The Most Important Metric for Sales Leaders in Subscription Businesses to Track and Use to Drive Revenue Growth

Business Intelligence, Big Data Management, Data Science

Article | May 2, 2023

The top-performing companies use data to navigate their way, and there's absolutely no reason why you shouldn't do the same with your business choices. Key performance indicators (KPIs) in business intelligence enable you to get insight into the overall health of your organization, any of your departments, or even how your consumers view your company. And you don't have to play the BI game manually anymore. You only need to invest in a good business intelligence platform to weave the magic figures for you, a feat that was formerly extremely constrained or even forbidden. If you are knowledgeable enough, you should be able to determine which business intelligence tools are best suited to your particular requirements. In this article, we will provide some of the most important business intelligence key performance indicators (KPIs) to give you a head start in analyzing how your company aligns with the objectives you have set for it at any point in time. Business Intelligence Key Performance Indicators for Evaluating Business Strategies Financial Metrics The most important metric of all. To calculate your financial metrics, you must look at your cash flow, balance sheet, and income statement using a tool such as your accounting software. Any of these criteria should tell you whether your company is financially sound, which indicates it is producing income and managing its finances well. If you want to push your company on a new growth path or spark the attention of possible investors, you will offer them these financial KPIs as evidence of investment value. Example: Liquidity Ratio Net Income vs. Net Earnings Working Capital Debt to Equity Ratio Marketing Metrics In terms of business effectiveness, marketing metrics rank second only to financial metrics. Marketing metrics show the data that tells you if your most recent marketing initiatives are achieving the results you expected. Capable marketing software tools must provide you with values, such as your new content strategy riding your most recent marketing initiatives across numerous platforms. Example: Customer Acquisition Cost (CAC) Conversion Rate Average Spend Per Customer Project Management Metrics If your finances and marketing expenses are in order, it could simply be because your production departments are working hard to complete projects on time or ahead of schedule, under budget, and while keeping both clients and employees satisfied. But what should be measured to know where everything moved at the end of the day or year? As a company owner or business leader, you should consider your productivity, profit margins, ROI, customer satisfaction, and earned value, among other things—all of which can be easily obtained from any of the top project management systems. Example: Return on Investment (ROI) Productivity Customer Service Metrics When you consider that 89% of U.S. consumers have moved to a company competitor after a bad experience, it is evident that any customer service metrics have to go beyond operational information and include how your customer service team engages with your customers. Experience data acknowledges the personal human aspect at the heart of company and customer relationships, enabling you to discover how your consumers value their interactions with your customer service executives. Example: Customer Effort Score (CES) Net Promoter Score (NPS) Closing Lines Business intelligence is an essential technology that provides crucial information about a company's operations. Identifying which aspects of your organization are performing well is one thing; ensuring that they continue to do so while addressing those that are struggling to stay up and meet your aims is another. Business intelligence solutions allow you to assess performance, identify shortcomings, and develop plans to increase workflow effectiveness and customer engagement.

