CIOApplications
static-image
  • Home
  • Applications
      • Bioinformatics
      • Business Continuity
      • Business Intelligence
      • Chatbot
      • Collaboration
      • Custom Software Development
      • CRM
      • Enterprise Reporting Software
      • GRC
      • Human Resource
      • Indoor Positioning
      • InsurTech
      • Intellectual Property
      • IT Operations Management
      • IT Service Management
      • Low Code Platform
      • Maintenance Management
      • Managed IT Services
      • MarTech
      • Master Data Management
      • Mobile Application
      • Order Management
      • Parking Management
      • Procurement Tech
      • Publishing Software
      • Remote Monitoring
      • RFID
      • Sales Tech
      • SAS
      • Software Testing
      • Task Management
      • Unified Communications
      • Workflow
      • Workplace Management
  • Verticals
      • BioTechnology
      • Construction
      • Contact Center
      • Education
      • Fintech
      • Food and Beverages
      • Government
      • Healthcare
      • Legal
      • Logistics
      • Manufacturing
      • Travel and Hospitality
      • Utilities
  • Technologies
      • Agile
      • API
      • Artificial Intelligence
      • Blockchain
      • CAD/CAM
      • Cloud
      • Cyber Security
      • Data Analytics
      • Data Center
      • Digital Transformation
      • Graphics
      • IoT
      • Machine Learning
      • Machine Vision and Imaging
      • Predictive Analytics
      • Robotic Process Automation
      • Simulation
      • Smart Labelling
  • Eco System
      • Adobe
      • Amazon
      • Esri
      • Google
      • IBM
      • Infor
      • Kubernetes Partner
      • NetSuite
      • Oracle
      • PTC Partners
      • Qlik Partner
      • Salesforce
      • ServiceNow
      • SiteCore
      • VMware
  • Vendors
  • News
  • Newsletter
  • Whitepaper
  • conferences
  • About Us
  • Specials

  • Menu
      • Business Continuity
      • Chatbot
      • Cloud
      • Collaboration
      • Contact Center
      • Esri
      • Human Resource
      • InsurTech
      • IT Service Management
      • Machine Learning
      • Manufacturing
      • Master Data Management
      • Procurement Tech
      • Robotic Process Automation
      • Salesforce
      • ServiceNow
      • Simulation
      • Software Testing
  • Contact Center
  • Collaboration
  • Chatbot
  • Esri
  • Simulation
  • InsurTech
  • Human Resource
Specials
  • Specials

  • Business Continuity
  • Chatbot
  • Cloud
  • Collaboration
  • Contact Center
  • Esri
  • Human Resource
  • InsurTech
  • IT Service Management
  • Machine Learning
  • Manufacturing
  • Master Data Management
  • Procurement Tech
  • Robotic Process Automation
  • Salesforce
  • ServiceNow
  • Simulation
  • Software Testing
×
#

CIO Applications Weekly Brief

Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from CIO Applications

Subscribe

loading

Thank you for Subscribing to CIO Applications Weekly Brief

  • Home
  • Artificial Intelligence
  • Top Companies
  • Cognitiv

Cognitiv: Self-Trained Deep Neural Networks to Transform Marketing

Cognitiv

Jeremy Fain, Co-Founder & CEO, CognitivJeremy Fain, Co-Founder & CEO
The use of programmatic advertising, or the ability to make real-time decisions on the purchase and sale of advertising space, has become commonplace in the online advertising market as players look to target more efficient spend. Yet, with the terabytes of data being generated each day, advertisers are struggling to take advantage of that information and further optimize their investment methods. This is where Cognitiv steps in. By training computers to, as they say, “play the game of marketing” with all of the gathered data, Cognitiv brings deep learning to the advertising market. Jeremy Fain, the CEO and Co-Founder of Cognitiv, shares more insights into how their technology enables advertisers to better produce the expected outcomes with their automated, custom, self-learning neural network algorithms.

Cognitiv—Ideal Pathway to Identifying and Reaching the Right Customer

As we know, consumer behaviour is very complex. Why someone buys a product, what stores they go to, which products they view or buy, what apps they have on their mobile phones, which websites they visit, what content they read, what time they decide to buy a product, demographic information—these are all important data points that can help illuminate a consumer’s behavior. With the help of such comprehensive data, brands should be able to better understand their consumers but it is just too much data to process with traditional data science teams. At Cognitiv, we have the ability to plug all of this information into our proprietary technology, which then allows us to predict consumer outcomes more accurately than ever before, which in turn leads to increased sales at lower costs. By plugging a marketer’s own Big Data into our deep learning platform Neural Mind, the resulting neural network algorithms are able to accurately predict the outcome of buying impressions for a user at a specific time and place.

When Deep Learning Meets Consumer Data: The First Neural Network Technology for Marketers

Marketers have been experimenting with machine learning for years now, with mixed results. Predicting consumer behaviour is extremely complicated because of the sheer number of data points that are required. Cognitiv’s technology marks the first time that marketers can enter an unlimited number of inputs because of the power of deep learning.

This huge leap forward in machine learning and AI means that our algorithms are able to train themselves by taking raw inputs and finding the patterns that lie within, transforming the data into an artificial super brain that can guess the right answers. Cognitiv’s neural network technology isthe first to be able to train itself to do this for marketers, a milestone in the development of deep learning.

