SOLUS AI is a system of Intelligence that powers brands with the Machine Learning tools that drive revenue from an existing customer base.
There are 4 core pillars around which SOLUS AI has been built.

Recommender Systems

Predictive Scores

Smart Campaigns

Insights

SOLUS AI is a system of Intelligence that powers brands with the Machine Learning tools that drive revenue from an existing customer base.
There are 4 core pillars around which SOLUS AI has been built.

Recommender Systems

Predictive Scores

Smart Campaigns

Insights

Recommender Systems

 

SOLUS comes with powerful Recommender systems to help brands recommend products, categories or offers to customers at the N=1 level.

 

  • Uses online, offline, transactional, non-transactional signals
  • Multiple Strategies: Genome Matching, Preference Vector, IBCF, Content-based filtering, Trending
  • SmartBasket capabilities that combine reorders and recommendations
  • Recommender of Recommenders
  • Reco Stories that convert Recommendations into customer friendly selling stories
  • Accounts for business rules such as exclusions, promoted products, stock checks and more
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The SOLUS URL Shortening Service creates short URLs for each Customer X Campaign, allowing sending of unique links that take customers to unique landing pages with curated product recommendations

 

Our Predictive Models are out of the box, use machine learning methods such as gradient boosting, and give you instant access to powerful tools such as gain charts, and tracking of how conversions vary across deciles.

Predictive Scores

 

SOLUS AI comes pre built with predictive scores that help with targeting customers with the propensity to demonstrate specific behaviours.

 

  • Likely to buy in the next N days (Can select between 7/ 15/ 30 days): Select customers with a high propensity to buy and either target them, or suppress them from campaign lists
  • Likely to Repeat: Propensity of a newly acquired customer to do a next transaction, allows marketers to prioritize spends and offers on higher propensity acquisitions.
  • Likely to Churn: Propensity of an existing customer to not transact again in the future
  • Propensity to be Won back: Likelihood of a lost customers to be won back, useful for marketers with large dormant databases who want to improve their ROI on winback campaigns.

Smart Campaigns

 

The SOLUS Smart Campaign systems have been built to power campaigns with a focus on personalization, recommendations, and incrementality tracking.

 

  • For both CLM (Recurring/ Lifecycle) or GTM (One Off/ Marketing Led)
  • Ability to use Recommender stories within campaigns 
  • Ability to manually set a waterfall or allow SOLUS to auto-determine campaign sequence using its contextual multi-armed bandit solvers
  • Ability to specify advanced response and attribution criteria
  • Ability to automatically choose the best day to target
  • Ability to configure unique (n=1 level) short URLs and landing pages for push campaigns
  • Ability to set up all multiple segmentation schemes, and create tactical segments for campaigns
  • Integrations for SMS/ WhatsApp (or similar)/ Email and Push Notification
  • Robust TG/ CG mechanism for Incrementality tracking
  • Ability to track campaign effectiveness using Multi Touch Attribution

 

Campaign Insights in SOLUS AI focus on Incrementality measurement and include:

 

  • Outreaches and channel split
  • Incremental Revenue, Lift, TG vs. CG metrics
  • CRM KPIs tracking such as Repeat, Retention, Winback etc.
  • Any vs. Hard Response (bought specific product)
  • Conversion Analysis – what was bought in the conversions 
  • Attribution views – Last Touch vs. MTA
  • Yield reports that specify the ROI from campaigns

 

Insights

 

The Insight section of SOLUS AI is a set of incredibly powerful reports covering Campaign and Customer insights.

 

Customer Insights gives marketers all the tools they need to manage their retention or CRM/ CLM programs. These include:

 

  • Repeat customer base and revenue tracking 
  • Bounce curve or Interpurchase cycle tracking
  • Repeat Cohorts 
  • Glue number and Glue cohorts (how sticky is the customer base)
  • Multiple Segmentation schemes with segment profiling
  • Customer frequency distributions
  • Segment movements over month/ quarter/ year

Recommender Systems

 

SOLUS comes with powerful Recommender systems to help brands recommend products, categories or offers to customers at the N=1 level.

