Generating Outcomes Map with GenAI
Practical Applications

Generating Outcomes Map with GenAI

I am a big believer in delivering outcomes. Bottom line, customers are not buying your product for its features, they are purchasing your product to generate business outcomes they care about. To that end, last year I had led an initiative at Gong to map out our capabilities to customer outcomes. The intent was to talk in the language of customer outcomes in addition to product capabilities. The ultimate goal was to build the entire customer journey around customer outcomes - Sales positions the outcomes, Sales engineering demos to the outcomes, during onboarding CS validates the outcomes, PS implements the outcomes and CS is constantly communicating to the customer on progress to delivering the outcomes.

The cross functional effort involved Marketing, Product, Post-Sales as our v1 of outcome mapping. It was a multi-month effort and I wanted to take a step back and see if GenAI could have helped with the initiative. Here is a link to the video with more details on how I did this.

Here is what ChapGPT came up with -

Outcomes Map

Learnings -

  1. ChatGPT can help come up with a really really good V1 point of view that cross functional teams can then work off of to build the final version. I find that coming up with a V1 is often the most time consuming part and people should be leveraging ChatGPT for that.

  2. If you feel threatened because your value was in coming up with that point of view, you should feel threatened. I got paid a handsome salary and a big reason for that was my ability to think strategically. That being said, this does not replace my domain expertise. My value is in building the right prompt to generate the V1 (collaboratively), understanding and editing the V1 (collaboratively) and then taking this v1 and building something that works for my business (collaboratively).

  3. This might be my ignorance but there are different GPTs that are good at doing certain things and if you know what these are the output is much better. E.g. ChatGPT to come up with the POV and Whimsical to come up with the mind map.

  4. It would be great if there was a technology that could let me orchesterate some of this as currently I am having to do some swivel chair between GPTs and I am excited to work with Dmitri Tcherevik and Helen Thomas at AnyQuest www.anyquest.ai to incubate this.

  5. Organizations need to be asking themselves, how can GenAI help my GTM teams. I think they are focused on how do I add GenAI to my product but RevOps needs to looking at ways to build GenAI micro-applications to drive productivity.

Stay Updated

Follow Vikram on LinkedIn for more insights on GenAI automation and go-to-market strategy.

Follow on LinkedIn →

Ready to Transform Your GTM Operations?

Let's discuss how AI agents can automate 60-75% of your manual work.

Schedule a Consultation View Case Studies