What are the best BI tools and examples for measuring ROI?

There are various Business Intelligence (BI) tools available in the market, each with its own strengths and features for measuring return on investment (ROI). Here is a list of popular BI tools: Tableau: A powerful and widely used data visualization and analytics platform that enables users to create interactive and shareable dashboards. It supports data integration from various sources and helps in analyzing and visualizing key performance indicators (KPIs). Microsoft Power BI: A user-friendly BI tool that integrates with various Microsoft products, offering robust data visualization, self-service analytics, and collaboration capabilities. Power BI allows users to create insightful reports and dashboards with a wide range of data.

BI tools make ROI analysis easier by visualising key metrics & KPIs like sales amount, growth, costs, profit, conversions & etc. They allow unique ROI calculations and customisable dashboards, allowing for data-driven decision-making. So, some top BI tools for analysing ROI are: Microsoft Power BI: Integrates well with the Microsoft environment, has powerful data visualisation features, & offers a free desktop version. Tableau: has an easy-to-use interface & great data visualisation, making it ideal for discovering & conveying findings. Looker: is a secure & scalable platform focusing on data governance & collaboration. Google Analytics: Free for basic website analysis; user behaviour & conversions are recorded.

Several business intelligence (BI) tools excel in measuring return on investment (ROI) across various business functions. Ex: Tableau: Tableau is a powerful data visualization tool that allows users to create interactive dashboards and reports to analyze and visualize data. Microsoft Power BI: Microsoft Power BI is a comprehensive BI platform that enables users to connect to various data sources, create dynamic dashboards, and perform advanced analytics. Google Analytics: Google Analytics is a web analytics tool that provides valuable insights into website performance, user behavior, and marketing effectiveness. SAP BusinessObjects: It is a suite of BI tools that provides robust capabilities for reporting, analytics, and data visualization.

Power BI: Microsoft Power BI offers a cost-effective solution with strong integration capabilities, particularly for organizations already using Microsoft products. Its self-service analytics empower users to create and share reports easily, contributing to efficiency gains and informed decision-making.

In my opinion, all of the BI tools some way or the other had its influences derived from spreadsheet applications. Firstly, start off with a subset of data ( assuming structured data from multiple sources ) as one validates data quality, perform data integration and explore results. Never ever, jump into analysis of the entire data set as the burden of its volume will slow down the analysis purpose. For example, if you have periodic data ( say 10 years ) break it down in chunks of 1-2 years , start from the latest and then moved historically will be a huge time saver. Another potentially impactful approach I apply is to make the end user / business stakeholders accountable for the data quality while supporting them in its cleansing.

I agree, when choosing a BI tool you need to look at a tool that will help the users to drill down for insights at granular level, and also be able to slice and dice the data the way they want to read the reports... Never create static boring dashboards, they'll be very limiting. But I also disagree on "Exporting features" users must start to adopt to change, I've seen instances where beautiful and insightful dashboards were created and users still asked for them to be exported to excel ??. For excel lovers, maybe a self service portal could be considered? An Excel portal connected to a database for users to play around the data the way they please - this could also be very useful during stress reporting and for urgent ad-hoc reporting

Tableau: Tableau is known for its intuitive visualization capabilities and user-friendly interface, allowing non-technical users to create insightful dashboards and reports. This leads to faster decision-making and improved operational efficiency, contributing to a positive ROI.

I have been using Power BI for several years, and quite impressed by the ease and feature set that it provides, and ability to quickly build dashboards with several connectors. Microstrategy lacked that power to build complex dashboards with ease.

Um adendo... na análise e modelagem de dados, a chave é entender as tendências e padr?es. Aqui, ferramentas como o Python, especialmente com bibliotecas como Pandas e NumPy, ou o R, s?o excelentes para manipula??o de dados e modelagem estatística.

When selecting a BI tool for ROI measurement, prioritize robust data analysis and modeling functionality. Look for a tool capable of performing descriptive, diagnostic, predictive, and prescriptive analyses to gain insights into past, present, and future ROl trends. Ensure it supports various methods like statistics, machine learning, optimization, and simulation to test and optimize ROl scenarios. Additionally, seek features for data exploration and discovery such as querying, slicing, and dicing to uncover valuable insights efficiently

To effectively measure Return on Investment (ROI) in business, leveraging Business Intelligence (BI) tools is essential. In marketing campaign ROI analysis, tools like Google Analytics and HubSpot are valuable. They track a range of metrics, including website visits, conversion rates, and revenue generated, allowing businesses to evaluate the effectiveness of their marketing campaigns comprehensively. For example, using Google Analytics, companies can analyze metrics such as website traffic generated from campaigns, conversion rates, and resulting revenue to calculate ROI accurately.

One common use case of BI tools is measuring marketing campaign ROI. This involves evaluating the effectiveness and efficiency of various marketing efforts like email, social media, or paid ads in terms of lead generation, conversions, and revenue. To achieve this, you need a BI tool capable of integrating data from marketing platforms like Google Analytics, Facebook Ads, or Mailchimp with sales platforms like Salesforce or HubSpot. It should visualize and report KPIs such as cost per lead, cost per acquisition, customer lifetime value, and return on ad spend. Additionally, the tool should analyze and model marketing campaign ROI by comparing channels, segments, or time periods, and forecasting and optimizing budget allocation.

Aqui, é importante medir o sucesso do produto no mercado. Ferramentas como JIRA para acompanhar o progresso do desenvolvimento e Salesforce para monitorar as vendas podem ser úteis. Analisar os custos de desenvolvimento versus o lucro gerado pelo produto após o lan?amento ajuda a entender o ROI.

Similarly, in assessing Product Development ROI, tools such as Tableau and Microsoft Power BI play a crucial role. These tools enable organizations to analyze various data points, including sales revenue, customer feedback, and market trends, to evaluate the success of new products or features. For instance, by using Tableau, a company can examine sales data, customer satisfaction scores, and development costs to determine the profitability and success of a new product launch, facilitating informed decision-making in future product development initiatives.

BI tools need to integrate with commonly used toolsets in the org like Jira, Github. So a central reporting repository is available to the org.

Para mensurar o ROI do engajamento dos funcionários, eu usaria pesquisas internas e ferramentas como o SurveyMonkey ou Qualtrics para avaliar a satisfa??o e produtividade dos colaboradores. Comparar esses dados com métricas de desempenho da empresa pode revelar a rela??o entre engajamento e resultados financeiros. Fica a sugest?o!

Além das ferramentas e exemplos específicos comentados anteriormente, é importante considerar a cultura de dados na empresa. Promover uma cultura que valorize a tomada de decis?o baseada em dados e o aprendizado contínuo é t?o crucial quanto as próprias ferramentas de BI. E claro, nunca subestime a importancia das habilidades comportamentais, como comunica??o e trabalho em equipe, para interpretar e compartilhar insights de forma eficaz.

It is very important to get your data in order and arrange its validation. There are things needs to be taken care off while choosing the tool.. 1. Quality of your Data Cohort 2. Accessibility 3. Integration's availability 4. Data organizer 5. Sequencing 6. Availability 7. Complexity of data 8. Ability to analyze data in any form 9. Dashboard 10. ROI Analysis 11. Business plan on basis of data 12. Financing tools All these factors are important once you move for a tool.