means that if half the people who visited a gaming information website were a head of household, and you could reach all the people who visited gaming information websites, you'd still only reach 28 percent of game playing heads of household. While this isn't an exact science, it does show us that relying only on contextual placements won't get us all the reach needed against our audience.
Our video game maker knows that many of the people who have bought games in the past have been 18-34-year-olds. There are 51.3 million people online in the 18-34 demographic. If you want to reach as many of them as possible, and even if you run ads with a company that has the highest reach of any ad-supported entity, it's still likely that with a pure mass reach buy only about one in three of your ads will actually be shown to someone who is 18-34, unless you add additional targeting.
You could also run on sites that have a high composition of unique users who are in your target demographic, such as Rediff.com, the outdoor network, or Self.com. But none of these sites has an audience larger than 2 million. Even if you bought every site with an audience composed of at least 60 percent or more of your target of 18-34-year-olds, you'd still only reach 5 million people or a tenth of your 18-34-year-olds. That's a nice addition to your contextual buy, but it's not going to sell enough games for you as a technique alone. Interestingly, none of the top contextual sites overlaps with the top demographic sites. That leads us to believe the target is more complex than either of these methods alone.
How can you then find the other prospects for this video game, knowing that choosing sites based on contextual or demographic clues are not enough? Behavioral targeting now allows you to develop models of audiences who share similar characteristics, often multiple characteristics to your target audience. The main benefit of using this method is you can build large audience pools that are not constrained by absolutes, such as visiting content or being in a demographic, but that encompass more people who are good consumers. This is also a good technique because it allows you to reach consumers in a quieter context without the competition of other advertisers in your market.
Behavioral has another benefit as well. Insights from behavioral reporting can often help provide further information about the target consumer. As an example of a relevant behavioral segment, Tacoda offers a segment of people called "Electronics Shoppers." This audience is sizable -- 31.5 million people. They are more than twice as likely than the average internet user to visit mass market video game sites such as for GuitarHero.com. Most importantly, they spend money on video games, and they have a comScore Buying Power Index of 186. This number is significantly higher than the average internet user. They also buy mobile phones, music videos and sports equipment at high rates.
About a third of this audience is in the 18-34-year-old range, and while many fall outside that, the fact that they are repeat consumers of electronics identifies them as good prospects.
This audience also frequents social network sites such as Facebook and MySpace and is likely to spread the word about new electronics purchases. Knowing that this audience is always shopping for the latest must-have gadget, the video game maker can advertise to a group that may be more inclined to run out and get the game when it's released, increasing immediate sales rankings. Tacoda's segment is just an example of the kind of audiences behavioral targeting can deliver at scale.
As the examples I've described reveal, finding a target consumer requires a layered approach to get the best of each type of media planning strategy. In the case of our video game maker, a strong plan might look like this:
Strategy -- share of budget -- rationale
- Integrated sponsorship in a contextual gaming area(s): 30 percent -- serves as centerpiece of a campaign and allows unique "breakout" positioning for new launch but only reaches a small portion of audience. High cost per unique reached but high impact.
- Contextual ad network: 30 percent -- reaches almost everyone the sponsorship will miss who is interested in gaming. Lower cost per unique with massive scale.
- Behavioral ad network: 30 percent -- finds people with high gaming purchase behaviors based on key indicators of interest and provides consumer insights. Price per unique is middle of the road but delivers massive scale with accuracy.
- Mass reach program with added demographic targeting filters and smaller demo focused sites: 10 percent -- a lower cost way to find similar people but interest is uncertain.
The percentages will certainly vary by client and category, but approaching the planning process as a layered strategy with a full understanding of the benefits and downsides of each approach makes for a stronger plan. Allocating budget based on scale ensures dollars aren't spent delivering too high frequencies to small audiences who can't move significant product off the store shelves.