This repository was archived by the owner on Dec 12, 2024. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 0
Demo Call Outline
Chris Pondoc edited this page Jun 8, 2024
·
1 revision
Here was our planned outline for Demo Calls.
-
Outline:
- Recap Previous Call
- Start Story and Product Orientation
- Pain and Benefits (Try to Highlight 3 Things)
-
Intro:
- Making sure this is still a good time?
- Thanks again! Been working with the team and would love to show you a demo of what weβve built
- How weβre gonna structure the call
- Recap the motivation
- Orient around the needs the product solves for
- Showcase pains and benefits
- Open-ended feedback
- Sounds good?
-
Recap Previous Call:
- We talked last time about the concept of AI search
- Search is an important part of e-commerce β first thing people see/go to on websites and is a critical part of conversion
- However, traditional search is old-school β youβre not capturing user intent, youβre only able to surface quite general search results, etc.
- We want to build a solution that is personalized and truly captures what a userβs intent is
- We talked last time about the concept of AI search
-
Start Story and Product Orientation:
- Letβs say Iβm an e-commerce business, and I have my internal list of SKUs (use the fashion dataset)
- Iβm using existing keyword search, but Iβm not getting a high conversion rate, even after optimizing other metrics
- I also want to build this new form of semantic search inspired by new AI platforms, but building in-house is tricky
- Maybe I donβt want to drain my engineering talent, maybe there are more relevant features on my product roadmap, so on and so forth
-
Is there a way to easily build from the ground up?
-
Pain Points and Benefits:
- For demo: explain the concept of SUPost
- First: it might be difficult to understand how to get started with your complex e-commerce data
- We offer a full platform that allows you to upload your arbitrary data, pick which features are relevant, and let us handle the complexities of implementing AI search
- You can also look back on all the collections youβve made, and then even do a preview of the search
- Next: search might be difficult because search queries change all the time, and users are giving more natural language queries that your search engine canβt understand
- Our search engine can handle them :) take a look at some sample queries
- Sample searches
- Cool art to put in my room
- Modern kitchen items
- Cheap computer equipment
- A new laptop for school
- Finally: you might be wondering why a specific search query gave you the results that it did
- Our algorithm handles that, as well! We provide the explanations necessary so that users donβt feel like itβs a black box
-
Feedback:
- Would love to leave it open for feedback!
For other information, check out our team's Google Drive. For a daily stream of thoughts, check this document.
- OKRs and KPIs
- Team Coding Standards
- Real Customer Profile
- Launch Week Recap
- Unusual Academy Pitch Event
- Final Reflection
- 1/23 - Jay Borenstein
- 1/26 - Chris Oh
- 1/30 - Glenn Reid
- 1/30 - Adam Heher
- 1/31 - Samantha Phillips
- 1/31 - Chris Tsakalakis
- 2/2 - MZ Zaveri and Kasey Zhang
- 1/25 - Introduction
- 2/1 - Proposing a Product
- 2/13 - OKRs and KPIs
- 2/27 - Catching up for Last Weeks of Winter
- 3/5 - Demo + Discussion
- 4/2 - New Quarter
- Strategy for Search for Shopping
- Ideal Customer Profile Brainstorming
- Outreach Messaging
- Tracking Outreach
- Discovery Call Outline
- Feedback from Unusual on Slides
- Meeting with Seena from Nike
- Meeting with Mike from Launch
- Meeting with Heather from Walmart
- Meeting with Sandy from Walmart
- Demo Call Outline
- Prototype v0: A New Shopping Experience
- Prototype v1: Updated Bookworm for Demo Day
- Prototype v3: SUPost Battle for Software Fair