Attention Retailers: 4 Advanced Moves to Effective Paid Search Marketing Nirvana

Photo Credit: Photo date: 1968 “2001: A Space Odyssey,” MGM 1968.
Keir Dullea Photo by MPTV - © MPTV - Image courtesy mptvimages.com

As Black Friday holiday shopping approaches, I thought I’d share my 4 Advanced Moves to Effective Paid Search Marketing Nirvana.  Is this eCommerce optimization framework you would use (read the list first)?  What resonates? Is search marketing no longer on your radar?  And, what if you’re not a retailer?  I’d love to hear your thoughts on what’s worked for you and well, what went in the trash.  Please post comments below.

Here we go….

Number 1.

Build out a localized Black Friday PPC Campaign that can be deployed around territories, stores or products that leverages insights from your consumer insights team.

a. Connect with your Customer Insights and Merchandizing teams to leverage recommendations by Merchants and Retailers to identify new opportunities of BF09.

b. Review archived PPC results for previous Black Friday trends and brand marketing goals. What worked?

c. Build out segmented ad groups with day parting that focus on attracting customers and linking them to product purchase behaviors based on customer insights. Here’s one model to stimulate some segmentation of your own:

i. Bought on Black Friday from a source (circular, brochure, catalog, direct mail piece)
ii. Bought on Black Friday but not from a particular source
iii. Didn’t buy on Black Friday but made a purchase during the holiday season.

d. Get your IT team on board as soon as possible and share your plan with your ad agency partner. Your new keywords are likely to guide site architecture for new pages so get your requests in early to the IT team. In fact, think of IT team as your part of your Ad Operation team. If IT is not informed your not as likely to achieve or sustain your desired campaign goals. Get their feedback on retargeting and display ad opportunities to boost profit growth.

e. Forecast maximum allowable investments (MAI’s) down to the keyword and ad group level.

Number 2.

Ensure the campaign and ad groups support the generation of high quality scores. You’re going to have one shot so make it count. Refine you keyword pool and bids, have a copy testing methodology in place with position targets across all ad groups on Google Adwords combined with deactivation of poor performing keyword phrases and ad groups. Have you established a deactivation threshold? Get to work. Connect with analytics team. Look for trends in ad groups and across keywords to find your ideal deactivation threshold. And, be sure every member of team is aware of that number and that it has been plugged into your optimization tool.

a. Use Omniture’s SearchCenter or another ad optimization tool. If you’re using SearchCenter, Leverage Born on Dating so that you can easily track performance of new ad groups.

b. I like to start with ad element testing then land pages. Titles, descriptions and URL would be tested (A/B split approach) to build 4 to 6 ad units for testing per ad group. Then introducing test to uncover winning titles and descriptions.

c. Start with phase and exact matching options and then scale up using broad matching and contextual networks.

d. If going mobile, only select iPhone platform since those uses out search other mobile devices users by approximately 4 :1.

e. Utilize insights from four customer tiers to fine tune messaging.

f. Map Keyword Assists (non-converting keywords that lead to a desired action) to converting terms and flow KA’s back in the ad copy as new creative tests. Did it work? Test hypothesis on why the Control may be winning.

g. Landing page testing will also be incorporated to assess the use of single terms on specific product pages vs. a single term and a category page as a method for achieving higher conversion rates. If you’re launching a new brand, drive people to product pages with pricing if pricing is your competitive advantage or to the homepage if Operations or Services are at the core of your organizations excellence.

h. Using testing as a syndication of best knowledge for ongoing testing on other search engines to expand reach, sales and profit. Learn in small chunks then plant a lot of seeds to expand your growth. Remember engines have different types of users, interests and matching options. Don’t forget: Search marketing campaign results on one engine are not interchangeable with another.

Number 3.

