I guess I like this event versus others, since it doesn’t seem as much like a vendor fest where everyone is on guard, or a trades show where rows of vendors are on show. This is a networking event where all types of things come out.
I’m encouraged to see lots of new faces, and some of the same faces — but with different logos on their sleeves — and some new crossover groups (other channels). While this is my 17th or 18th Insider event, I just wonder how long it will remain an “Email” summit — or will it morph into a more-ubiquitous view of messaging as we evolve as an industry? Evolution is a good thing.
This year is of particular interest, given what’s been happening with the consumer over the last two years. The mass consolidations of technologies and the general outlook for digital has never been stronger. There’s been a lot of momentum centered on building better-connected journeys, the cross device experience, the impacts of machine learning on how you react today and predict tomorrow.
We’ve come a long way from justifying email as a channel or talking generically about big data. It will be interesting to see how far we’ve come in our thinking this week.
Here are a few hot topics on my mind:
— Stormy clouds: Is big better? Is defensible your primary goal? I love the vision of a connected ecosystem. As a mar-tech enthusiast, I do believe in the value of an environment where you aren’t required to have power outlets in each room. We now have big marketing clouds shaping the industry, where they are seemingly a part of every conversation and being sold at the top levels of organizations.
The gaps are still there, so I’m very interested to see how marketers and integrators see this new world, and how the newer technologies fit in that landscape. Big usually translates to big budget.
— Machine learning: How far off are we from real machine learning and optimizing communications? All trends suggest the industry is dabbling with it, but for email, I’ve yet to really see great execution at scale with any form of machine learning.
Again, the term may be the hang-up, as it can mean a lot of things to different people. It will be fascinating to see how people are using machine learning to optimize copy, text, subject lines and cross-device experiences.
Or are we still in the world of a latent legacy
classifier system, where you need to sit your data in a data warehouse and wait for it to learn
before you react? The real key is not the great answers people may get — we’ve had models and recommendations systems for decades, I’m looking for examples of how companies are operationalizing this on a continual basis.
At 8,000 feet, funny things seem to happen: The air is thin, the mind a bit confused with rich food, drinks and lack of oxygen. But for some reason, that mix seems to bring out some really good thinking and ideas. Stay tuned to it on Twitter #MPEIS. Stay warm!