The Opportunity Cost of Targeting to Death: Part I of IV - Steve Bookbinder- Digital Media Training

Are you an over-targeter? Do you find that you shop endlessly for just the right target –audience profile and content and the both together - only to find that no one can hit your targeted impression goals on quality content? Publishers and networks call this targeting to death. A horrible way to go. Often the publisher misses the goal for the first 3 weeks of the campaign month and then a network comes in for a scaled AND targeted BIG week 4. Was this really necessary? More importantly, is it in the advertiser's best interest?

One of the best things about digital advertising is the ability to target. Apart from contextually targeting users on relevant content, we can reach any demographic through behavioral targeting and past shoppers with retargeting. Let's not leave out geo, day-part as well as targeting by OS, device, browser and even Geo-dem. There are 62 pieces of information that can be known about each user. There are many PC operating systems that we can target and 150 mobile ones. There are more than 30 tablets even if you only heard of 1 or 2 of them. Given that, how valuable is targeting too tightly in advance of testing? What are we really trying to accomplish – reach a particular target? Or, achieve a particular (and valuable) marketing effect on either branding or performance? That said, over-targeting may put too much focus on the front end of the process and encourage guessing. End result: buyers wanting no-waste in reaching a very specific person --even if there are only 7 of those people and it'd be simpler to call them to let them know you are targeting them for a marketing campaign.

Before locking in on a target, we should consider the opportunity-cost of too narrowly selecting a target …the right audience on exactly the right content…before testing a new campaign on a new site. Below are 4 things to consider before putting a specific demo target in the cross-hairs; this week we will focus on #1.

1. Grouping strategy

2. Referring traffic

3. Taxonomy

4. Cost of Scaling

Grouping Strategy – This has an impact on both paid search and display; the clearest way to understand grouping strategy is to start by envisioning a Paid Search campaign. On SERPs (search engine results pages) there is a war going on as marketers fight, not so much for the top of the page but for overall brand supremacy.

All brands know that each paid position has a predictable CTR (click through rate). Their bid cost, in general, will be higher for top positions but can be lowered through factors like QS (quality score). So, improving QS is a never ending practice. Apart from position and cost-per-click for that position, the marketer has to decide which matching strategy to apply to each Keyword: Broad Match, Phrase Match or Exact Match. By the way, as in all advertising, the more targeted the more expensive but the smaller the inventory. Marketers test each key word with each matching strategy at each position to learn which combination converts most efficiently as well as which one scales best. Why not simply always bid for positions # 1-3? Because the possible inventory usually exceeds the marketer's budget; the game is about maximizing the impact of their budget. It's about optimizing and scaling. It's possible, given the cost to that marketer for being in those top positions, they will not have enough budget to cover all of the desired hours of the day as well as additional keywords if they use up all of their funds against the most coveted (and expensive) key words, which their peers are also competing for. But the trickiest part of the planning is the grouping of Keyword>Matching Strategy>Creative>Landing Page>Conversion (any desired action or engagement). Each part of the grouping strategy has to be constantly tested to ensure optimal optimization. The first part of the group is really before Keyword – what is the intention of a user who searches with that keyword? Can a different intention be inferred from users using that same keyword across various search engines? Should we show a person with a different intention a differently worded ad? Use a different matching strategy? Bring them to a different landing page?

Now, let's consider how grouping impacts display. We think we are simplifying the game by pre-determining the exact content and demo target and now all we have to do is worry about which creative to serve them. But, let's look at the entire group: The user's Intention>Choice of Creative>Served on a particular device>at that time> with that geo-target>landing page>conversion path to desired action. With all of those moving parts, how sure can we be that the correct target is M 34—39; HHI over $150k, interested in finance, etc…with the ad served when the content is relevant (contextual targeting) or irrelevant (BT)? Even if we worked out the perfect grouping strategy recipe on a different site or network can we be so sure it'd convert that way again on a different platform we are testing? If we guess wrong on the target or guess wrong on being too tightly targeted we miss learning what is just outside of our bulls-eye. Maybe the next outer ring would convert better? Or have a higher AOV (average order value) or higher LTV (lifetime value)?

Maybe we should spend more time creating the right landing pages and less time guessing the perfect target? Think about that the next time you are tempted to over-target when testing a new campaign or a new site or network.

Next time, we will look at #2 – how Referring Traffic data may be more important than over-targeting.

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