Search Marketing Now 1/27/09 Webinar

I listened to this webinar to try to get an idea of where internet sales were over the holiday season, since we all already know how bad the national chain averages were.

1. Jeff Hackett
Showed % change in search traffic for retail sales
-Paid up 6.7%, 24.1%, 5%, 17.8% for apparel, books, electronics, home furnishings
-organic: 4.0%, -9.7%, -1%, -16%
-totals: 4.9%, 5.3%, .9%, ?%

online sales growth only 7% for 2008, 17% for 2007

online spending by consumer by income level
-under $50,000 hit hardest, -17%
-50k-99k: -10
100k+: 17%

fast growing segments
fitness: 16%
video games: 10%
consumer electronics: 3%
apparel: 2%
music, movies: -34%
jewelry: -24% (first time online beat store, but still bad)

google product search +162% from last year

Mike Deckman (
-remained strong in Q4 despite the usual lul due to holidays and housing recession

-Philippe Petit theory: sales survival
success isn’t an accident
(planned stunt walking cable between twin towers with success)
look at problems from distant perpective
short, broad goals
what matters most?
-need for good analytics
-know what the analytics mean and how to use them
-know what data is important
act only on what data shows (not opinion)
-know differences between revenue channels
economic factors
when do people want X?
good organics can make up for PPC
-what keywords generate income vs traffic
many clicks may not net very much profit
-anticipate problems and find solutions
know what is going on
example of research in dec, buy in jan
consistency pays off
negative keywords
savings in PPC
optimize data feeds
fix everything
promote most popular product over unpopular
-focus on what you can do, not what you cannot
-create a plan and stick to it
allow for change due to data

Chris Wine (sponsor)
-16% of holiday online sales were search driven
-spend more when more demand is expected
assuming more profits
raised bids
increased budgets
-effectiveness of coupons
-offline 3X utilization of coupons as online
-2008 “year of coupon”
-thanksgiving week 30% raise over baseline conversions
-promotional branding of site for seasons
-most people found to be reactive (lagged actions)
-margins go up, but conversions missed
would have been more had predictions been made
-dec 9 busiest day online for shopping
-Marin software
bids changed daily based on trends
daily for every keyword
compares conversions to searches
distributes money from competitive to less competitive to maximize revenue
looks to see when a keyword can stand on its own
based on conversion. 10% can, 1% cannot
collects data on keywords or uses existing data
-strategy that reflects traffic
-keyword attribution
how is a single product marketed?
brand? category?
-too many packages rely on redirects
-PPC agents will make suggestions to improve results

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