Big Data Or Big Logic: What's Really Driving Email Success?

The sheer volume of data available to marketers today is astounding, with many more tools available to help marketers track, analyze and take action on that data. The good news is, those tools have become more cost-effective and attainable than ever before.

Still, just because you have the tools and CAN take action with Big Data, does that mean you SHOULD? In the end, you have to ask yourself if you really will drive more revenue for your brand (and the channel) with all of that analysis, strategic application and content creation.

 I am not going to say definitively that you won’t. Chances are you may -- if your brand has amassed an organization and staff to focus specifically on that task -- but for many marketers and brands, the reality is that they may not be resourced to benefit from all of this data.

To drive more revenue for your brand, you should focus your energy on Big Logic, not Big Data.

Getting to Big Logic involves two perspectives: the business of email and the strategy of email. The business side involves mapping and aligning your marketing goals and objectives to the purpose of the email communications you send. The strategy side is about defining how you will motivate your subscribers to act in a way that meets your program goals. You can think about things like your targeting and segmentation strategies, content strategies and the business rules you have associated with driving your dynamic content. By splitting Big Logic into two perspectives, you can shift your focus away from how much and what kind of data you have, to the true strategy that will help you achieve your goals and objectives. 



The email marketing channel, unlike many other channels, has an innate ability to apply business rules to data in order to deliver relevant messages to subscribers and customers. Still, the reality is that many email marketers don’t use data in this way. Even industry experts that chant the “send more email” mantra do so with an expectation that brands are leveraging some common sense about the use and application of the channel. So where do you really begin to build that logic? And how complicated does it really need to get?

This is the first in my series of posts on Big Logic. This week, I am going to focus specifically on the purpose of your program and its ability to meet the needs of your subscribers. Next, we will dive into how to map goals and objectives to the right data and big logic, and finally wrap up the series with some tips on how to build logic to drive success.

Apply “Big Logic” to avoid getting your message lost in translation

Some of the best email marketing programs succeed by demonstrating a succinct understanding of customers’ needs. A case study about Febreze in the book “The Power of Habit”by Charles Duhigg ilustrates this concept. Febreze initially targeted the product to people with an “odor issue,” like pet owners or smokers. Product adoption was low primarily because these people did not recognize their odor issue. It wasn’t a product flaw, but a flaw in appealing to the logic of consumers. As soon as scent was added to the product and it was marketed as an air freshener, it became wildly successful. The same can hold true for your email program: just because you know what you want people to take away from your message, doesn’t mean that they will.

In order to really start applying Big Logic to your email program, you need to ask yourself the hard question: “Do my subscribers get the value they expect out of my email program?”

Answering this question can, and should, be done in a few ways. First, look at your engagement metrics: Do you see minimal engagement activity during the first 30 days of subscription? If so, this should be a red flag telling you that you are not delivering on the inferred or interpreted value proposition. You should also ask your subscribers for their opinions about what they deem valuable in your email program – poll them on Facebook, send them a survey, or execute a #hashtag promotion to solicit feedback and input. 

Next, you need to analyze that data and map your findings to your goals and objectives, which we will dive into in the next post. Until then, ask yourself that tough question: Am I really delivering the value that my subscribers expect?

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