 

  • Uses online, offline, transactional, non-transactional signals
  • Multiple Strategies: Genome Matching, Preference Vector, IBCF, Content-based filtering, Trending
  • SmartBasket capabilities that combine reorders and recommendations
  • Recommender of Recommenders
  • Reco Stories that convert Recommendations into customer friendly selling stories
  • Accounts for business rules such as exclusions, promoted products, stock checks and more
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The SOLUS URL Shortening Service creates short URLs for each Customer X Campaign, allowing sending of unique links that take customers to unique landing pages with curated product recommendations

 

Predictive Scores

 

SOLUS AI comes pre built with predictive scores that help with targeting customers with the propensity to demonstrate specific behaviours.

 

  • Likely to buy in the next N days (Can select between 7/ 15/ 30 days): Select customers with a high propensity to buy and either target them, or suppress them from campaign lists
  • Likely to Repeat: Propensity of a newly acquired customer to do a next transaction, allows marketers to prioritize spends and offers on higher propensity acquisitions.
  • Likely to Churn: Propensity of an existing customer to not transact again in the future
  • Propensity to be Won back: Likelihood of a lost customers to be won back, useful for marketers with large dormant databases who want to improve their ROI on winback campaigns.

Our Predictive Models are out of the box, use machine learning methods such as gradient boosting, and give you instant access to powerful tools such as gain charts, and tracking of how conversions vary across deciles.

Smart Campaigns

 

The SOLUS Smart Campaign systems have been built to power campaigns with a focus on personalization, recommendations, and incrementality tracking.

 

  • For both CLM (Recurring/ Lifecycle) or GTM (One Off/ Marketing Led)
  • Ability to use Recommender stories within campaigns 
  • Ability to manually set a waterfall or allow SOLUS to auto-determine campaign sequence using its contextual multi-armed bandit solvers
  • Ability to specify advanced response and attribution criteria
  • Ability to automatically choose the best day to target
  • Ability to configure unique (n=1 level) short URLs and landing pages for push campaigns
  • Ability to set up all multiple segmentation schemes, and create tactical segments for campaigns
  • Integrations for SMS/ WhatsApp (or similar)/ Email and Push Notification
  • Robust TG/ CG mechanism for Incrementality tracking
  • Ability to track campaign effectiveness using Multi Touch Attribution

Insights

 

The Insight section of SOLUS AI is a set of incredibly powerful reports covering Campaign and Customer insights.

 

Customer Insights gives marketers all the tools they need to manage their retention or CRM/ CLM programs. These include:

 

  • Repeat customer base and revenue tracking 
  • Bounce curve or Interpurchase cycle tracking
  • Repeat Cohorts 
  • Glue number and Glue cohorts (how sticky is the customer base)
  • Multiple Segmentation schemes with segment profiling
  • Customer frequency distributions
  • Segment movements over month/ quarter/ year

 

Campaign Insights in SOLUS AI focus on Incrementality measurement and include:

 

  • Outreaches and channel split
  • Incremental Revenue, Lift, TG vs. CG metrics
  • CRM KPIs tracking such as Repeat, Retention, Winback etc.
  • Any vs. Hard Response (bought specific product)
  • Conversion Analysis – what was bought in the conversions 
  • Attribution views – Last Touch vs. MTA
  • Yield reports that specify the ROI from campaigns

 

A SOLUS AI Use Case

Who Uses SOLUS AI

Omni Retail

Personalization in Push, CLM, Recommendations on App/ Web

D2C

Recommendations on App/ Web, Push + Landing Page Recommendations 

QSR

Lifecycle Management, Customer insight, Personalization

Brokerages

Scrip/ Sector recommendations for better customer nudges

Hospitality

Booking propensity, Lifecycle management, Resort recommendations

AMC

Fund recommendation, Customer Nudge, Agent Productivity

The Impact We Create

Yield on Recommender led campaigns 4-5X of those without Recommendations 
Proven impact of increased Personalization fields. Campaigns with 3 or more Personalization fields perform 15-50% better.
Lower Bounce Rate
SmartBasket and Recommender Led Landing pages have amongst the lowest Bounce rates
Incremental Sales
Lift or Incremental Revenue as a % of Topline in the range of 3-10% across implementations

