How To Use Social Networks To Create Laser-Targeted B2B Advertising Campaigns

The bane of most search marketers’ existence is search query ambiguity. Is a user searching for [one night stand] interested in an illicit affair or a piece of antique oak furniture for his bedroom? Does the query [internet security] reflect the needs of a consumer fed up with viruses or a CIO looking for a $10 million enterprise solution?

John Battelle has called a search engine a “database of intentions,” but that database is often fuzzy, to say the least.

In many cases, it would be much easier for marketers to know who the user doing the search was, as opposed to for what they were searching. Take the two examples above: if you knew that the searcher was a 19-year-old college student whose favorite brands were [Axe deodorant] and [Bud Light], you could probably determine quite quickly whether either query was right for your advertising budget.

But, with the exception of the limited use cases of Google’s RLSA (retargeting lists for search ads), the ability to fuse demographic or behavioral intent with query data does not exist on search engines.

In the last few months, however, social networks – led by Facebook and LinkedIn – have rolled out targeting features that enable advertisers to get very close to answering the “who” question. Importantly, these tools work especially well for B2B marketers, simply because they enable advertisers to exclude consumers (or just include businesses).

While still in their infancy, these new targeting tools are opening up big B2B opportunities online. If you’ve been frustrated by too many double-entendre keywords in your SEM campaigns, social media could be a better use of marketing dollars.

LinkedIn: Using Endorsements, Groups & Demographics For Fun & Profit

With over 200 million users, the odds are pretty high that if you are trying to reach a business professional, you can probably find him or her on LinkedIn. When LinkedIn’s self-service advertising platform was originally launched, advertisers could only target based on a LinkedIn user’s self-identified data. I say only because even this data is quite robust. Fields include:

• Languages spoken (I put “Old French – 842-ca.1400” on my profile, but no one has targeted me in that yet)
• Company or type of company
• School(s) attended
• Seniority
• Gender
• Age
• Geography (down to a city)

LinkedIn then upped the ante by allowing advertisers to target users based on their LinkedIn group membership as well. Since many groups are narrowly focused around specific business issues and needs, targeting groups (in combination with demographics) is a great way to find users specifically looking for what you might be selling.

As example, I typed in [data warehouse] into the groups search box on LinkedIn and found more than 250 groups, some of which had over 20,000 members

Fable Technology :