Web Analytics and Targeting: A Quick Blogviation
Targeting refers to the process of identifying characteristics of a segment so that relevant content may be matched to it and delivered at a time when the segment is most open to the message. The idea is the right content to the right visitor at the right time (optimally in real time).
For example, you may visit a site, and see some type of ad unit calling out at you to “meet singles in <insert_your_city>.” When browsing real estate you may see ad units for realtors and mortgage companies. After entering a keyword such as “car prices” and clickingthrough the SERP, you may see an ad for a local car dealer. That’s targeting in a nutshell. It’s simple:
- Visitor X has these attributes.
- We have content that we think will appeal to Vistor X’s attributes.
- Let’s show that content.
While targeting has helped to increase ad clickthrough rates, it’s far from an ideal science. Current methods for targeting have inefficiencies. What if Visitor X just bought a new car after his recent marriage? Unless the targeting engine is made aware of the visitor’s current state, the targeting may be off and not yield desired results.
Even with limitations around “current awareness” targeting is perceived in the Internet industry as a crucial activity for maximizing the effectiveness of advertising and content. Targeting is the next stage after A/B and multivariate testing. Once you determine the preference of segments based on testing, you identify content to target.
In new media, targeting is something associated with paid search campaigning, ad serving, and content optimization. It’s not uncommon for targeting activities to be based on:
- Category and sub-category. Conceptual constructs like “categories” of topics on a media web site or products on an ecommerce site can be targeted to include certain types of ads or messages. The notion of a “zone” fits in here as well. The idea is that if visitors are browsing in your category for “hardware floors” you could offer them an ad or content specific to “flooring installation services.”
- Geography. Country, region, city, state, DMA are all targetable constructs. You may choose target people surfing from 02141 (Cambridge, MA) an ad for pre-sale Red Sox tix or content about Mike Lowell’s recent contract.
- Browsing environment such as the connection speed, type of browser, operating system, user software, domain, and ISP. An ad network serves an ad for Verizon DSL to a modem-based surfer by detecting the visitor’s browsing environment.
- Time. The idea of only showing content during specific periods of time is called “parting.” Common types include day-parting and season-parting. For example, a B2B site only choosing to show ads for a particular manufacturers product during business hours – the site’s busiest time of day – would be an example of day parting.
- Keyword. There are many different types of keyword targeting. Google does fantastic things with targeting ads based on the keywords in queries. Content Management Systems can target content based on on-site search keywords or referring keywords. “Keywords” may be associated as metadata with site sections or pages, similar to a zone or a category targeting on an ad server. Once a page is associated with “keyword” metadata, you can tell your server to target that keyword (and all pages where it exists as metadata). If two categories each with different content share a targetable keyword, I can target ads across both categories to pages tagged with that specific keyword.
- Language. When a language is set, you can target ads to visitors with that setting. Think Google. Keep in mind that when you target by language, the creative copy is not translated.
- Demographics. If the ad server is aware of a segment’s demographics, such as age, gender, income, title, purchasing power, and so on, an ad can be targeted on that basis. Sometimes this is called “profile targeting.”
- Context. Think of Google AdSense and how it matches ads based on the semantics in site content. Now you understand content targeting based on context.
- Profile. Targeting is possible based on conclusions drawn and rules created from the known attributes (such as purchasing propensity) about and individual or segment.
Enter one of the holy grails of online advertising and new media: “behavioral targeting” – an advanced form of targeting. Behavioral targeting refers to the process in which content is shown to a visitor based on the web sites they visit (or have visited) and the actions they take on those sites.
Behavioral targeting involves:
- Knowing where a visitor “comes from” and what they’ve done in the past.
- Determining the context of the visitor on the site.
- Detecting the visitor’s current behavior.
- Serving relevant content and/or ads matched to the behavior.
By understanding the visitor’s past history, current state, and most recent behavior the marketer can target content in order to influence some point in the customer buying cycle- often at the stages of awareness and consideration.
So where does web analytics come in? You would think web analytics data from “web analytics” technology would provide the seed data for enabling “targeting.” It can be but in most cases, targeting is a function provided by the ad server or network or another technology called the “behavioral targeting platform,” not the analytics tool… the data does not come directly from the web analytics tool. I’d love to hear how well (or if at all) Omniture TouchClarity is integrated with Omniture Discover or other offerings.
In order to make web analytics data useful for targeting (if you can at all), you will need to use your web analytics data to:
- Define segments to target (hard to export from web analytics tools)
- Feed those segments and associated behavioral data to another tool (achievable if you own your data and run a tool in-house. Harder and more costly if not).
- Report on segment performance after targeting (that requires employing the right people and enabling them with the right tools)..
- Analyze segment performance after targeting (again employ the right people and enable them with the appropriate tools and resources).
While I’ve only covered a very little bit about “targeting” and even less about “behavioral targeting” in the context of web analytics, I hope that my simple description of current methods for targeting and some thinking about “what is BT” will help you understand the emerging ecosystem in which analytics tool are interoperating now and will interoperate in the future.
SuperJogos - Todos os jogos da internet » Web Analytics and Targeting: A Quick Blogivation added the following ...
