We implement analytics, train teams, and build data processes to replace assumptions with fact-based decisions, driving company growth.
Stage 0
We help formulate a clear and measurable goal that will serve as the foundation for building analytics.
This stage includes an analysis of the current situation, identification of key roles, selection of tools, and development of a goal achievement plan.
We also provide recommendations for improving data infrastructure to enable data-driven decision-making and business growth.
This stage delivers standalone value and can be ordered separately.
Stage 1
Interviews with key company stakeholders:
Who is currently responsible for this process? How is it organized today? Who needs to be involved in decision-making regarding adjustments to the current business processes?Internal tools audit:
What tools and data are available? How are they used? What documentation exists for them? How well is the data collected and how frequently is it updated? What is the current structure of the development team?Competitor analysis (if necessary):
If the goal is related to customer behavior (offline or online) and the company does not hold a dominant market share, it is important to understand competitors’ customer engagement strategies.Market analysis (if necessary):
To better understand customer behavior, we study segmentation (by JTBD, consumer groups, etc.) and identify current problems. This helps refine the product offering or assortment.Benchmarking tools (if necessary):
We benchmark available analytical and administrative tools to select the most suitable ones for achieving the set goals.Formulating and discussing the implementation plan:
Based on the findings, we develop a detailed action plan to achieve the stated goals.
Deliverables of this stage:
Market and competitor analysis results (if conducted):
Analysis of the current market situation and competitor strategies to generate hypotheses and gain a better understanding of customer needs.List of project participants:
Identification of individuals involved in the project, including decision-makers (business stakeholders) and those responsible for execution and implementation (technical teams).List of tools to be implemented:
A detailed list of analytical and organizational tools needed for the project (if required).Recommendations for improving data infrastructure:
Suggestions to enhance the collection, storage, and usage of data to create a solid foundation for future analytics.Goal achievement plan:
Step-by-step actions for achieving the goal, including technical and organizational activities, assignment of responsibilities, and elimination of critical data quality issues.Workshop and training plan:
A schedule of training activities to equip the team with the necessary skills for successful data utilization.Final cost estimate:
A comprehensive evaluation of all project costs, including implementation and training.
Stage 2
This process requires close collaboration between our analysts, developers, and the client's team.
The duration of this stage depends on the scope of modifications needed, the condition of existing data, the number of integrations, and the complexity of the infrastructure. Implementation time may vary from 1 month to 6 months or longer in the case of unforeseen technical challenges.
Key steps of the stage:
Data collection: Technical work is completed to implement tools and integrate various data sources.
Data validation: Data is verified and prepared for further use.
BI systems setup: All systems are configured for data visualization and dashboard creation.
Stage 3
Goal and Metric Detailing
This stage focuses on enhancing the quality of analytics and its integration with real business processes. We break down overarching goals into low-level metrics that serve as KPIs or OKRs for employees or teams.
Collaboratively, we construct a metric tree, align expectations, and establish interconnections between metrics to ensure the entire team clearly understands their significance and role in achieving objectives.
This process involves multiple iterations and workshops (at least two, each lasting 1.5 hours) utilizing tools like MIRO.
Mapping Real Events to Data
Concurrently, we align real business events with data to improve interpretation and facilitate informed decision-making.
We analyze the customer journey—from brand awareness to purchase—and determine how to digitize and assess this journey using data.
This approach is equally vital for both online and offline processes in B2C and B2B contexts. We select appropriate data collection tools tailored to the business's specific characteristics.
Deliverables of this stage:
Taxonomy: A document illustrating the connection between real events and metrics (e.g., a Customer Journey Map or data matching file).
Technical Specification for Analytics Development: A detailed description of metric calculations and visualizations/dashboards to ensure accurate interpretation.
Metric Tree: A representation of the interrelation of key company metrics following the North Star Metrics methodology.
Stage 4
This is a flexible, iterative process in which the team learns how to interpret data and works closely with our experts.
The goal of this stage is not only to teach how to understand data but also to demonstrate how to influence metrics through the implementation of changes.
The process involves trial and error, but with the guidance of our experts, it becomes more structured and effective.
Before starting the training, we prepare all necessary resources:
Build basic visualizations to evaluate the metric tree with real data and create dashboards.
Set up infrastructure for collaboration (e.g., MIRO boards, task planning tools, a shared space for training materials).
Through real projects and practical tasks, we develop four key skills:
I understand and interpret data.
I can make decisions based on data.
I can argue and justify my position using data.
I can request additional data when needed.
We work in weekly iterations. Each week:
We assess the results of the previous week.
We generate hypotheses for achieving company goals based on data.
We update and prioritize the action plan using the RICE methodology to select the right operational and tactical steps.
We set a plan and tasks for the following week for each team member.
It is crucial for the team to develop the habit of consistently using and interpreting data.
This skill does not develop instantly, but over time it becomes as natural as regular exercise or healthy eating.
Deliverables of this stage:
Internal decision-making processes based on data are established.
Project and hypothesis management tools are configured.
Dashboards and visualizations for metric evaluation are ready.
The team is capable of working with data and influencing the company’s key metrics.
