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Jessica Best

Director of Data-Driven Marketing, Barkley

Jessica Best: 6 Steps to Putting Data to Work in Email

Jessica Best: 6 Steps to Putting Data to Work in Email

It’s now 2017. We marketers have been chanting for “More data!” for years… and I think we can agree: we got it. Marketers use between 3 and 15 (!) data sources in their marketing, and the problem more often than not is that it doesn’t all live somewhere we can get to it or make sense of it.

Data Driven Email in 2017We don’t need more data; we need to make our data more USEFUL.

This dream data plan is has 2 sides: First, we need to focus on what data actually means something or moves the needle for a marketing campaign. Not all data is particularly useful. You can use any of it, but only some will actually impact your results. Second, you have to be able to get to it. It all needs to talk to each other (or at least it should all talk to the marketing system you’re using).

Let’s take a look at putting data to work for your email program in 6 steps:

#1 – First, define the goals of your email campaign or program. Yes, write them down. In pen (digitally speaking). Make sure everyone who determines how you spend your marketing budget or reviews your role & job performance agrees that these are the goals you’re all working towards. It seems silly, but you’d be surprised how often people still gloss over this step.

#2 - Set the measuring stick: What are the exact metrics you’ll be measuring this goal with? They have to fit the goal itself. Open rates are great, but will that tell you if you achieved your goal of getting more online orders from your campaign, for example?

#3 - Take inventory of all the data sources you have. What attributes do you have, where they live, how are they organized (by contact, by transaction, etc.), where are they synced from/to, what data “wins” in a discrepancy?

#4 – Make a list of what data moves the needle. This is different for just about every company and industry, and the best way to answer this question is to test it. Second best, though, is borrowing ideas. Read up on case studies of what others are doing to great effect.

(Not sure where to find case studies? Start with Marketing Sherpa/MEC Labs and eMarketer for measurable stories. Also, try subscribing to, previously called Which Test Won.)

Think of data boosting in your email program in 3 different categories:

  1. Data can determine the timing of your email, i.e. automation and segmentation, ensuring the most effective use of your program.
  2. Data can determine the content of your email, i.e. personalization and dynamic content, a.k.a. the juicy stuff.
  3. Data can determine the impact of your email, meaning you’re learning something from each send to use in the next campaign. Make the most of your best-performing campaigns.

#5 - Define what data you’re missing in order to make magic happen. What data point did that case study have that you don’t? Why not? Where does it live? Can you substitute similar data? Can you budget for an integration of that data with your marketing tools? What is the value of adding that data? This becomes your budget for the project. If the value of that data doesn’t pay for itself, try a different idea.

#6 - Choose your data hub. Once you answer #4 & 5, you’ll probably be revisiting where and how you store all of your sales, marketing, and even company data. This doesn’t have to mean a system overhaul!

Figure out which data setup is right for you and your company:

  1. It may just be your email service provider. If you have entirely offline sales and are a consumer-facing company, the data that you have or need may all fit within your email platform. Use nightly secure FTP file drops (auto export & import) to sync data to and from other systems as needed. Or, check out Zapier for a few (free or paid) plug-ins to common platforms.
  2. If you have direct sales or service contact with your customers outside your store, i.e. business-to-business companies, you’re likely using a customer relationship management system to house your customer data, plus the notes on interactions from humans and technology alike. In this case, you’re CRM becomes your hub and you can sync your accounting data, contracts, and more right into one main data system that is largely aligned by contact.
  3. When you have more than 5 data sources, OR if you don’t need a CRM, OR you have data that you want to put to use in marketing that isn’t organized by contact (i.e. store data, inventory data, transactional data, etc.), you’re likely ready for a bigger solution like a Data Management Platform or Data Warehouse. It’s a custom database solution, specifically for housing multiple types and large quantities of data to make them useful. They consolidate your data for a single, robust view of your customer across all your data points, and they come in all shapes, sizes, and budgets.

best slide2Predictably, a data warehouse will probably be more of an investment than just using your ESP or CRM (which you’re already paying for) and doing a few data integrations. This is why it’s important to start from the beginning and define your goals. Can your data system help you achieve those measurable goals? If so, it might be worth it. If not: save yourself the time and investment until it can pay off.

Go forth and put your data to work, my friends!

Title: 6 Steps to Putting Data to Work in Email
About: Big Data in Marketing
Audience: Email Marketers
Copyright 2017, Only Influencers, LLC


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Monday, 21 August 2017

Because email marketers are under resourced, busy people – and often new to the profession or have nobody to show them the ropes – they look to "best practices" as silver bullets that will fix their problems or keep them on the right side the law

Coupled with our history of being associated with spam, it's easy to see why marketers are so focused on following best practices. They use it as a solution to a common problem. The solution becomes a trend, and before you know it, it's promoted to a best practice.

However, I see too many marketers rushing to implement best practices without questioning whether something is truly a best practice, a trend or a bad habit that has evolved into a rule.

The concepts of Retention and Predictive Marketing have been around for quite some time; however, at its inception, only the largest stores could afford to invest in this type of data warehouse and management. Over the past few years, solutions have evolved to help retailers gain access to their data and enable retention and predictive marketing, but adoption has been mostly exhibited by innovators and early adopters. Over the past three years, we’ve conducted the Retention and Predictive Marketing survey to better understand trends in the marketplace, adoption of retention and predictive marketing, and barriers and successes retailers, who’ve invested in this technology, are experiencing. This year’s survey was completed by hundreds of retailers, spanning industries and revenue levels. Here’s a breakdown of the results from the 2017 Retention & Predictive Marketing Report.

We know that email is a money-printing machine. (Flash to the hundreds of articles that quote the outrageous and unbeatable Return on Marketing Investment.) As I often say with clients and at conferences, “Why wouldn’t you stand in front of the email marketing machine and just put in all your money?”

List size is a metric that is ridiculous on its own. As every Email Marketer knows, it’s not about the size of the list, but the quality.

The battle over when to suppress users is age old, commonly fought between those who are focused on the size of the list, and those on the email side who understand that inactives hurt deliverability.

Your customer data is a goldmine of information just waiting to be discovered. You know that emails which reflect a customer's data are more relevant and likely to be acted on, but too many marketers stop at basics like name, gender or location.  

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