Create higher value performance metrics that will be used to drive campaign decisions now and in the future.

a. Utilize the COGS Vista rule within SearchCenter. SiteCatalyst allows you to upload a list of product IDs and unit costs so that SiteCatalyst can apply the unit costs in a custom event automatically on each purchase. I know I’m making a bunch of assumptions that your using a paid vs. free product. I love free but you get what you pay.
b. The objective is to calculate gross profit using the COGS Vista rule.
c. Combine the COGS Vista rule with an EBITA (earning before the deduction of interest, tax and amortization expenses). This is how Vintage Bath & Tub are cleaning up!
d. So what happens when you optimize around revenue or profit? In many cases, the sales volume is going to go down initially. Therefore, be sure to share the strategic implications with Sales, Finance and other executives. I had this experience with a retail client. They wanted to improve their PPC performance. I took that to mean ROI and even forecasted a 3x increase in ROI performance (I came in a 2.6x – not bad). When the campaign was fully implemented the ROI levels increased to 4x at one point with 18% decline in order volume. Let me put it this way: the sales team was not happy.

Number 4.

Begin to Close the Loop on Untracked Revenue Gaps. If you have a physical location, the hypothesis to explore is whether individuals who live within 10 to 12 miles of one of your stores are likely to respond to sales promotions by exhibiting Urgent Printer Behavior (UPB). Urgent Printer Behavior is when a customer goes to your site for an immediate product or service need and adds a desired product/service to a shopping cart so that they can see the price. (Note: This happens all the time in the real estate industry.  You see a house you like a printout pages of the listing.) The customer then prints the page to take to a local store to get the product and the price-matching price for that product. How do you close the gap for your organization? Monitor dialogs across message boards, tweets, and blog posts and comments to uncover unpredictable user behavior and insights. How does your marketing organization fulfill the “now” need and capture data and insights that can be shared across your entire organization? The idea is to look at your organization form the standpoint of Search Engine Marketing Readiness from how analysts are pulling in insights into dashboards to when the search team is brought in to do their optimization magic. In many cases, search optimization is a silo. Start planning for 2010, you may just realize “My God! It’s full of stars!”

Note: Quote from Keir Dullea who played Dave Bowman in 2010 A Space Odyssey.

PostRank Launches Discovery Engine

PostRank is launching a Discovery Engine to support dialog monitoring.  The announcement is not earthshaking news but the announcement is an interesting industry twist with individual collaboration vendors spinning out their own dialog “discovery” tools.  Finding dialogs is one thing but finding business value is another.

As Discovery Engines evolve from simple pointers that identify the location of a dialog to a reference tool that can be used to help initiate new conversations among individuals with shared interest you have to wonder about how marketing will evolve.  These tools could lead to content generators of segmented page content that shed light on the deep web of unranked and unindexed user generated information.

I think PostRank’s announcement also points to the beginning of the end for big monitoring vendors.  How does the army of PostRank announcements impact big dialog monitoring players like SM2’s Techrigy?  Who knows but I’m interested to see how PopUrls.com and Alltop.com (Guy Kawasaki’s aggregation platform #guykawaski) move from conversation clearinghouses that aggregate dialogs to businesses that become audience engagement generators.

Very exciting stuff… Here’s the announcement that has me think:

From:     info@aiderss.com
Subject:     Discover and share great blogs with PostRank!
Date:     April 7, 2009 2:19:57 PM EDT
To:     todd(at)audiencemachine(dot)com
Reply-To:     beta@aiderss.com

Hello, we have some exciting news about PostRank, and want to share it with all of our community!

We’re launching the PostRank Discovery engine, which enables everyone to:

- discover the most timely, relevant, and engaging content online
- search and segment content by specific topic areas and interesting and influential publishers
- create, share, and subscribe to the the best curated and auto-updated reading lists.

You already have an account on postrank.com, so you’re ready to get started. Head over to the PostRank website (http://postrank.com/register) and create a profile. You can use your existing login information — email and password or OpenID.