Deep learning itself is in the midst of taking a huge leap forward, and is being applied to solve problems across many different industries. Cognitiv’s aim is to show how deep learning can be applied to marketing, which is especially important at a time when businesses can no longer afford to waste any money on poorly targeted advertising. Instead, marketers need to find solutions that will allow them to target the right people at the right time at scale.

Cognitiv trains computers to play the game of marketing


For instance, a large company like Target wants to figure out how to target their advertising to the people who have either never heard of them or who are dissatisfied with their existing one-stop-shop; otherwise, they’ll end up spending a lot of money advertising to those who already shop there, or to people who have no intention of switching retailers.

To give another example, how can you find the people who are more likely to buy a BMW over a Mercedes? Given that both companies market to roughly the same demographics, it’s not exactly clear how one company might triumph over the other. Finding out what makes someone a BMW loyalist or a proud owner of a Mercedes is complicated, and marketers have thus far been unable to make that leap consistently due to lagging technology—but no longer.

Relieving the Pain in Manual Optimization with Hyper-Optimized Automated Marketing

Marketers spend a lot of money and time online, but the tools their agencies use require them to hire large workforces and optimize campaigns manually. Cognitiv gives marketers the ability to automate that work and optimize their campaigns much more effectively, freeing up marketers to think more creatively about their overall campaign strategies. Today, advertisers want to be more specific with their targeting and get better results, and our technology enables them to do that without adding hard-to-find data science resources or large manual optimization teams.

Moment of Pride: Proof of Cognitiv’s Ability to Drive Customers

Our algorithms can predict any kind of outcome, depending on a marketer’s needs. A company like Uber might want to identify the habits of their most loyal customers, defined as the people who use their service at least five times a week, and use that information to attract new customers. By looking at the list of people who fit this consumer profile, we can create a neural network that determines other consumers who are likely to exhibit similar types of behaviour, and optimize advertising accordingly. Similarly, we can figure out who is going to ask for an auto insurance quote, or how much money someone is going to deposit with a bank or brokerage. All that is measurable or has an existing database, such as a marketer’s customer list, can be used to create algorithms unique to that marketer’s specific need and make it easy for them to find new customers.

Out of the many organizations we have served, one interesting example involves a top mobile phone wireless carrier that wanted to leverage the Cognitiv platform to drive more in-store visits. In order to run that campaign, we used a third-party location data provider to develop a list of the device IDs that had gone to the carrier stores in the last 60 days, as this was the type of person that we wanted to find more of. We then trained our neural networks using that visit data, and advertised to people who the algorithm believed were good prospects (and not existing customers). Not only did we beat our client’s goal by 773 percent, we were also able to drive more in-store visits than any other media partner—and with a cost savings of 50 percent. This is just one example of just how effective our algorithms are at targeting the right people, in the right environment, at just the right time.

Strategic Approach to Reign over the Marketplace

Our engagement with IBM Watson has been an important partnership for us, especially as it validates our technology. IBM Watson has a history of being a strong player in Natural Language Processing (NLP) and image recognition. IBM was looking for a partner that had built deep learning technology with all the links to digital marketing platforms, and we were excited by the opportunity to add our technology to IBM Watson’s portfolio of AI capabilities. That is a huge accomplishment for Cognitiv, which was only two years old at the time of the implementation. As a result of this partnership, our technology continues to advance and be used by more and more marketers each month.

We are are also working on developing other toolsets for marketers that are very specific to mobile application marketing and looking to expand our footprint globally. As it stands, our technology has achieved great results for businesses in several verticals, including financial services, retail, and the automotive industry.


Read Also

Institutional Cash Distributors: Flexible, Efficient and Secure Trading

Tory Hazard, CEO, Institutional Cash Distributors

1787fp: Working toward Financial Independence

Jean Jacques Borno, CFP®, Founder & CEO, 1787fp

Advisor Software: Enabling Financial Institutions Revamp Digitally

Andrew Rudd, CEO, Advisor Software

NETSOL Technologies [NASDAQ:NTWK]: How Netsol Technologies Helps Companies Transform Their Asset Financing And Leasing Operations

Douglas Jones, Vice President Operations, NETSOL Technologies

Share this Article:
Tweet

Top Artificial Intelligence Companies

Top Artificial Intelligence Companies
ON THE DECK

Artificial Intelligence 2020

Top Vendors

Artificial Intelligence 2019

Top Vendors

Previous Next
Tweets by CIOApplications

I agree We use cookies on this website to enhance your user experience. By clicking any link on this page you are giving your consent for us to set cookies. More info

Copyright © 2021 CIOApplications. All rights reserved. Registration on or use of this site constitutes acceptance of our Terms of Use and Privacy Policy |  Sitemap  |  Subscribe |  About Us

follow on linkedin follow on twitter follow on rss
This content is copyright protected close

However, if you would like to share the information in this article, you may use the link below:

https://artificial-intelligence.cioapplications.com/vendor/cognitiv-selftrained-deep-neural-networks-to-transform-marketing-cid-2043-mid-112.html