Digital Marketing Insights

3 Steps to Getting Over Analysis Paralysis with Structured Email Campaign Prioritization

Here's an article I wrote for ClickZ:

Savvy email marketers now have the ability to rapidly send precisely targeted, relevant email marketing campaigns, driven by a wealth of customer data collected from different sources.

Organizations are investing in making even more customer data available to marketers, based on the premise that more data will improve marketing results.

Faced with so many possible improvements, how do we identify the best opportunities to pursue - those we can accomplish quickly and count on to actually improve our marketing performance? We want to uncover the most impactful avenues to pursue first.

Start by making a list of potential projects and evaluate each opportunity against the following criteria:

• Which are most likely to improve KPIs?
• Which are most feasible given our timeline and budget?
• Which is easiest to accomplish and will produce measureable results?

Let us imagine a fictional company:, a casual clothing retailer for men, women and children. The marketers at now have access to on-site analytics data by user, cart status, shopping history and certain demographic information. Currently, they are only using cart status to drive a rudimentary abandoned cart program, which simply sends customers a reminder that they have abandoned their cart. It does not identify which products have been abandoned.

Let's examine's options using the three criteria above, to identify which program changes they should make first, given their new abilities.

1. Which Are Most Likely to Improve KPIs?

It may seem odd to ask this question before understanding what is feasible, but you can often get much better results by having an end goal in mind before gauging feasibility. You may be able to find or reallocate resources once there is a compelling vision to work toward. now has easy access to the following new data:

• On-site usage data by user
• Cart status and shopping history
• Some demographic data

Here are just a few of the potential improvements they can pursue:

Option 1 could use the new cart status and shopping history data to improve their abandoned cart program with more relevant content, including the actual products abandoned and relevant promotions based on past purchase history.

Option 2

They could combine on-site usage and shopping history data to identify and leverage a customer's affinity for certain products and categories on their site, then use that insight to personalize future promotional and service messages.

Option 3

They could take demographic data and make assumptions about which products to highlight, based on informed assumptions about the preferences of particular demographic groups.

After compiles this list of possibilities, they evaluate which option will provide the greatest improvement to their KPIs. Of the three options above, the marketers decide that Option 3 is a gamble, while Options 1 and 2 show strong potential as campaign improvements.

2. Which is Most Feasible Given Our Timeline and Budget?

Next, does a deep-dive assessment of Options 1 and 2, to determine the requirements to make each option a reality.

Option 1 Requirements

In order to create an enhanced abandoned cart campaign, the marketing team would need to create new templates that dynamically populate messages listing the products in the user's cart, as well as the price the user originally saw. They would also need to build some sort of rule about that user's adoption rate of certain promotions, to decide whether to offer free shipping or a percentage discount.

Finally, the marketers would need to have a near real-time feed of user data, so they could avoid sending the abandoned cart program to users who had since purchased.

Option 2 Requirements

In order to personalize promotions based on on-site behavior, the marketing team would have to build several rules to associate behavior metrics with affinity (ie.: time spent in different categories, products in a single category purchased as percentage of total purchases, etc.). These rules could be basic or more complex, but something would need to translate what the customer did into a specific message that the customer would receive. would also need to remake some of their templates, adding the ability to insert dynamic content based on customer record. They would need to plan for multiple versions moving forward, making sure they curate the content for all possible variations.

In this step, the marketers at are beginning to create a project plan around implementing new data insight into their programs, while simultaneously evaluating whether or not the required investment will be worth the potential gains. After considering the requirements for the two options above, decides that both campaigns will require some investment, but both are feasible given their current access to data and ability to create and manage new content.

3. Which is Easiest to Accomplish and Will Produce Measureable Results? must now identify which option - Option 1 or Option 2 - is easiest to accomplish and measure improvements. Note that this is effective only after they have thought through the aspects of possibility, benefits and which capabilities and resources are required. Beginning your option evaluation on this last step is a mistake; if the marketers at had started here, they would likely have rejected several viable options as too difficult, unfeasible or unlikely to deliver results.

