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Monday, March 24, 2008
Search Engine Strategies New York

Presented by Tim Ash, President, Site Tuners

What is Landing Page Optimization?

Online Marketing Activities

Acquisition–Get people to your site

Conversion–Persuade them to take desired action

Retention–Increase lifetime value of relationship

Conversion Rate -Percentage of visitors who take desired action

Landing Page Optimization -Improving conversion rate by testing website changes

Why should you care?

You have neglected your landing pages, and your conversion rate is too low, and it is costing you a lot of money.

The economics of conversion: Cost per Acquisition=Cost per Click/ Conversion Rate.

Who should design your site? Your boss, IT, Ad agency, webmaster, or marketing? None of the above! Your website visitors! Your site should be focused only on conversion!

Case Studies

Realage.com Conversion action-Completion of Real Age Test Registration, using Sitetuners Tuning engine. Test size 552, 960 unique recipes.

Results: 40% lift in conversion rate, $3,285,000 annual profit improvement.

Uniblue Registry Booster Conversion action-Free software download, extensive previous testing by client, tuning method Sitetuners Tuning Engine, test size 3,110,400 unique “recipes.” Results 24% increase in conversion, CR improved from 30.3% to 37.7%, $182,000 annual profit improvement.

Power Options Conversion actions-Free two week trial sign up, method A-B split testing, 3 unique “recipes.” Results 75% increase in post trial sales, and $200,000 annual profit increase.

Engine Ready an SEM Debt Negotiation Client, Conversion action-online form or phone lead, large scale PPC campaign, 192 unique recipes.

Results 51% increase in revenue per visitor, $48,000,000 annual revenue increase.

THE MATRIX

The Matrix = Roles x Tasks x AIDA Getting the right people, thru the right activities, in the right order.

Roles-Visitor classes who interact with the mission critical parts of your site.

Tasks- Specific activities that a visitor in a particular role wants to complete.

The AIDA sales funnel- Awareness Interest Desire Action AIDA

Common awareness problems: Banner ads, entry pop ups, cluttered homepages. Keys to creating awareness-stop screaming at your visitors, eliminate choices, unclutter what remains.

The rules of web awareness- if you can’t find something easily, it does not exist; if you emphasize too many items, all of them lose importance; any delay increases frustration.

The rules of web interest- understand who I am; understand what I am trying to do.

Typical Desire activities: Do you have what I want? Research, compare, get details, and customize.

Rules of web desire- make me feel appreciated, make me feel safe, and understand that I am in control.

Action stage considerations: Why should I get it from you?

Brand strength

Previous resource investment

The total solution

Risk reducers and credibility

Rules of Web action: Get out of my way, make it easy, and don’t surprise me!

Picking a tuning method!

How do you tune? Key considerations: size of test, and the need to consider variable interactions. Interactions are very important! The best setting for variable depends on its context. Maximize positive interactions and eliminate negative interactions!

Don’t ignore variable interactions! Interactions exist and can be very strong; ignoring them will lead to sub optimal results. A/B splits and multivariate/Taguchi testing assume that there are no interactions.

A-B Split Testing

Test one variable at a time, send equal traffic to all versions, and keep very simple to track and implement.

Multivariate Testing

AKA “design of experiments” and “Taguchi method” testing several variables at a time, and ignores variable interactions, as well a s tries to predict best setting for each variable.

Non-parametric tuning: proprietary math for Internet marketing, designed for large scale tests, which takes variable interactions into account.

Avoiding the pitfalls

Tuning pitfall #1 ignoring your baseline, always devotes some bandwidth to your current version, the baseline, and measure relative to the baseline, not absolute performance.

Tuning pitfall#2 not collections enough data, do not make decisions based on too little data, pick a confidence level, and wait to see which version is better



by: Shawna Seigel



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