Through our own experience as social marketers, we realised that marketing technology was delivering lots of data, and some great tools to help you execute, but the real opportunity to make a massive difference, was in delivering insights and actionable recommendations that identified, how, when, what and why to execute, to help you deliver more effective marketing outcomes.
This is where MRT comes in. We look for patterns in the data to make recommendations that help you to market yourself better, and take some of the stress out of having to continually monitor what your community is doing and if you have the right content scheduled.
To load MRT, click on the yellow light bulb in the top left of The Hub interface:
This will load up the main MRT Panel:
This is what we refer to as your Card Stream. This changes over time as new recommendations appear and other disappear or are removed by you.
You can close it by clicking anywhere outside of the panel.
Each card represents different information, ranging from information about how locations are performing to the latest Metigy news articles.
All of the cards have buttons at the bottom of them which behave different according to the content of the card:
The Action layer outlines the MRT recommendation for the card. This might be simple information like new to something more urgent like a post is getting excessive traffic or negative sentiment.
What does this card mean? Why have we made this recommendation and what you can do with the information? Examples include suggesting you respond to the situation, apply some spending or just useful information about the definition.
Some recommendations need backing up, and MRT is built around the idea of trusting what it says. If you are interested or a data nerd like us, this panel will give you more insight as to what data was used to make this suggestion.
Sometimes you no longer want to see a card or you've already actioned it - also, cards have an expiry time so they will automatically remove themselves from the list. To manually delete a card, click on the trash can, and you will be asked to confirm the deletion.
NOTE: Once you delete a card, it's gone for good.
Greg has a passion for what AI and Deep Learning can bring to the MarTech stack and how small and medium businesses can benefit from these new technologies.
He has over 20 years experience as an engineer and product developer, having worked for significant global marketing agencies, Razorfish and We Are Social.
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