Every business collects data, but not every business uses it effectively.
Your CRM is packed with contact records, your marketing automation platform tracks every click and conversion, and your sales team logs countless interactions.
Yet despite this wealth of information, many organisations struggle to answer basic questions.
Which prospects are most likely to convert?
What’s causing pipeline stagnation?
Where should we focus our resources next quarter?
The challenge isn’t a lack of data; it’s the absence of meaningful insights. Raw data without context or interpretation won’t move the needle. Numbers in a spreadsheet don’t help you make better decisions, but insights from that data do.
In 2025, thriving companies will master transforming complex datasets into a clear, strategic direction. This means moving beyond dashboards that display metrics to frameworks that reveal what those metrics mean for your business—and more importantly, what you should do about them.
Ready to get insights from your data? Here are the six steps to follow.
Every insight initiative should begin with specific business questions that align with strategic objectives.
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Your insights will be unreliable if your information is scattered across multiple systems or contaminated with errors. Centralise your data by doing the following:
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Choose analytical methods that match your business questions and data types. Different insights require different approaches.
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Choose visual formats that impress viewers and help stakeholders get the point quickly.
The goal is immediate comprehension, not artistic beauty, and these tips can help:
A marketing team increased their reporting impact by 50% after switching from complex multi-metric dashboards to simple, focused visuals that highlighted one key insight each.
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Raw analysis results aren’t insights until you understand what they mean and why they matter for your business.
Insights only create value when they can influence decisions and drive measurable changes in business performance. Here are a few tips to turn your insights into actions:
Data insights are actionable findings derived from analysing raw data that help you understand patterns, predict outcomes, and make informed business decisions.
Think of it this way: Data is the ingredient, insights are the recipe. You might have flour, eggs, and sugar (your raw data), but without understanding how to combine them properly, you won’t create anything valuable (your insights).
Insights provide the knowledge and context needed to leverage the raw data into action.
Let’s look at an example. Your sales team has been increasing outreach to generate more pipeline. They’re making more cold calls and sending more cold emails, but they’re successfully connecting with fewer leads and booking fewer meetings.
You comb through the data to make sense of this. You realise that while outreach is up, personalisation has decreased, and some reps were prioritising quantity over quality. This insight can help you create a new training plan to help team members find ways to scale outreach without sacrificing personalisation.
The business landscape has fundamentally shifted towards data-driven decision-making, making insights more critical.
Ultimately, insight-led organisations outperform reactive ones in sales, product development, and marketing.
Data is raw and unprocessed, and may include numbers, records, and facts without interpretation.
Insights are the conclusions drawn from analysing that data, providing understanding of what those numbers mean and what actions you should take.
A few common examples of business data insights include:
Get better insights from your CRM data with these tips:
Popular business intelligence tools include Power BI for Microsoft-integrated environments, Tableau for advanced visualisation, and Looker for embedded analytics.
CRM-specific tools like Salesforce Analytics and HubSpot Reports provide pre-built sales and marketing data insights.
Tools like Talend handle integration and cleaning for data preparation, while platforms like Cognism enrich datasets with additional context. The best tool depends on your technical requirements, budget, and existing technology stack.
The proper framework is a great start, but the right tools can be invaluable when operationalising data insights. Let’s look at the best tools for data quality and insight generation.
Best for: Enriching CRM data to unlock buyer intent and firmographic information.
Cognism provides comprehensive B2B data enrichment that fills gaps in your existing customer and prospect records, helping you maintain exceptional sales data quality.
It's particularly valuable for sales and marketing teams that need a complete picture of their target accounts.
Cognism offers real-time data verification, GDPR-compliant contact information, and advanced search capabilities that help identify high-intent prospects. Integrations with major CRM platforms also make it easy to enhance your existing data automatically.
Best for: Seamless dashboarding for the Microsoft ecosystem.
Power BI is a business intelligence tool that integrates data from multiple Microsoft applications (including Excel, Dynamics, and SharePoint) while offering robust visualisation capabilities.
It's a powerful option for organisations already using Microsoft Office 365, providing natural language queries, automated insights, and collaborative reporting features.
The tool handles both simple dashboards and complex analytical models, making it suitable for teams with various technical expertise levels.
Best for: Customisable data visualisations for enterprise teams.
Tableau offers unparalleled flexibility in creating complex visualisations and supports advanced statistical analysis.
It’s ideal for organisations with dedicated data teams who must create highly customised reports and interactive dashboards. The platform excels at handling large datasets and provides extensive integration options for diverse data sources that can prevent silos and data decay.
Best for: Marketing and sales performance insights.
HubSpot Reports has pre-built reports and dashboards specifically designed for inbound marketing, sales pipeline analysis, and customer lifecycle tracking.
It’s particularly valuable for teams already using HubSpot’s CRM and marketing automation tools, offering seamless data flow and context-aware insights that don’t require technical setup.
Best for: Deep dive into pipeline and sales performance data.
Salesforce CRM analytics provides sophisticated forecasting, opportunity analysis, and insights into sales teams’ performance.
It’s designed specifically for Salesforce users who need to understand sales patterns, pipeline health, and revenue forecasting. The platform offers AI-powered insights and predictive analytics that help sales teams focus on the most promising opportunities.
Best for: Embedded analytics platform offering scalable dashboards and data exploration capabilities.
Looker is particularly strong for organisations that need to embed analytics into their existing applications or provide self-service analytics to non-technical users.
It offers a unique modelling layer, which helps ensure consistent definitions across all reports. The platform also supports real-time data exploration without requiring technical SQL knowledge, making it a good fit for teams with limited technical resources.
Best for: Free, flexible dashboard solution ideal for digital marketing teams and smaller organisations.
Google Looker Studio tool integrates seamlessly with Google's marketing and analytics platforms (including Google Analytics, Google Ads, YouTube) while also connecting to external data sources. The free version of the tool is relatively robust, making it a good option for budget-conscious teams, though a paid version is available.
It's perfect for teams that need professional-looking reports, though it has limitations compared to enterprise-grade solutions.
Best for: Data integration and preparation platform that cleanses and transforms data for analytics.
Talend handles the complex work of connecting separate data sources, identifying inconsistencies, and preparing datasets for analysis.
It's helpful for organisations with data quality issues or multiple systems that need to be combined for comprehensive insights. The platform supports both batch and real-time data processing.
Best for: Email and CRM data quality platform that improves accuracy for more reliable reporting.
Validity focuses specifically on ensuring contact data accuracy, which is crucial for sales and marketing insights.
It provides email verification, data cleansing, and ongoing monitoring to maintain database quality. This foundation work is essential for generating trustworthy insights about customer engagement and campaign performance.
Best for: Cloud data warehouse that powers business intelligence tools with scalable data storage and processing.
Snowflake provides the underlying infrastructure for enterprise-scale analytics, handling massive datasets while maintaining query performance.
It’s particularly valuable for organisations with complex data requirements or those planning to implement advanced analytics and machine learning capabilities.
The shift from collecting data to extracting insights is essential for businesses that want to improve their decision-making. To understand or optimise performance on marketing tactics, customer success programs, or new sales initiatives, you must look beyond the numbers to know what they mean.
Businesses that can quickly extract meaningful insights from emerging data patterns and translate those insights into immediate action have a competitive advantage. Speed and accuracy are now everything, allowing you to pivot rapidly in an agile marketplace.
Strong data quality yields the best insights. Book a demo to see how Cognism can improve data accuracy today.