Team

Sandeep Mittal
Sandeep Mittal
Founder, Managing Director
Founder, Managing Director

Sandeep Mittal

An alumnus of IIM-Calcutta, Sandeep founded his first startup whilst still in college, started and edited an underground online magazine, and worked on how to nudge customer behaviour using first party data in Direxions, prior to founding Cartesian and SOLUS AI. Sandeep has been regularly recognized as a leading light in the analytics industry in India and evangelizes data driven marketing.

Shikha Lath
Shikha Lath
Co-Founder, Head of Sales & Marketing
Co-Founder & Head of Sales & Marketing

Shikha Lath

Shikha Co-founded Cartesian, and then SOLUS AI after over 13 years of marketing, CRM, loyalty and direct marketing experience across organizations like P&G, JWT and Direxions. She has been the driving force behind some of the best CRM work in the Indian market and specialises in bringing information and insights to life through communication and campaigns.

Narasimha Murthy Pappu
Narasimha Murthy Pappu
VP, Technology
VP, Technology

Narasimha Murthy Pappu

An alumnus of IIT Mumbai, Narasimha has over 20 years of professional experience in Business Analytics, IT Services, Enterprise Software Development and research in Information and Decision Technolgies. He is a recognized leader with prior roles at Cisco, Genpact Analytics Center of Excellence and GE Research. He has expertise in developing Enterprise IT solutions and is the driving force behind the development of SOLUS AI.

RamasubramanianSundararajan
Ramasubramanian
Sundararajan
Head, Product R&D
Head, Product R&D

Ramasubramanian
Sundararajan

An alumnus of BITS Pilani and a PhD from IIM Calcutta in Machine Learning, Ramasubramanian (Ramsu) Sundararajan heads Product R&D at Cartesian. He started his journey as a researcher at IIM Calcutta and has worked at GE’s Global Research division as well as at Sabre Airline Solutions’ Operations Research group. In his current role at Cartesian, he is building the learning systems within SOLUS AI.

Rabindra Panigrahi
Rabindra Panigrahi
Head, Product Engineering
Head, Product Engineering

Rabindra Panigrahi

An alumnus of IIT Kanpur, Rabindra has 20+ years of experience in Product Architecture, Product Roadmap Development, Product Innovation and Release Planning & Delivery. He has led product engineering teams at large organisations like Oracle and Aris Global as well as at start-ups like Tarang Technology and hCentive. At Cartesian, Rabindra is spearheading development of SOLUS AI.

Deepa Ghosh
Deepa Ghosh
VP Sales, APAC
VP Sales, APAC

Deepa Ghosh

Deepa is backed by 16 years of Marketing and Communication experience across organizations like Oxfam India, Direxions, Vodafone, JWT and Lowe. She has played a key role in setting up the CRM and loyalty marketing practice for both established and start-up brands across sectors – telecom, e-retail, insurance, hospitality, consumer electronics, NGOs. Deepa is a people’s person and enjoys a winning reputation with internal and external customers.

Pearl D’Souza
Pearl D’Souza
Head, People Practices
Head, People Practices

Pearl D’Souza

Pearl has 16 years of core HR experience across varied industries with organizations like ICICI Lombard, Kotak Mahindra Bank, IDBI Federal, and Yatra.com where in addition to her role in HR she led Organization Learning & Capability Development. She alumnus of the Tata Institute of Social Sciences. At Cartesian, Pearl leads the People’s Practice and is responsible to create an ecosystem where our sharpest and most talented minds thrive together to create value for our clients.

Achievements

Videos

SOLUS AI: An Introduction

How SOLUS powers
personalization in BFSI

How SOLUS enables Guided
Selling For CPG

A Few Of Our Clients