Data Analytics

What Data Analytics Includes

Business intelligence covers descriptive and diagnostic analysis, meaning dashboards, reports and visualizations that show performance and explain variations by customer, product, channel, region and team. Advanced analytics covers predictive and prescriptive analysis, such as churn risk, demand and sales forecasts, customer segmentation and recommendations for the next best action.

The two are connected through the quality of the data. Forecasts are only as good as the definitions and sources underneath them, and a dashboard is only used when every area agrees on what a customer, an order or a lead is. For that reason we treat data preparation, definitions and governance as part of the service and not as a technical detail.

The work follows four steps. We agree on the decisions and questions to be answered, we collect and organize the sources and define the indicators, we build the analysis and the dashboards for each audience, and we set a review routine in which findings become actions with an owner and a date.

Analytics creates value when a leader can name the decision it changed.

Benefits of Data Analytics

Analytics matters when it changes how the company allocates effort and money. These are the results our clients look for.

Decisions based on one set of numbers. Shared definitions and a single source for key indicators move meetings from discussing whose figures are right to deciding what to do.

Earlier warning of problems and opportunities. Churn indicators, pipeline signals and demand patterns show up before they appear in results, so the company can act while there is still time.

Better use of marketing, sales and service resources. Knowing which segments, channels and offers produce the best return lets leaders move budget and effort to where it works.

Lower cost through process insight. Analysis of operations highlights delays, rework and inefficiencies, and gives finance a basis for deciding where to improve.

Deeper knowledge of the customer. Behavior, feedback and purchase history combine into a view of preferences and needs that improves attraction, conversion, retention and repurchase.

Find out which decisions in your company would improve with better data.

Our Data Analytics Approach

ICX starts from the business decision and works backward to the data. We ask what the leadership team needs to decide in the next quarters, and only then define the indicators, sources and models that support those decisions.

The ICX Maturity Model assesses how your organization collects, governs and uses data today and what the next level requires. The ICX Process Transformation Framework maps the target operating model and the processes that produce the data, so that every indicator has a clear owner. The ICX Executive Blueprint connects processes, technology, business rules and KPIs in one view. ICX Compass turns the diagnosis into a roadmap, and the ICX Transformation Framework guides adoption so that teams use the new reports in their weekly routine. Where pricing or costing decisions are involved, we apply Pricing IQ and Costing IQ.

We build on the tools you already use, such as Power BI, HubSpot and Salesforce, and we can operate the solution for you through CX Intelligence, our managed analytics service.

Tell us which decisions you want to make with better data and we will outline the path.

Data Analytics Use Cases

When a company needs data analytics

Customers are leaving and the reasons are not clear. Analytics identifies the behaviors and service experiences that come before churn, so retention actions can target the right accounts.

Conversion is low and the journey is hard to read. Behavior and funnel analysis show where prospects drop out and what differentiates those who buy.

A new digital product or market is being planned. Market, customer and pricing data estimate demand and show which segments and regions justify the investment.

Every area reports different numbers. A common data model and shared indicator definitions give the leadership team a single version of performance.

Customer feedback arrives in volume and nobody can use it. Text and sentiment analysis turn comments and surveys into a ranked list of improvements.

Costs are rising and the causes are unclear. Operational and cost analysis locate delays, rework and low return activities, and quantify what fixing them is worth.

What data analytics gives each leader

CEO. A short set of indicators on growth, margin, customers and risk, with forecasts that support strategic and budget decisions.

CFO. Reliable figures on profitability by customer, product and channel, and models that estimate the financial impact of each decision.

CMO. Segmentation, campaign return and customer behavior insights that guide where to invest to attract and convert.

CSO and sales leadership. Pipeline visibility, forecast reliability and identification of the prospects and accounts with the highest potential.

CCO and head of customer service. Service performance, satisfaction and churn signals by team and segment, to plan capacity and prevent loss.

Want to know which of these cases applies to your company?