Below is live coverage of the Paid Search Testing And Reporting panel from the SMX West 2011 conference. This coverage is provided by Keri Morgret of Strike Models.
Disclaimer: The coverage is brought to you in real time, using a custom live blogging tool. Feel free to ask questions or leave comments for inclusion into the live coverage. During the live event, live notes will auto-scroll with newest entries at top. After the session is complete the archive version will have the oldest entries at the top. We ask you to please excuse any typos, as these are live notes.
Craig Danuloff starts us off.
Are we testing, or just "giving it a try"?
Paid search really should be a test-driven process, but it rarely is. Reasons: it's really difficult to do.
How is testing different from trying?
Testing benefits from a strategy and a management framework. Need to be able to repeat the experiment.
Testing assumes a goal and a hypothesis.
Testing requires a controlled experiment, valid statistics, and a consulsion and resulting action.
It's also hard when you've got a lot of people in making changes, not everyone makes the same types of changes, so it's really hard to have a controlled experiment.
Sometimes you have a hard time convincing a boss or the organization in general that you should turn off certain keywords. He jokes about geo-targeting for only boss' house.
Strategic considerations in testing.
Are campaigns split by stage in buying cycle? Need to look beyond just the final conversion?
Are there success metrics beyond standard conversions?
Are there distinc values for distinct types of events?
Is there consideration of lifetime value?
Is there a method of tracking cross-channel and offline conversions?
Management Framework considerations:
Clear 'way you do things'? When do you choose to do something or make a change?
Agreed upon key metrics?
Rules for pausing keywords and ad copy?
eBook is available, and printed at their booth.
Control over variables.
Impact of text ad copy change on keywords?
Impact of bid or position changes on text ad copy?
Impact of impression share on keyword or ad copy?
Impact of quality score changes on bid or ad position?
Impact of AvgCPC against MaxCPC (% of MaxCPC taken)
Don't forget about external variables. If it's the end of the month and a competitor runs out of money and stops advertising, it's nothing you necessarily did that resulted in going up a couple of positions.
Tools to manage test? (things he really wished existed that would help this!!)
Lock options/elements around control?
Report if bid or ad copy has changed during test period?
Report if keywords added to ad group during ad copy test?
Report if position changed (due to competition) during bid test?
Verify significance of any change or comparision?
Goal: Is it attracting the right people?
What's the Goal?
Clicks start coming. What do you look at?
- Quality of queries -- are the right people coming?
- Queries tell what the people are thinking and what Google is thinking.
- Are those the people you wanted?
- Does Google have your meaning right?
- If not: rethink keyword or negatives or match type.
What Does the Quality Score Say?
In brief:
Over 7, great job.
Equal to 7, good job.
Less than 7, this keyword may not be for you.
Does the keyword work for you?
Consider key metrics
Decide if you should be advertising on this keyword
Act: kill it, work harder, or make modifications
Topic: what is a good control experiment, main requirements, how to make test successful.
1) Implement a valid testing procedure
Identify market and account factors that potentially affect the test.
- There are things you don't have control over, like seasonality, competition, consumer behavior, algo updates, etc.
- Identify account factors (internal factors). Your budgets, editorial changes, bid management, targeting settings, etc.
Anticipate Market Factors
The external factors from above -- try to make predictions about them, look at last year, etc.
Again, what Craig said. Don't make multiple changes at the same time.
One client had only phrase and exact match. Agency wanted to try broad match. To help control, they did a broad match campaign, and did negative match for phrase match keywords.
When evaluating a test, take into account what you expected (anticipating market factors), not what happened last week.
Use statistical laws to determine whether the standard deviation is statistically significant.
He shows how to use the chi square test in excel.
Since you'll need a lot of stats, run the tests on high traffic keywords.
Focus on the CTR, or the conversion rate, or both: Conversions/Impressions.
PR agency hypothese: client is wrong.
Agency hypothesis: we don't know, just want to run the test.
Reduced the number of age groups.
Reduced from 42 individual ages to five decade buckets.
Reduced number of cells considerably.
Keep creative constant and standardized.
Used CPM bidding to ensure equal distribution.
Artist, age, city, gender targeting on ad level.
Separated individual ages within ad structure but categorically tagged w/in system.
Set significance threshold for impressions.
No matter what the city or artist, CTR goes up with age.
Most acts skew male. Donny & Marie skew female, George Wallace closer to gender-neutral.
Target travel packages to older temo
Take picture of 30 something couple in bed off website.
If looking to get 300something travelers, get lively looking folks in their 40s, maybe there will be perimeter effect on people in 30s.
Incorporate learning in other media and marketing efforts
Focus acquisition efforts on highest responding groups
Now that you know the relative response rates by demo, start message testing to find optimal language for each bucket -- speak to them in the right way.
So many different variables! You want to test them all, but you really need to focus on what you can test, what's feasible, what brings customer value.
Biggest challenge getting internal buyin
- Who cares about testing?
- Is there internal buy in/ From what level?
- Is testing a priority?
- Are there dedicated resources?
You need funding, you need cooperative IT department, etc.
What is the culture of your company? Is it comfortable with wild changes, or very conservative?
Qualitative data:
- why do customers come to your site?
- What influences customers to make a purchase? What matters to them?
- What type of customers come? What motivates them to buy? what are their goals?
Purchasers don't use search, just got straight to the site.
- Make their jobs easier
- Make them more efficient
- Help them reach their goals
- Make testing and optimization part of their job.
Customer/business benefit: reach and engage more customers.
Different results for different regions. Now they're only going to focus on translations for regions that had good results.
Education to gain top down support
Engage resources: communicate and attribute results
Establishing and maintaining a rhythm: get tests out the door, start with tests that matter internally and externally.