Ekibana Analytical reports platform for SAAS,
e-commerce and B2C services

Typical business questions

How much should we budget for marketing and what is the marketing ROI?

How long would it take to recoup the initial investment made for a project?

The problem:

  • Data on marketing expenditure is in the cloud: Google AdWords, Facebook, Yandex.Direct etc.
  • Data on sales and indirect costs can be found in internal services and databases: Mongo, Postgres etc.

CEOs and Product Owners require the full sales funnel information: from ad banner click to product purchase, but often it's difficult to integrate data from different sources into one report.

Ekibana is a tool that facilitates data collection and unification and has the capability of producing 50+ typical marketing reports.

Ekibana implements connectors to all of the common data sources

We collect data from all products and services into a unified repository, normalize data, and identify meaningful connections between the data segments.

Raw input data is transformed into a system of business entities, that becomes the foundation for marketing and KPI reports.

Connectors

Typical report: Marketing channel effectiveness

Report questions:

  • What are the CAC and LTV for all of the marketing channels?
  • Which channels are ineffective (CAC>LTV)?

Report metrics:

Report metrics

Typical report: Business model effectiveness

Report questions:

  • Does the service retain it's customers?
  • What is the Revenue Grow Rate?

Report metrics:

Report metrics

Typical report: Monthly Recurring Revenue movements

Breaking MRR into its component parts gives a useful overview of both revenue received and expenditure. When viewed as a monthly trend, it’s easy to evaluate high-level performance compared to previous months.

Report questions:

Monthly Recurring Revenue

Typical report: Customers satisfaction

Report questions:

Customers satisfaction

Typical report: Cohort analysis

Cohort analyses are powerful tools to help you understand how your subscriptions evolve over time and identify important trends in churn or retention rates.

Example

Take all new customers who start paying in a given time period (usually a single month around 6–12 months in the past) and analyze how they develop over a period of time (usually 6–12 months). In this example, we can see that month two shows significant churn rates.

% of churned customers in lifetime month

Our clients

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