Ep. 26 – Jon Chang: Spiderman, Better Email Marketing, & AI Data Insights

“Marketers really do ruin everything.”

If there were some sort of marketing nerd Olympics, Jon Chang (@changahroo) would be the Michael Phelps of the marketing nerd decathlon.  Currently an international speaker, product marketer at IBM Watson, and web analytics professor at NYU, Jon is walking the walk all day, every day.  Couple this with his background at high-growth start-ups such as General Assembly and Kickstarter, and you have a marketing enthusiast who has send hundreds of millions of marketing emails in his day.  While he thinks that in many ways we’re all blowing it, all is not lost; a bit of consideration for audiences and some AI-driven data insights might just save the day.

As a marketing professional, this was a really fun while somewhat meandering conversation and the reason is simple: Jon is an enthusiastic teacher who has a ton of great information and insight to share.  For this article I’m going to stick mainly to email marketing practices (and framed up for vendors selling through indirect sales channels), but I do recommend you give the entire episode (embedded below) a listen.

Jon begins with a premise that I think we can all agree on: as I write this in early May of 2019, marketers send way too much email, and there’s a reason it feels like too much, besides the obvious volume problem.  A big part of the feeling of “too much” comes from the fact that not enough of us are taking the time to segment our lists well and to consider what’s in it for the recipient.  We’re cranking on the email machine, thinking about our calls to action and thinking about the outcomes that serve us, forgetting some basic things such as how our simple, single email could be adding value to the lives of our list members.  How maybe it’s okay if people don’t buy a new widget or book a demo or write an order or whatever every time they interact with us. Perhaps it’s okay if we just signal each other a bit more subtly that we can trust each other to consider the other’s best interests?

Relevant Email Marketing

Jon’s framework for delivering relevant email marketing is to think of three main types of emails your company could want to send:

Transactional – This is a simple one to understand.  Transactional emails are trigger-based on some action that was taken where we then send an email to the user to confirm that the action was taken.  In the case of say, a channel marketing incentive, this could be a short email acknowledging receipt of an incentive claim.  In our framework of delivering value to the recipient, a great question to ask ourselves is “how can this email be as helpful as possible?”  Can we provide next steps, estimated time to processing/payment or other relevant information?  Could we offer the partner a link to relevant training or additional information that makes their life easier and helps them make more money?  Maybe they just signed up to become a partner through your online partner portal – would it be an appropriate time to thank them and give them access to information they may be looking for?

Of course, you’re still a marketer, and you still have a job to do – transactional emails are a great first step to easing the user into a nurture campaign of some sort.  In the channel marketing model, this could be a list that you use to deliver partner enablement and build further affinity for your brand.

Nurture – Nurture emails are where you can thrive creatively because these live in the crowded and noisiest neighbourhood of people’s inbox: Newsletterville.  Remember, Jon is not suggesting that sending email newsletters is a bad idea.  On the contrary, he’s saying that it’s still a great idea that too many people are executing on poorly.  Nurture emails are always a fantastic way to bring your users along with you on whatever journey is going to help you achieve your business objectives, but they need to be relevant and useful to the reader, or else nobody wins.  The fix is to think hard about the personas you are marketing to and consider what sort of content would need to go in to an email newsletter they would actually look forward to receiving and reading.  Over the course of your nurturing emails, you are signalling to your readers that you understand and want to serve their needs.  They, in turn, are signalling their areas of interest and intent to you through clicks on your content.

Engagement – “This is an email where you know what the reader wants, and you single them out,” enthuses Jon.  He uses the example of a fashion brand targeting a consumer on whom they have gathered enough data to know that the person would enjoy a particular shirt, but let’s take it back to the channel marketing world.  First, think for a moment about how you can leverage nurture emails to work your way up to engagement emails; today’s marketing automation software will measure just about every possible behaviour a recipient can take with your email from clicking on links to reporting you as a spammer.  Over the course of a nurture campaign, you should be able to gather enough signals in the form of these various interactions without ever having to ask anything of the person.  You’re helping them along with content designed to improve the lives of the people on your carefully segmented list, and once a reader has returned enough engagement signals, they’re ready to move to your engagement list.

Do you offer tiered rewards to your channel partners?  Do you want to invite your most engaged partners to be on an advisory board?  Are there further incentives they could be accessing by taking specific training that your brand offers?  By now, you should have a feel for what the partner reseller is interested in and be able to move them to an appropriate email list.

Jon wraps it up; “If you’re thinking about channel enablement, automation is a (big) key to success.”

The Promise of AI for Data Insights

Although Jon is a product marketer for IBM Watson, his knowledge of and enthusiasm for the space shine through in a way that is brand and platform agnostic.

For as long as we’ve been hearing about the value of Big Data for marketers, many have been scratching their heads trying to imagine how they could ever de-silo and clean their data up to a point where it would be sufficiently useful.  AI is just the fix we’ve all been waiting for.  Imagine if you had a team of the most skilled and experienced marketers and data scientists at your disposal. Now imagine that over time, they not only remove nearly all the barriers between your data silos but can also analyze and make recommendations based on fresh data insights almost as fast as the new information pours in.

How fast could you test and learn?  How quickly could you optimize every initiative for maximum ROI?  How much fun would it be to do your job?

LISTEN TO THE ENTIRE CONVERSATION NOW:

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