Business intelligence in marketing:
end-to-end solution overview

Business intelligence in marketing: end-to-end solution overview

June 23, 2023

Business intelligence for marketing: top 7 use cases

Business analytics is a solid foundation for many marketing activities. Let's have a look at how business intelligence is applied in the marketing field.

Business intelligence for marketing: top 7 use cases

Companies can target the right segments with the right message at the right time by collecting and processing customer demographic information, preferred product lines and services, interaction patterns, and purchasing habits from multiple channels, including the company’s website, corporate applications, social media platforms, and third-party sources.

The marketing team can track customer lifetime value to focus their efforts more effectively, target the most profitable customers, and identify new audiences worth engaging with.

Marketing BI adopters can determine the best-performing marketing tactics to focus on the most effective methods, abandon or revamp marketing strategies, optimize marketing budget allocation, and identify cost-saving opportunities.

Using BI, marketers can get a 360-degree customer view with data from different heterogeneous sources and use it to personalize multi-channel interactions and marketing activities, allocate marketing efforts more wisely, and create customer journey maps.

Marketers can gain a deep understanding of the target market, the most profitable customer segments, a potential customer base, customer feedback and sentiment, and competitor offering and let the product management team know about the spotted gaps in the market.

Marketing specialists can easily research market trends and competitor marketing campaigns and conduct an advanced analysis of a competitor’s audience. Using this information, they can assess competitors’ marketing practices for specific channels, find new customer segments, and adjust current marketing efforts (change pricing, increase marketing spend for a particular channel, target different demographics, etc.).

Companies can use disparate data on marketing performance (website visits, goal completion rates, leads, conversion rates, and ROI) to create new campaigns, merchandising activities, and loyalty programs or refine the existing ones.

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Essential integrations for BI in marketing

Here are the most commonly used data sources in marketing that are worth integrating with marketing BI:

CRM software

Customer service software

Email marketing software

Web analytics and paid ads platforms

SEO tools

Mobile marketing software

Social media analytics platforms

Market research platforms

Key integration options

CRM software

  • Personal customer data (age, sex, marital status, address, job title)
  • Contact data
  • Purchasing history
  • Notes/observations about the customer
  • Customer characteristics and behavior patterns
  • Customer complaints

Real-life example of BI for marketing

The customer is a leading digital media company that uses its marketing platform to promote its clients via organic and paid promotion methods. The company decided to revamp its data analysis and visualization processes to monitor and predict ad campaigns’ progress more effectively. Itransition developed a set of analytics optimization solutions equipped with dynamic dashboards and customizable campaign-specific benchmarks, which has helped the customer make realistic forecasts and real-time predictions, as well as monitor advertising campaign performance through user-friendly dashboards. With a newly implemented analyticбs solution, the customer managed to improve benchmark achievement by 8x and reduce overspending by 7x.


improved benchmark achievement

Top business intelligence tools for marketing

Traditionally, full-scale business intelligence solutions for marketing are built with the following software:

  • Data integration and quality management software to help manage and automate data gathering, transformation, cleansing, and other tasks and prepare data for storage and analysis.?
  • Database management systems for structuring and storing consolidated data in a central data warehouse for further analysis.
  • BI tool and data analytics software for analyzing, delivering, and visualizing business information to help marketing teams monitor KPIs, track progress, and spot inefficiencies.

Here, we describe top business intelligence tools for marketing, each among leaders in the Gartner Magic Quadrant and The Forrester Wave reports.

Completeness of visionAbility to executeChallengersGoogleDomoNiche playersMicroStrategyPyramid AnalyticsIncortaZohoAmazon Web ServicesAlibaba CloudLeadersQlikMicrosoftSalesforce (Tableau)VisionariesSAPOracleSisenseThoughtSpotTIBCO SoftwareSASYellowfinTelliusIBM

Key features
  • Connects to hundreds of data sources in the cloud and on-premises, including Salesforce, Google Analytics, Excel
  • Native integration with Microsoft products, including Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure SQL database, Azure Machine Learning Studio
  • Support for DAX, Power Query, SQL, R, and Python
  • Advanced AI (text analytics, image detection, automated ML)
  • Self-service data preparation, analysis, reporting, and visualization
  • Pre-built and custom visuals
  • NLP capabilities
  • Team commenting and content subscriptions
  • Mobile support
  • Embedded BI
  • Row-level and object-level security, user authentication, data encryption, data sensitivity labels

Power BI Desktop


Power BI Pro

$9.99 per user/month

Power BI Premium

$20 per user/month or $4,995 per capacity/month with an annual subscription

Free trial

2-month free trial for each new user

    • Data handling capacity for a free version is relatively limited

    Marketing BI software selection checklist

    The BI software market is mature, so while choosing an optimal marketing BI platform, companies can be selective and rely on their unique needs and goals. Modern BI platforms support a full analytics workflow and are easy to use due to self-service BI capabilities and augmented analytics.

