We believe that only a true symbiosis of business expertise and neural-network mastery can successfully build and adapt turnkey RGM solutions.
Four founders and a scientific advisor. Decades of hands-on practice in strategy, marketing and business growth management. Deep expertise in machine learning (ML), applied statistics and decision modelling.
Ekaterina Aleksandrova
Co-founder · Strategy and RGM
22 years of expertise at Coca-Cola across Strategy and Insights, Revenue Growth Management, Sales and Marketing, RtM, Key Account Management and Category Management. Led the RGM launch in Russia and Eastern Europe, developed the RGM methodology and advised other markets.
Since 2019 – a successful track record as an independent consultant, leading RGM, Strategy and Business Development projects with Chernogolovka, Baltika, Orimi, Splat, Perfetti Van Melle, Paulig and others.
Education
MBA
✦ Mini-philosophy
“I love it when the complex becomes clear.”
✦ Favourite moment in a project
What I enjoy most is hunting for hidden growth opportunities.
Anastasiya Merezhko
Co-founder · Marketing and portfolio strategy
30 years of experience in FMCG Marketing. Built brands such as Coca-Cola, Bonaqua, Powerade, Absolut, Martell, Kozel, Efes, Grolsch, Peroni, Chernogolovka and other international and Russian names. Expertise in portfolio strategy, brand strategy, innovation, category development, commercialisation and Revenue Growth Management.
At Chernogolovka she led the transformation of the beverage portfolio and the launch of new categories. The Chernogolovka brand reached No. 1 in penetration and brand equity in its category, while water grew from No. 5 to No. 2 in market share.
Education
MGIMO University (Russian Ministry of Foreign Affairs), Faculty of International Economic Relations
✦ Mini-philosophy
“Big results begin with the right question.”
✦ Favourite moment in a project
When dozens of hypotheses narrow down to the one that truly works.
Mikhail Ionitsa
Co-founder · Data Scientist · machine learning
Experience as a Data Scientist at Nestlé and Barclays, ex-Head of Data Science at StudyHall.AI.
Designing and training machine-learning (ML) models, building analytical systems, processing big data, forecasting and optimising business processes.
Education
BSc Data Science (First-Class Honours) – University of Warwick
✦ Mini-philosophy
“A good algorithm is always simpler than it looks.”
✦ Favourite moment in a project
When a model finds a pattern no one else had noticed.
Fyodor Bachkala
Co-founder · Management · AI adoption
Product lead at StudyHall.AI, customer support at Bending Spoons. Founder of the education platform “Not Quite Lessons”. Graduate of the Warwick Xelerate accelerator.
Building digital products, rolling out AI tools and integrating technology into business processes.
Education
BSc Computer Science with Business Studies – University of Warwick · MSc Management, Technology & Economics – ETH Zürich
✦ Mini-philosophy
“Technology is useless if the team doesn’t use it.”
✦ Favourite moment in a project
When a new tool becomes a habit for the whole team.
Georgiy Bachkala
Scientific advisor
Experience as a Machine Learning Scientist at Expedia Group; researcher and developer of computer-vision models for medical and commercial projects.
Building applied machine-learning (ML) models, evaluating and deploying algorithms to improve business performance.
Education
PhD (doctoral programme) in Health Data Science – University of Oxford
✦ Mini-philosophy
“If you cannot measure it, you cannot improve it.”
— Lord Kelvin
✦ Favourite moment in a project
When the mathematics confirms the business intuition.
A letter from the team
We’re glad you stopped by.
Let’s talk about what is keeping 100% of executives and owners up at night right now.
There are more business challenges than ever: you need to react fast, and better still – to act ahead of the curve. In our experience, three situations come up most often:
There seems to be a strategy, but you’re no longer sure it’s still relevant and will get you to the goal you need.
The team works hard, but the result doesn’t match the effort.
The market changes fast – new categories, competitors, raw-material prices – and there’s a feeling that something important is being noticed too late.
The typical business response to these challenges is three familiar moves: cut budgets, raise prices, shrink the team.
If these questions sound familiar and you want to solve them – let’s talk. We have been through similar challenges ourselves and, drawing on that experience, built tools that help answer a business’s key challenges systematically.
We work end-to-end with 10 RGM tools that show where you can raise price without losing volume, which kind of activation actually works and pays off, which SKUs wreck margin and which – drive growth.
Our company – Insight Machine (IM10) – connects in one place market data, your reporting, the team’s accumulated knowledge and the industry’s best practices. All of it works across three modules:
Vector – understanding the market and growth opportunities. Where to grow: which demand segments and products are the priority and how to build a long-term strategy.
Tactics – growth in turnover and profit. How to win here and now: pricing, promo and assortment grounded in the numbers.
Pulse – a live business monitor. What is happening: key metrics, critical deviations and their drivers – the why, not just the what.
A real example. In the “M1” retail chain, sales of the “Citrus Fresh” drink fell for 4 months running. It turned out a direct competitor had appeared on the shelf at the same price and in the same pack, while that pack size had been exclusive to “Citrus Fresh” before the competitor arrived. The team only managed to register the decline by the end of the third month, and to find the cause – by the end of the fourth.
With our system, signals like this are visible within 2–4 weeks – and options for corrective steps form straight away.
The options are built on four things: RGM theory and practice, our team’s decades of industry expertise, machine learning and scenario modelling, and your own history and data. The system proposes 2–3 solutions with an assessment: resource → timeline → feasibility → impact. Then, together with your team, we pick the right one and move into implementation.
Where artificial intelligence fits in. The calculations are done by specialised machine-learning models built for specific tasks – price elasticity, budget allocation across channels, demand forecasting. Large language models (LLMs) plug in around them: they explain the result in plain language, help find significant factors, draft conclusions and speed up the review of new data. The numbers themselves stay on verifiable ML models, not on a neural network’s “opinion”.
Online and offline. If a notable share of sales goes through marketplaces, the model is built separately for traditional retail and for online – the economics are different there, with their own drivers.
About the team. Four founders plus a scientific advisor:
Decades of practice in strategy, marketing and RGM – real decisions at major FMCG companies, not theory.
Experience at Coca-Cola and Chernogolovka for two co-founders (strategy, RGM, portfolio strategy, brand development).
Data Science at Nestlé, Barclays, Expedia – for the other two co-founders (machine learning, applied statistics, optimisation of management decisions).
Scientific advisor – an Oxford PhD in machine learning and statistics, practising in Big Tech.
At the intersection of these three competencies – marketing, RGM and Data Science – is where we build Insight Machine.
