Commentary

Breakout Session Notes -- Making Data Driven Decisions -- B2B

Please see this post for the background and disclaimer (although in this case I was the notetaker, so feel free to shoot me).

Dema Zlotin, Founder of Covario, led this roundtable discussion and outlined 3 key challenges B2B marketers face:

1. Multi-tiered distribution models -- the end sale does not always take place on the marketer's site so attribution is tough.

2. Latent purchase cycle -- the time from lead to close can be many months which makes it difficult to forecast, optimize, etc.

3. Competition with channel partners -- a marketer may be buying the same keywords as other partners and resellers of the product.

The group then offered up 3 additional challenges:

1. B2B audience searches differently -- Gord Hotchkiss shared Enquiro research that B2B searchers often repeat "landmark queries." And they are typically risk averse so emotion does not play a factor. They are very rational.

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2. Often times, a marketer has both B2B and B2C platforms -- leads to internal competition for keywords (eg, who owns the keyword "notebook computers")

3. In B2B there are often multiple decision makers -- how do you connect all the dots?

Here are some of the solutions the group came up with:

1. Attribution -- use unique 800#'s and add tracking to CRM tools to pass variables all the way through from search to click to lead to close.

2. Latency -- if your avg. sales cycle is 18 months calculate net present value and back into milestones at 12 months, 6 months, and 3 months based on the phases of the cycle and optimize accordingly.

3. Multiple decision makers and Latency -- track "micro-conversions" like white paper downloads, flash vdeo vidws, repeat visits, etc. and build an enagement scoring system to optimize from.

4. Unique B2B search audience and Multiple decision makers -- run qualitative research on your site to understand the intent of visitors. Tools like 4Qs from IPerceptions may be helpful.

5. Internal competition - use split landing pages to let visitors self-select between B2B and B2C. At the end of the day, let the data decide who should own the keyword.

6. Unique B2B search audience -- mine onsite chat logs, search queries as well as notes in CRM from customer service reps to better understand the language these folks are using and what the pain points are. Then apply those learnings to your keyword list, copy, landing page selection, etc.

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