    Marketing BI software selection checklist

    Here is the list of critical capabilities you should look for in a BI solution for marketing:

    • Vast data source connectivity to connect to and ingest marketing data in various formats from multiple storage platforms, both on-premises and the cloud
    • Complex data models support for comprehensive marketing analytics
    • Self-service data preparation for combining marketing data from different sources and creating analytic models without IT teams’ help
    • ML-based analytics for automatically generating analytics insights for marketing departments
    • Natural language generation and data querying for describing marketing insights found in data and querying data with business terms
    • Data visualization, including the support of common chart forms (bar/column, line/area, pie, and geographic maps) as well as highly interactive dashboards
    • Reporting capabilities to distribute reports on a scheduled basis
    • Highly interactive dashboards and visual data exploration
    • Embedded analytics capabilities to seamlessly integrate valuable insights into the marketing process
    • Security capabilities for user administration and authentication and platform access audit
    • Data governance for managing and controlling marketing data flows
    • Data catalogs to quickly access the required analytics content
    • Cloud support

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    6 reasons for investing in BI for marketing

    Effective marketing campaigns

    BI tools help marketing specialists measure promotion effectiveness and identify strategies that work best, as well as areas of improvement for low-selling products, and effectively execute their upsell and cross-sell campaigns.

    Enhanced customer experience

    Comprehensive omnichannel customer insights delivered by BI software empower marketing teams to target the audience with tailored offerings, personalize every customer interaction, and deliver the best customer experience to increase customer loyalty and CLV.

    Targeted demographics

    BI software enables effective customer segmentation and accurate customer lifetime value tracking, helping marketers to focus on the most profitable customers, timely identify new customer segments, and retain high-value customers.

    Optimized marketing spend

    BI tools can identify how advertisements, promotional activities, and executed marketing campaigns influence the bottom line. This way, marketing teams can implement the most effective marketing activities and identify areas where marketing teams can cut costs.

    Improved user productivity

    By automating manual, repetitive tasks (data inputting and cleansing, report generation), marketers can prevent inefficiency bottlenecks, prioritize more critical business workflows, and have more time for high-priority activities.

    Enhanced data security and compliance

    Integrated data security and governance capabilities help marketing specialists identify where business data resides, track data workflows, and control data access according to user roles to prevent data loss, manipulation, and sensitive data exposure.

    Common marketing BI adoption challenges and how to handle them

    While BI promises multiple tangible benefits for marketing, many companies that have invested in BI are still far from leveraging its full potential. Let’s see what are some common BI adoption stumbling blocks and how to make BI software work for your marketing department.

    Data quality issues

    Data used for marketing analytics comes from multiple heterogeneous systems, which can result in duplicates, errors, and inconsistencies. Poor data quality complicates and slows down the analytics process and compromises the validity of results.

    A comprehensive and well-setup data quality management process helps mitigate all erroneous data risks. You can:

    • Appoint a dedicated committee to manage the process of data quality management.
    • Establish an effective data quality framework in line with the company's data quality objectives.
    • Adopt data quality management software to automate data profiling, standardization, and transformation.
    • Ensure that employees working with data understand the importance of proper data quality and actively participate in data quality management activities.
    Self-service BI issues

    Data democratization driven by BI self-service capabilities can create risks of sensitive data exposure, uncontrolled software deployments, high licensing costs, and inaccurate analytics insights.

    Before implementing self-service BI software, establish a solid data governance strategy. Also, to minimize data security issues and ensure the analytics insight are viable, consider implementing the following:

    • Role-based data access and multi-factor user authentication
    • Dynamic data masking, end-to-end encryption, and sensitive data labeling
    • Continuous user activity monitoring
    • Regular risk and vulnerability assessments
    • Complete data audit trail
    User adoption issues

    After BI implementation, end users can continue using familiar tools, making new functionality and improved data capabilities useless.

    To improve the chances of BI marketing initiatives for success, you should develop a change management strategy, which includes the following:

    • Change readiness assessment to gauge how well the company will handle forthcoming changes to systems, processes, organizational structure, roles, and responsibilities.
    • Custom training for end users to help them obtain the necessary BI skills and experience.
    • Communication plans tailored to employee groups explaining the benefits of new software and how to navigate the new BI environment.
    • Communication channels to timely support end users, continuously monitor user activity and feedback and timely identify adoption problems and user resistance.

    BI implementation cost factors

    Cost factors

    Data sources – their number, integration flexibility, deployment environment

    Data for analysis – its volume, refresh frequency, structure, variability, and format

    Initial data quality and data quality requirements

    Data storage layer complexity, particularly the availability of an enterprise data warehouse, data marts, and complementary data storage

    Data analytics complexity, including the number of entities, data flow complexity, ML and AI tools, analytics streaming, and real-time data analytics

    Data visualization and reporting requirements, including embedded reporting, self-service BI, and custom visualization

    Mobile support

    Data security and compliance requirements

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    Implement BI for data-driven marketing

    Since marketing has become increasingly data-driven, BI is a staple for marketing specialists. Companies use analytics insights derived from BI software across industries to streamline the decision-making process in marketing, design better marketing campaigns, target the right audience, spot marketing trends, increase customer loyalty, and generate high ROI. Still, BI implementation is wrought with numerous challenges, so if you want to get an effective marketing BI solution that makes a difference from the get-to, consider hiring BI experts like Itransition for expert assistance.