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Tomi.ai

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About

Tomi.ai is a predictive marketing platform designed to bridge the gap between website behavior and final sales outcomes for high-ticket businesses. By leveraging machine learning, the tool identifies complex patterns in user behavior to predict a visitor's propensity to buy and their expected 30-90 day lifetime value (LTV) in near real-time. This approach is particularly effective for industries with long sales cycles or significant offline components, such as B2B SaaS, real estate, and banking, where immediate conversion data is often sparse or non-existent. The platform operates through a multi-step process that starts with the installation of a patented tracking pixel. It collects behavioral data from websites and mobile apps and then matches these visits with sales data from a company's CRM. Using this integrated data, Tomi.ai runs machine learning models to identify high-value visitor patterns. These predictions are fed back into advertising platforms like Meta and Google via Marketing APIs, allowing for value-based bidding and the creation of highly targeted predictive lookalike audiences. This tool is best suited for performance marketers and digital marketing directors who manage complex acquisition funnels with large transaction values. It is ideal for roles in EdTech, Insurance, and FinTech where the feedback loop between an ad click and a final purchase can take weeks or months. By providing a forward-looking view of revenue, it helps teams optimize their spending based on future profit potential rather than just historical click data or shallow lead metrics. What sets Tomi.ai apart is its US-patented technology and its ability to score anonymous visitors. Unlike standard analytics tools that focus on historical reporting, Tomi.ai creates a positive reinforcement loop for ad algorithms by providing them with high-intent signals early in the customer journey. Its predictive accuracy is notable, with customer evidence suggesting revenue forecasts typically land within a 20% margin of error of actual results, providing a reliable foundation for scaling marketing budgets.

Pros & Cons

Guarantees at least a 15% reduction in Customer Acquisition Cost on Meta and Google.

Utilizes a US-patented real-time predictive engine to score anonymous visitors.

Highly accurate revenue predictions that often fall within a 20% margin of error.

Optimizes for deep-funnel events even in industries with very long sales cycles.

Provides full access to raw data and supports server-side conversion tracking.

High starting price point of $3500 per month may be prohibitive for smaller businesses.

Requires a significant data collection period of 2-6 weeks before models can be trained.

Lower pricing tiers have strict caps on the amount of monthly ad spend that can be optimized.

Mobile app user scoring and advanced mobile optimizations are restricted to the Enterprise plan.

Use Cases

B2B SaaS marketers can use predictive lead scoring to identify the incremental impact of website visits and prioritize high-value leads for sales outreach.

Real estate agencies can reduce cost-per-purchase by optimizing Facebook Lead Ads for high-intent visitors likely to visit an office.

High-ticket e-commerce brands can implement value-based lookalike audiences to target shoppers with higher predicted lifetime value.

Banking performance teams can optimize non-brand search campaigns by using predictive attribution to track account openings that occur weeks after the initial click.

Insurance providers can utilize predictive retargeting to focus ad spend on users with the highest probability to buy, reducing wasted budget.

Platform
Web
Task
marketing optimization

Features

predictive lead scoring

ga4 event scoring

patented behavioral analysis

server-side conversion tracking

crm and advertising api integration

real-time ltv prediction

predictive attribution modeling

value-based audience targeting

FAQs

How does the pricing for Tomi.ai work?

Plan pricing is determined by the specific features selected, the number of unique monthly or annual website visitors, and the total amount of ad spend being optimized by the platform.

How long does it take to see the first results from the platform?

While the initial pixel installation takes only 15 minutes, the process involves 2-6 weeks of data collection and 1-2 weeks of model training, with the first significant results typically appearing in 2-3 months.

Does Tomi.ai support mobile application tracking?

Yes, mobile app user scoring and mobile ads optimization are available, specifically as part of the Enterprise tier for businesses with significant app-based customer journeys.

Is the platform compliant with data privacy regulations?

