MarTech Interviews by Theme

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MarTech Interviews by Theme by Mind Map: MarTech Interviews by Theme

1. Current Day-to-Day Activities

2. MarTech Capabilities that are Working Well

2.1. Note: Tool-specific praise was listed under the specific tool in the "MarTech Tools & Agencies Used" column.

2.2. General praise for MarTech

2.2.1. Efficiency we developed using existing tools

2.2.2. Have good processes, tools, and partners

2.2.3. Currently feels like things are moving in the right direction, i.e. with OICMS.

2.2.4. What's working: advertising platforms, bid optimization.

2.2.5. Meeting our goals

2.2.6. Standardizing naming convention for campaigns is a focus now (looked into Claredy?).

2.2.7. It’s good to have a system

2.2.8. Rule clarity because of the nature of the team and work

2.2.9. Feels like there’s an abundance of tools right now

2.2.10. The data we collect is good (through Adobe), we are able to answer the key business questions we need to answer.

2.2.11. Excited about the new tools that are about to launch (Decibel, Adobe Analytics)

2.2.12. A ton of effort around data usage agreements so we could leverage tools we want to leverage.

2.2.13. Last year we learned that TV was most effective

2.2.14. Adobe Analytics and naming is being addressed.

2.2.15. There is no hole where there is no solution on the way.

2.2.16. Starting making progress, especially on the personalization front.

2.2.17. Looking holistically is great (us)

2.3. Praise for inter-team work and support

2.3.1. Lifecycle managers are watching over the customer interactions across channers (i.e. Becka), but still managing lead lifecycle takes more people

2.3.2. Laura has been helping a lot with documenting of how the team works - that will help to prioritize what needs to be addressed. It will help with moving to more self-serve.

2.3.3. Regular check-ins with our CG partners about what they’ve been doing and what’s working for them re: vendors

2.3.4. A lot of support from other BUs - collaboration is great, people are helpful, smart

2.3.5. Joint account manager across BUs at different vendors

2.3.6. Worked with data scientists on a propensity model that was able to predict conversion with 80% accuracy. The model sends the values into Segment & we use the data to trigger push notifications with the best messages depending on Next Best Action.

2.3.7. Monthly updates from Q’s team help with visibility also seeing the roadmaps

2.3.8. Jennifer driving the documentation.

2.3.9. Relationship with Samaj and Q