yaamur

cross channel ad platform with machine learning
Startup name
yaamur
Web address
Founding date
March 2016
Incorporation
Yes
Total team member
3
Startup stage
Prototype
Category
Enterprise
Sector
Enterprise software
Product usage or interact
Desktop, Mobile/Tablet (iOS), Mobile/Tablet (Android)
City
Istanbul, TR

Elevator pitch

ad tech and AI have been a game that only big brands and agencies could play. we’re bringing data-driven Machine Learning to small and medium size businesses because they deserve to thrive in this digital economy, too.
why choose yaamur;
get more for your ad dollars with our AI algorithm
increase efficiency with cross-channel reporting

We’re here to make ad tech smart, usable and accessible

Team

Can Kuris

Eran Karaso

graduated from Koc University, finished a program at UC Berkeley then worked for a .com company in San Francisco for 5 years. was the director of online operations at Penti for 2 years. decided to start yaamur; launched with a different concept, pivoted and started development for mentioned scope

Business model

Target customer

small and medium size businesses and ad agencies

Customer acquisition strategy

paid acquisition, content marketing, referral program, direct sales

Revenue model

monthly or annual subscription plans for gaining access to our platform. there are 3 tiers for accessing our platform with different usage caps as well as different features such as ad optimization and scheduled reports/ alerts...

Market info

Market size

$ 15,000,000,000

Competitors

Competition

there are multiple saas products in the mar-tech field, some with very sophisticated artificial intelligence algorithms and some with basic automation tools. we plan on positioning yaamur in-between the 2 with our machine learning software and automation tool such as smart alerts based on campaign performance. our machine learning algorithm will be continuously improved in order to provide the greatest benefit possible to our customers.

KPI's

  • 0 ROAS (return on ad spend)
  • 0 increase in efficiency

Startup traction

we foresee a %10-15 improvement on ROAS (return on ad spend) with the help of our machine learning algorithm. also, with the use of cross-channel reporting tool as well as scheduled reporting and alerts users will benefit from increased efficiency when managing their ad campaigns.

Publication date: 28 September 2017