Tomi.ai is GDPR compliant and uses a patented tracking pixel designed to handle first-party data securely while working with Drata on SOC2 compliance.

Pricing Plans

Starter
USD3500.00 / per month

Website visitor scoring

Website session scoring

Predictive conversions (basic set)

Predicted value-based bidding

Predictive retargeting

Predictive lookalikes

Up to 1,000,000 website visits

Up to $50k/mo optimized ad spend

Server-side conversion tracking

Basic onboarding and training

Professional
USD6000.00 / per month

Everything in Starter

Inbound lead scoring

Custom GA4 event scoring

Predictive conversions (advanced)

Pipeline expansion (warm outbound)

Predictive attribution

Advanced analytics

Up to 3,000,000 website visits

Up to $150k/mo optimized ad spend

Dedicated customer success team

Enterprise
Unknown Price

Everything in Professional

Mobile app user scoring

Mobile ads optimization

Category-based scoring models

Product-qualified leads

Custom integrations

Unlimited website visits

Unlimited optimized ad spend

White-glove onboarding

Monthly strategy sessions

Job Opportunities

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Tomi.ai

Data Python Engineer

Reduce customer acquisition costs by 15% or more using patented predictive AI to identify high-value visitors and optimize Meta and Google ad campaigns.

engineeringremotefull-time

Benefits:

  • opportunity to become a co-owner

  • remote work

  • open to new technologies

  • no grades

  • no strict vertical relationships

Experience Requirements:

  • experience in industrial development in Python from 3 years

  • experience with Kubernetes and Google Cloud

  • experience with pandas, scikit-learn, xgboost, TensorFlow libraries

  • experience with Linux environment

Other Requirements:

  • excellent data skills in Python / SQL / BigQuery

  • understanding of microservice architecture

  • team player, independent, and passionate

Responsibilities:

  • setting up the CI/CD process

  • setting up monitoring and alerts

  • improving storage security

  • building Data pipelines in Kubernetes and Google Cloud

  • development of microservices for big data and ML

Show more details

Business/Sales Development Representative (outbound sales)

Reduce customer acquisition costs by 15% or more using patented predictive AI to identify high-value visitors and optimize Meta and Google ad campaigns.

Benefits:

  • learn from Founder & CEO (Stanford MBA)

  • learn from Co-Founder (Ex-McKinsey)

  • Practical experience in IT/SaaS and AI

  • Potential to earn stock options

  • Unlimited career opportunities

Experience Requirements:

  • some prior work experience in tech sales

  • cold outbound prospecting

  • experience working with sales enablement technology

Other Requirements:

  • Strong problem solving, analytical, and communication skills

  • Very good or excellent written and verbal English

Responsibilities:

  • Conduct prospect research

  • Build and execute email and LinkedIn prospecting campaigns

  • Create highly effective email copies

  • Identify and create lead generation best practices

Show more details

Customer Success Manager

Reduce customer acquisition costs by 15% or more using patented predictive AI to identify high-value visitors and optimize Meta and Google ad campaigns.

Benefits:

  • opportunity to become a co-owner

  • remote work

  • open to new technologies

  • no grades

  • no strict vertical relationships

Education Requirements:

  • higher education

  • a technical degree is a plus

Experience Requirements:

  • experience in launching online advertising campaigns (Facebook, Google, etc.)

  • experience in Online Campaign Management or Account Management

  • experience in Web Analysis or Customer Success roles

Other Requirements:

  • knowledge of marketing analytics tools (Google Analytics, Yandex Metrica)

  • analytical mindset

  • knowledge of web and mobile technologies

  • excellent written and spoken English

  • ability to switch between multiple tasks

Responsibilities:

  • support customers in technical integration

  • set up integrations with advertising platforms

  • prepare recommendations for campaign effectiveness

  • analyze and prepare reports of current ad campaigns

  • design and deliver weekly/monthly progress reports

Show more details

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