The LA eec Mixer hosted and sponsored by Edmunds.com, JibJab and Cordial was a success! The event featured a series of discussion tracks on Personalization, Testing and Machine Learning, led by Alessandra Souers of JibJab and Adam Meshot of Cordial. While gender inequality is a hot topic amongst industry discussion groups, this event proved that the women email marketers of Los Angeles are a strong contingency, with women accounting for over 80% of those in attendance.
This event featured some of the most recognizable brands from retail to media to subscription business models. The first topic kicked off with Next Gen Email Personalization, starting with a poll of the audience to get a baseline for which brands were just getting started and which brands were kicking some tail with really advanced approached to email personalization.
The group discussed the 3 stages of personalization:
- Taking advantage of stated preferences and basic profile information,
- Leveraging historical purchase and email engagement data with some automation, and
- Leveraging real-time behavioral triggered messaging, contextual, advanced testing and optimization, machine learning and predictive intelligence.
Over 1/3 of the audience felt that they are progressive in their email marketing practices, with “progressive” defined as the ability to personalize emails, make use of triggered email programs, and test machine learning and product recommendation technologies.
Some key call-outs from the group of roughly 30 senior email marketing executives:
- 1 out of 5 marketers are using only simple email personalization (first stage)
- 1 out of 3 marketers are using some version of historical behavioral data for personalization (second stage)
- 5 considered themselves “advanced” – using some form of contextual or real-time data (such as web browsing or cart abandonment) for real-time triggers (third stage).
We learned a large dating site is piloting machine learning for subject lines with mixed reviews, but plans to continue to test. Otherwise, very few if any were really leveraging any kind of machine learning or predictive technology to advance their programs.
- Price alerts
- Product announcements (e.g. when a movie is coming out)
- Staggering high-engaged with low-engaged audiences to cross-sell content.
Machine learning was primarily misunderstood for what it can do for email marketers. In a poll, only 3 out of the group felt that machine learning was predatory to their job in the future, while the vast majority of the group felt they didn’t know enough about what it could do. Most understood product recommendations and the idea of predictive analytics.
A few of the larger organizations are still hitting obstacles in expanding what they can achieve with email. This is due to organizational silos, limited IT resources and in some organizations, email marketers still struggle to sell at the C-Level the benefits of what you are doing unless you have a conversion end point with attribution.
There was a discussion on Data Hygiene services and the fact that Hygiene is relatively easy and inexpensive to put on your site for real-time data verification within the email capture process. This makes sense to put hygiene at the front of the funnel at a lower cost per email vs letting bad data infiltrate your list and paying more for hygeine later or worse, suffering through delivery challenges caused by dirty data.
The groups broke out into 4 groups helping build a “mock” program for 4 lifecycle stages for a member based retail site. Each group paired off to develop an onboarding program, promotional strategy, win-back program and behavioral trigger program. Each team then did a group pitch to the audience with their creative ideas, data they would need to drive their strategy, promotional ideas and cadence plans and presented to the entire group. Wonderful effort and team working sessions.
We had a wonderful evening filled with peer-to-peer networking, some sharing some scar tissue over wine, and we all left with new friends and some great takeaways.