MarketingExperiments Blog: Research-driven optimization, testing, and marketing ideas

Twenty four conversations, countless emails and three-and-a-half Red Bulls later, I walked away from my last coaching clinic session at MarketingSherpa Email Summit 2013.

I realized a lot of the questions I was asked were deeper than:

• Which subject line?
• What should I track?
• Long copy or short?

Instead, at the root of many questions was a thirst for advice on strategic thinking and test planning.

A common problem I see among marketers is  a lack of sound strategy behind testing. We are asking the wrong questions. We’re asking, “What headline should we test?” when we need to begin by asking, “Why is the current headline underperforming?” We need to ask “Why?” before “What?”

As an optimization manager, one of my responsibilities is guiding my coworkers through planning an effective test series for our Research Partners. Each time I go through this exercise, there is a thought process I follow, which is what today’s MarketingExperiments blog post will teach.

But before we begin, I want to emphasize the most important point of this post – the reason I follow this process. If you leave this page with nothing else, please remember:

We test solutions to problems, not ideas.

Okay, now we can get down to the nitty-gritty. Let’s talk about the thought process you should follow to craft a strategy-centered test.

STEP #1:  STATE YOUR GOAL

Start by asking yourself, “What am I trying to accomplish? What is the objective of this test?”

This will lay the foundation for your test, and you will need to continuously refer to your goal. It helps me to write the goal on the whiteboard to remind everyone what we are working towards. This way, we all stay focused.

An example of your goal could be to:

Increase the average order value of customer transactions.

STEP #2: IDENTIFY THE PROBLEM – The “Why”

Now that you have identified your goal, it’s time to start thinking about how to achieve that goal. But before you can craft a successful solution, you need to understand the problem. Ask yourself, “Why?”

If your goal is to increase average order value, you may begin by asking:

Why are users only spending an average of $50 on my site?

Once you have asked “Why?” you should then form your hypothesis by formulating possible answers to your question – the “Because.”

Users are only spending an average of $50 because:

     A. We place the most emphasis on the product that costs $50.

     B. The only product that is relevant to our customers is the one that costs $50.

     C. They are unaware of the extra benefits of our more expensive products.

As you can see, you can quickly identify multiple possible problems. A trap many people fall into at this point is trying to solve all of these problems at once. This will put you on the fast track to failure with no tangible learnings from your test. Choose one problem to solve at a time.

Sometimes, the biggest problem may not be feasibly solved within your project scope (possibly Problem B). You must choose the problem to solve by weighing the benefits of solving the problem with the costs of testing and implementing the solution.

Let’s move forward with Problem A – We place most emphasis on the $50 product.

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A thought for future Web clinics:

There are millions of small businesses like mine. (Think small and local: your dentist, dry cleaner, pizza delivery). We are, in the grand picture, very small. My website generates, on average, 400 visitors in a month. (That’s around 14 a day. It works for me.) 

We run tests and split tests all the time, but it is hard to draw any real conclusion for what is working and what is not working with really small amounts of data. 

Is there something small business can do to better interpret small amounts of data? Thanks for your help and insight.

– Chris

Thanks for the question, Chris. After having a mini-brainstorm session with one of our data analysts, Anuj Shrestha, I’ve written up some tips for dealing with a small sample size:

Read more…

You’ve finally set up tracking on your site and have gathered weeks of information. You are now staring at your data saying, “Now what?”

Objectively interpreting your data can be extremely overwhelming and very difficult to do correctly … but it is essential.

The only thing worse than having no insights is having incorrect insights. The latter can be extremely costly to your business.

Use these six simple steps to help you effectively and correctly interpret your data.

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You spent years creating a valuable email list that gets Kim Johnson to opt in. Then, you craft an amazing email that inspires Kim Johnson to click to the landing page, where your marketing prowess is again on display, and Kim Johnson adds your product to her cart. And then… And then… Nothing. But why? And, what can you do to avoid this scenario as much as possible?

Well, at least you’re not alone – 88% of consumers have abandoned an online shopping cart without completing their transaction, according to a Forrester study. While you cannot eliminate cart abandonment, and many factors are out of your control (some customers just weren’t ready to purchase), you do have the ability to reduce abandonment.

 If you want to reduce your shopping cart abandonment rates, follow these seven simple steps:

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