Check out these topic lists created by people in the know:

Marketing by Joe Thornley: http://beta.postrank.com/user/thornley/topic/marketing
Venture Capital by Jim Murphy: http://beta.postrank.com/user/jimmurphy/topic/vc
Ruby by Ilya Grigorik: http://beta.postrank.com/user/igrigorik/topic/ruby

And here are some of our most popular topics:

Moms: http://postrank.com/topic/Moms
Politics: http://postrank.com/topic/Politics
Technology: http://postrank.com/topic/Technology

Once you’ve created a profile, all the feeds in your account will be publicly viewable by default. You can make feeds private if you like. (That is, only you will be able to see your subscription to that feed, and only if you’re logged in to PostRank.com.) You can change your feed privacy settings on your account’s Subscriptions page once you’re logged in.

For more information on what PostRank Discovery is all about, check out the blog post: http://blog.postrank.com/2009/04/05/postrank-delivers-the-best-blog-discovery-engine/

And for a quick start overview: http://blog.postrank.com/introduction-to-postrank-discovery/

If you have any questions or problems, please let us know via:

- email: melanie@aiderss.com
- Twitter: http://twitter.com/aiderss)
- Get Satisfaction: http://getsatisfaction.com/aiderss

We hope you’ll love PostRank Discovery as much as we do!

The AideRSS Team

This email was sent to todd@audiencemachine.com.
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A Content Distribution Model

In May of 2006, I published a research paper with Osterman Research highlighting the challenges brands would face as they embarked on implementing word of mouth marketing campaigns.  The study took 6 months to implement and eventually grew to 54 pages of content.

My goal was to provide organizations interested in, or even intimidated by, word-of-mouth (WOM) campaigns with data and guidance designed to help them integrate this exciting strategy into their marketing and media plans.

The study is titled Perceptions, Practices & Ethics in Word of Mouth Marketing.  And, I’m making it available again.  Is it still relevant?  Well, from a planning standpoint I think the topics are still as relevant today as they were two years ago.

I also turned the release of the study into an example of how to support viral marketing pass along.  The study was downloaded over 150,000 from May 2006 to February 2009.

Here’s how we did it:

1. We started with no marketing budget and decided to use a free e-book framework to drive distribution.
2. We became members of communities to hear what was going on and to gain qualified participants for the survey. This platform also allowed us to announce to relevant communities when the study was available.
3. Created a database. We captured the email addresses, names, and company names of all survey participants. We also included email requests for the survey that were appended to the database. There are 217 records in the database for email requests.
4. We communicated. We thanked individuals for participating.  And, sent them a link to pick up the results.
5. We said something important. The study took 6 months from formulation to publishing and we focused on giving readers valuable and actionable information. The content publishing focus was on tips and techniques.
6. We focused on co-creation. This is an important step. We reached out to 45 industry experts and competitor firms in our industry ten days before we published and, asked them for their feedback and insight. 38 individuals responded, and 17 of those people provided lengthy comments and insight that enhanced the quality of the work and required us to rethink some of the conclusions and rationale. Personally, I’m still thrilled and humbled that competitor firms say that the work is incredibly valuable and comprehensive.
7. We recognized the contributions of those that contributed feedback.  And, even asked some individuals for reviews of the study that we published as Accolades.
8. We did a blogged press release. Having a blog press release really helped to drive distribution.
9. We created a counter so that we could track downloads.
10. We provided links to relevant publishers that cover the WOM industry.
11. We talked about the study at industry events.
12. We commented on comments to be part of the conversation.  Thanking people for reviews gave us more content to reference in the form of lists of people who were talking about the study.  This became blog post content.
13. We shared our success by publishing download counts.
14. We published snippets of content from the study with additional insight on our blog.
15. Once it was added on Wikipedia — we linked to it.  NOTE:  If you feel the study is worth adding back into the Wikipedia article for Word of Mouth or Word of Mouth Marketing, I hope you’ll add it as a resource.

In addition to the 150,000 downloads, I was interviewed for a New York Time article on social media and generated $1.685 million in new business.

TAGS:  Word of mouth, word of mouth marketing, wikipedia, Osterman Research, Audience Machine, content distribution, viral marketing,