[…] technobiosphere wrote an interesting post today!.Here’s a quick excerpt Targeting refers to the process of identifying characteristics of a segment so that relevant content may be matched to it and delivered at a time when the segment is most open to the message. The idea is the right content to the right visitor at the right time (optimally in real time). For example, you may visit a site, and see some type of ad unit calling out at you for a “Free Test Drive at ” or “Meet Singles in .” That’s target […]
Michael Whitaker added the following ...
Hi Judah;
Great post. If I understand you correctly, targeting is essentially a technology found in an ad server that attempts to match up visitors with the “right” content or destination. I can see how ad serving platforms would want to increase click-through rates or conversions on behalf of publishers and advertisers, but what if your site is not ad-supported, such as is the case with most e-commerce sites?
On an e-commerce site, I guess instead of showing ads, you could show related products or coupons based on past browsing behavior or referrer, but I can only see such targeting as having any measurable impact on nothing but the biggest sites. Not that there is anything wrong with that, I’d just like to get your opinion whether targeting is at all applicable to the “long tail” of websites.
Would you do targeting on your blog for example?
Many thanks,
Michael
Steve added the following ...
“Quick”???? I’d hate to see Long! 
Lot to digest in this one Judah! Yet another excellent post.
Cheers!
- Steve
Judah added the following ...
Steve: LOL! Thanks for the nice words! I appreciate the positive feedback.
Michael: Yes, you got it. Depending on the ad server (or the ad network’s ad server), targeting functions will vary. But it also possible to use other technologies to target content, whether a CMS, MVT system, site optimization technology, or a homegrown/proprietary technology.
One of the best examples of targeting on an ecommerce site–outside of ad servers and not exclusive to “ads”–is Amazon’s “personalized recommendations.” Targeting by behavior, context, and profile - an impressive implementation indeed.
In terms of “long tail” I consider a site that is in the “long tail” as one that has a product mix where many low demand items, when considered collectively, contribute more to revenue and margins than the smaller number of high-demand items sold. Once again Amazon illustrates this concept nicely.
In a sense targeting (and especially behavorial targeting) is the way ad inventory is made “long tail” by ad networks or publishers in the way I describe above… selling lower numbers of targeted ads at a higher cost, which when considered collectively make you more $$$$ than selling all “punch the monkey” banners.
I don’t necessarily consider a site “long tail” by traffic volume only, but I understand that thinking especially in analytics given the statistical origins of the term. And it makes sense in context too.
So I think what you are asking is if I consider targeting to be useful for sites that don’t have high traffic volume (such as my blog which has gets about thousands of visits/month)? I would say “yes” with restraint.
For example, say I didn’t use Wordpress, I wouldn’t bake myself up or buy a whole content targeting and site optimization technology. What I would do is sprinkle a little AdSense or other contextual advertising technology and some targeted display ads (from an ad network) along with the normal text and affiliate links.
Thanks so much for your comment, question, and for reading my blog… which incidentally I don’t monetize at all!
Shahar Nechmad added the following ...
You nailed most of the points. Actually this is exactly what my startup is doing (we have a very unique new analytics solution).
There are a couple of really big challenges in making web analytics data “targeting ready”:
1. Speed - Ads should be delivered in a very fast manner otherwise you hurt the site experience. This means that you need to have all your profiles and data compiled and ready all the time. When we talk about analytics of big sites, we are talking about tera bytes of information that should be constantly analyzed.
2. Scale - In order to build a good profile of a user it’s not enough to just track him on one site. You should be able to get information about him from multiples sources. This basically requires your cookies to be set in a wide range of popular web sites
3. Easy integration - In order to get this wide scale, you need to let web sites integrate your platform in a very easy and fast way. This makes it hard to ask them to put multiple tag and categories on every page in their site.
4. Context - To build an accurate profile of a user you need to understand the context of his actions. A drastic example is when a user goes into a britney spears forum and writes how much he hates her. Without context he will actually start to get ads for her latest album
There are many other issues (I won’t even get into privacy…) that makes BT a very hard thing to nail, but no doubt that this is the holy grail of the industry
Judah added the following ...
Hello Shahar,
Speed is absolutely necessary. One thing we can’t forget either is the cost of the hardware and database licenses and so on to enable the scale and speed necessary to do BT.
As for scale, I’m not totally convinced that you need a third party cookie to do BT if you have enough in-house data to use.
Easy integration means a lot of things, and I whatever we think I’m thinking web services is part of it. As for “multiple tag categories on every page in their site”- that’s precisely why we see BT in the realm of ad servers… You need to tag the pages to serve the ads, and the tags have variables.
You bring up a very good point on Context.
Thank you for comments, and good luck with your new company!
Jeff C added the following ...
Wow Judah!
Very impressive insight and analysis. Can I pay you to help optimize my sight?
I sure hope your current employer is paying you handsomly.
Regards…
Iguanaz » Web Analytics and Targeting: A Quick Blogivation added the following ...
[…] Check it out! While looking through the blogosphere we stumbled on an interesting post today.Here’s a quick excerpt Targeting refers to the process of identifying characteristics of a segment so that relevant content may be matched to it and delivered at a time when the segment is most open to the message. The idea is the right content to the right visitor at the right time (optimally in real time). For example, you may visit a site, and see some type of ad unit calling out at you for a “Free Test Drive at ” or “Meet Singles in .” That’s target […]