Consumer Analytics

Optimize marketing, cut costs, and boost retention by understanding customer behavior for smarter decisions and product growth.

Business context

Although digital technology feels ubiquitous, it has only started transforming industries. As it advances, the impact on revenues, profits, and business opportunities will be profound, reshaping how companies operate.

Companies see revenue boost with consumer analytics by

5-10%

Consumer analytics boosts conversion rates by

5-15%

Process

Becoming data-driven is a journey

Switching your prioritises to your data is like changing how you eat: if you want sustainable effects, it’s a lifestyle change, not a one-ff

01.

Understand your business objectives

Grasping the business context – strategic goals, objectives processes
Key stakeholders engagement and objectives

02.

Define Data Goal and KPI’s

Strategic direction for data strategy aligned with business
Definition of business measures and their cross-alignment
Setting KPI’s for data & analytics

03.

Assess Current State

Holistic assessment of data: sources, storage, integration, quality, consumption
Data strategy execution feasibility study and technology gap

04.

Roadmap Preparation

HoIdentification od necessary data initiatives (projects)
Prioritization of tasks
Timeline
Resources allocation and potential gap

05.

Management Change

Ensuring adoption – involvement of stakeholders across the organisation creating awareness and focusing on quick benefits
Proper communication to address potential resistance and foster positive attitude
Aligning culture and behaviour shifting it towards data-driven mindset

Predict and boost

You can get deep insights into your customer base, enabling data-driven decisions that drive growth and enhance customer experiences. Using advanced analytics, we help predict customer behavior, refine marketing strategies, and boost operational efficiency. Our tailored solutions provide actionable insights to achieve measurable results aligned with your business needs.

Key Features

Customer Segmentation

Identify and target distinct customer groups based on behavior, preferences, and demographics for more effective marketing.

RFM Analysis

Evaluate customer value by analysing Recency, Frequency, and Monetary value to tailor retention strategies and increase engagement.

Predictive Analytics

Forecast future customer behavior and trends using historical data, allowing for proactive decision-making and strategy adjustments.

Conversion Rate Optimization (CRO)

Analyse and optimize user interactions on your website or app to improve conversion rates and boost sales.

Customer Lifetime Value (CLTV) Analysis

Calculate and enhance the long-term value of your customers through targeted strategies and personalized offers.

Churn Prediction

Identify at-risk customers and implement retention strategies to reduce churn and maintain a loyal customer base.

Sentiment Analysis

Monitor and analyse customer feedback and sentiment to improve product offerings and customer service.

Services

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