Think back to your latest RFP process when your company was picking a new email service provider. Why did you make the selection you did? Ideally, it was because this particular vendor described in detail why they were the best fit for your particular needs, and how they could help you meet your specific email-related goals.

But, quite often, that’s not the case. At the end of a long, exhausting RFP process, a company might choose an ESP for a variety of reasons. Maybe their sales team had a key connection at your company. Perhaps they had the broadest set of features, or you had an existing relationship via other tools. Or maybe they merely offered the lowest price, and the higher-ups said that was the bottom line.

One of the most profound movements in marketing over the past five years or so has been the desire to consolidate as much customer information as possible into a single 360-degree customer database — more specifically, a Data Warehouse. If you have every piece (or nearly every piece) of first-party, second-party, and third-party data that you own or have acquired about your customer in one place, you can be even more personalized, responsive, and predictive (i.e. leverage AI models) about how best to serve and communicate to those customers. And customers increasingly expect you to leverage their data in this manner — to deliver a better cross-channel experience that “surprises and delights.”  To fail to do so is to risk losing that customer relationship.

When sending enterprise email at a large scale, a common obstacle that many B2C martech / marketing operations groups face is the struggle of moving and using their data. We’ve spoken about this topic in the past, and we’ve written about it too — but that’s because there are so many hurdles caused by the data movement necessary with a traditional marketing cloud ESP. Whether it’s setting up nightly copy and replication jobs to send your customer data to your marketing cloud ESP, fitting your data to their stringent data model, handling PII data security, or finding a way to bring your email data back down to your environment, using traditional ESPs at a massive scale can cause headaches for most marketing ops groups.

If you’re reading this, you’re probably not a graphic designer. But you may know good design when you see it … or you may not. Good design isn’t blatantly noticeable. Good design conveys the information effectively, efficiently, and subtly. Good design is easy to look at. But why is it easy to look at? What makes a design ‘good’?

For many marketers, their conversations with I.T. are mostly limited to times when they have a problem or need something, and they’re hoping I.T. has a solution. That can lead to a largely transactional relationship, where the two are separate teams that only come together when they have no choice, and only for as long as necessary.

That can lead to a lack of understanding — on both sides — of the crucial role the other team plays with respect to the success of the business, and to growing mistrust. The Marketing team thinks I.T. is being too iron-fisted about security and standing in the way of them drumming up new business. At the same time, I.T. thinks Marketing has no appreciation for the risks associated with data exposure, and that it’s I.T.’s responsibility to be the guardians.