Reviewing the remaining options, decides that Option 2 will be easier to accomplish since it does not require the real-time link that Option 1 requires, to avoid emailing people who have completed their cart. They also decided that Option 2 is more likely to show results quickly, since the reach of all promotions and service messages that will change is greater than the reach of the abandoned cart campaign. They decide to pursue Option 2.

Get Over Analysis Paralysis with Methodical Opportunity Evaluation

This theoretical situation faced by the fictional company is similar to the situation faced by many email marketers today. The abundance of potential customer data insights that marketers can pursue to improve their campaign performance is overwhelming - so much is possible, and it can be difficult to decide which options to invest in first.

By analyzing opportunities in a structure similar to the example shown above, however, marketers can overcome 'analysis paralysis' and focus on making the promised benefits of big data become a reality.

Posted by: Justin Williams at 9:40 AM
Categories: email campaign prioritization, email, analysis

How can I demonstrate the impact of my email campaign?

Here's an article I wrote for BtoB:

Understanding how an email campaign influenced your audience is not always easy. There are many factors that could contribute to why your customers engage at any particular time. Let's take the example of a conference for which you are trying to get registrations.

Customer Y is considering registering for the conference. He may be using all kinds of information to make his decision—a colleague who is also going, a brochure you sent to his office, an email you sent or all three.

At some point, he makes the decision to attend, but hasn't gotten around to registering yet. Then your “Last Chance to Register” email lands in his inbox. It's got an incentive—a 10%-off registration code. He submits his RSVP. Do you attribute his registration to the last- chance email? Likely so.

However, what you don't know is that Customer Y was invited by one of the guest speakers and was planning to register anyway. By coincidence, the 10%-off registration code arrived moments before he was going to register; it didn't change his course of action, but it did save his company a few bucks.

This story illustrates potential pitfalls in trying to accurately attribute the impact of each of your marketing tactics. Is there anything we can do to militate against this problem?

One technique that email marketers can employ is to leverage distinct test and control groups within your audience to measure the impact of an email in the inbox; you may be familiar with control groups in the medical community as it pertains to clinical drug trials—one group receives the actual drug; the other (control) group receives a placebo.

In email marketing terms, a control group receives the same treatment that it would have received if no tests were being conducted. They receive the same number of emails, at the same pace with the same content as your last conference campaign. Conversely, the experimental group receives a campaign in which a new variable is introduced—different content, a different number of messages, different offers. Ideally you would change one variable at a time within each experimental group and, if your audience is large enough, you can run multiple tests across multiple groups simultaneously.

Insight can be drawn when you measure response of the test versus the control group. What was the impact of your email campaign within each group? Did the experimental groups perform differently than the control? Did more people register from the test group who received a 15%-off registration code versus the control group that received a 10%-off incentive?

With other variables held constant, test and control groups allow you to more accurately measure the impact of your email campaign with greater confidence.

Posted by: Amanda Hinkle at 9:36 AM
Categories: control groups, email marketing, email campaign, email

Gmail Changes the Way it Renders Images

UK email marketing agency Alchemy Worx recently announced an important change in the way that Gmail renders image code. I've re-posted the full announcement below. As a reminder, always use an email campaign preview tool to see what your email campaign is going to look like in various email clients prior to deployment!

From Alchemy Worx....

Why does this matter?
It matters because it causes unwanted spaces to be added to your email potentially breaking the layout of your HTML. Code that used to render perfectly may now render incorrectly.

The change appears to be affecting messages in Gmail webmail when viewed in Firefox, Opera, Chrome and Safari. However it does not appear to have any effect on HTML emails in Gmail webmail viewed in Internet Explorer.

The solution

This issue is similar to a long-standing Hotmail bug. However, although you can fix this by addingat the top of your email in Hotmail, Gmail ignores this code so that fix will not work.

To ensure your HTML emails render the way they should in Gmail the following needs to be added to every image tag: style="display:block"

There is one exception: when you are displaying images directly alongside text, such as when you are wrapping text or putting images inside paragraphs.

Don't forget your triggered and transactional messages

The change will not just affect new messages you create, it will also affect any triggered or transactional email templates you have already set up.

Posted by: Kristin Hersant at 3:14 PM
Categories: alchemy worx, email campaign preview, email campaign preview tool, email marketing, gmail, image blocking, image rendering