AI Creative Strategist
Creatives are the #1 lever to optimize and scale performance while running ads on Meta, Google, TikTok or any paid media channel.
Yet, most growth and creative teams don’t have a data-driven process to iterate on creatives.
There’s no clear answer for:
- Why do some ads work and others don’t?
- What are the top objections and concerns users have?
- What angles and concepts are working for my competitors?
- How do I learn from these insights and make ads faster?
So we built the AI Creative Strategist that helps you iterate faster and launch winning ads.
https://www.youtube.com/watch?v=bLOutqGo4wU
This is how teams run their creative process with GetCrux:
- Surface Insights: AI watches every ad, finds patterns across creatives, tells you what works and why
- Learn from the Market: Learns from competitor ads, comments, reviews, and comes up with new angles
- Execute at Lightning Speed: Converts insights into on-brand and compliant creatives and auto-publish to ad platforms
We connect with all your data sources:
- Ad Platforms (Meta, Google, TikTok, YouTube, Pinterest, Snapchat, Display, App Campaigns, Applovin, TradeDesk, Inmobi, Criteo, Atari)
- 1st Party Data Sources (Snowflake, Tableau, Metabase, Looker)
- Attribution, MMPs or 3rd Party Tools (AppsFlyer, Adjust, etc.)
Growth and creative teams from large publicly listed enterprises to some of the fastest growing startups, including YC companies iterate 10X faster, and have even scaled 2X at a 10% lower CAC with our ads.
We’re one of the best teams working on this problem:
- Backed by senior execs from Google and Meta
- Our 1st product was acquired by one of the largest ad agency
- Building AI tools for marketers for over 3 years now
- Best AI engineers from IITs (top 0.01%) with avg age of 23!
If you’re a growth, paid social, or creative team that wants to iterate faster, we would love to chat. Talk to the founders.
GetCrux: AI Creative Strategist to Launch Winning Ads
getcrux: AI Copilot for Performance Marketing
Describe what your company does in 50 characters or less.
Customer-facing Analytics Copilot for SaaS
How long have each of you been working on this? How much of that has been full-time? Please explain.
We have been working full-time on this for the last 18 months and staying together.
February 2022 - June 2022 (5 months) We worked on several ideas in real-money gaming and web3.
July 2022 - January 2023 (7 months) We worked full time on a ‘User Acquisition Tool for Web3 Games’. Raised a pre-seed round, scaled to $10K revenue, and served 10+ games with 100,000 NFT drops
February - May 2023 (4 months) Pivoted away from web3, explored several idea spaces, and saw great opportunity in recent LLM developments
May - August 2023 (3 months) Built Crux - AI Copilot for Analytics for marketers in DTC brands in the US.
August 2023 - present (2 months) Building Crux in its current form.
What is your company going to make? Please describe your product and what it does or will do.
Problem Statement:- A growth stage SaaS company ($10M - $100M ARR) serving enterprises gets 100-200 ad-hoc requests per account per month to create custom reports, dashboards and provide insights. A pre-configured dashboard rarely solves the problem since the needs of the account are constantly evolving & every user in the account tracks different metrics.
These ad-hoc requests come to the customer success manager, who takes it to an analyst or engineer who fetches data, reconfigures the dashboard, and generates a report which takes 48-72h on average depending on complexity of the query.
Solution:- Crux is an AI Copilot for SaaS companies to provide customized analytics to their enterprise accounts by asking questions in plain English. Crux connects with all data sources, converts English queries to SQL, and generates insights & visualization.
Vision/Roadmap:- We want to help SaaS companies with one thing - enabling their customers to take the right decision quickly & effortlessly. This will be through:
Stage 1: Fetching the data lying in the SaaS via custom reports & dashboards
Stage 2: Proactively generating insights by identifying trends in the data
Stage 3: Being a co-pilot in planning by making predictions & executing tasks