Performance Management

Article | May 30, 2023

Learn, re Learn and Unlearn The times we are living in, we have to upgrade ourselves constantly in order to stay afloat with the industry be it Logistics, Traditional business, Agriculture, etc.. Technology is constantly changing our lives the way we used to live, living and will live. Anyone who thinks technology is not their cup of tea then I would say he /she will have no place in the world to live. It’s a blessing or curse on human race, only time will tell but effects are already surfacing in the market in the form of Job cut, poverty, some roles are no longer needed or replaced with. Poor is getting poorer and rich is getting richer. Covid19 has not only brought the curse on human race but it has been a blessing in disguise for Tech giants and E-commerce. Technology not only changing the business but every human’s outlook towards life, family structure, the globalization of talents etc. It is nerve wrenching to imagine just what the world will look like in coming 20 years from now. Can all of us adapt to learn, re learn and unlearn quote? Or we have to depend upon countries/Governments to announce Minimum Wage to sustain our basic needs? Uncertainties are looming as the world is coming closer due to technology but emotionally going far. It’s sad to see children, colleagues communicating via emails and messages in the same home and office. Human is losing its touch and feel. Repercussion to resists of learning, unlearning and relearning can bring down choices to none in the long run. Delay in adapting to change can be increasingly expensive as one can lose their place in a world earlier than one think. From 1992, where fewer people used to have facility of internet around , People used to stay in jobs for life but same people are now not wanted in the jobs when they go for interview as they lack in experience just because they have been doing what they were doing in one job without exposing themselves to the world’s new requirement of learn , re learn and unlearn. Chances of this group, getting a job will be negative. World has thrown different types of challenges to people, community, jobs, businesses , those people used to be applauded for remaining On one job for life ,same group of people are looked differently by corporate firms as redundant due to technology. So should people keep changing jobs after few years to just get on to learn, re learn and unlearn or continue waiting for their existing companies to face challenges and go off from the market? Only time and technology will determine what is store for human race next. According to some of the studies, its shown the longer the delay in adopting technology for any given nation, the lower the per capita income of that nation. It shows extreme reliance on Technology but can all of us adopt to the technology at the same rate as its been introduced to us? Can our children or upcoming next generations adopt technology at same scale? Or future is Either Technology or nothing, in Short Job or Jobless there is no in between option? Stephen Goldsmith, director of the Innovations in Government Program and Data-Smart City Solutions at the John F. Kennedy School of Government at Harvard University, said that in some areas, technological advancements have exceeded expectations made in 2000. The Internet also has exploded beyond expectations. From 2000 to 2010, the number of Internet users increased 500 percent, from 361 million worldwide to almost 2 billion. Now, close to 4 billion people throughout the world use the Internet. People go online for everything from buying groceries and clothes to finding a date. They can register their cars online, earn a college degree, shop for houses and apply for a mortgage but again same question is arising , Can each one of us at the same scale use or advance their skill to use technology or we are leaving our senior generations behind and making them cripple in today’s society? Or How about Mid age people who are in their 50s and soon going to take over senior society , Can they get the job and advance their skill to meet technology demands or learn, unlearn and re learn or Not only pandemic but even Technology is going to make human redundant before their actual retirement and their knowledge, skill obsolete. There should be a way forward to achieve balance, absolute reliance on Technology is not only cyber threat to governments but in long term, Unemployment, Creating Jobs or paying minimum wage to unemployed mass will be a huge worry. At the end of the day, humans need basic and then luxury. Technology can bring ease of doing business, connecting businesses and out flows, connecting Wholesalers to end users but in between many jobs, heads will be slashed down and impact will be dire. Therefore Humans have to get themselves prepared to learn, unlearn and re learn to meet today’s technology requirement or prepare themselves for early retirement.

Business Intelligence, Big Data Management, Big Data

Article | July 18, 2023

The COVID-19 compelled organizations utilizing traditional analytics methods to accept digital data analytics platforms. The pandemic has also accelerated the digital revolution, and as we already know, data and analytics with technologies like AI, NLP, and ML have become the heart of this digital revolution. Therefore, this is the perfect time to break through data, analytics, and AI to make the most of it and stay a step ahead of competitors. Besides that, Techjury says that by 2023, the big data analytics market is expected to be worth $103 billion. This shows how quickly the field of data analytics is growing. Today, the data analytics market has numerous tools and strategies evolving rapidly to keep up with the ever-increasing volume of data gathered and used by businesses. Considering the swift pace and increasing use of data analytics, it is crucial to keep upgrading to stay ahead of the curve. But before we explore the leading data analytics trends, let's check out some data analytics use cases. Data Analytics Use Cases Customer Relationship Analytics One of the biggest challenges is recognizing clients who will spend money continuously for a long period purchasing their products. This insight will assist businesses in attracting customers who will add long-term value to their business. Product Propensity Product propensity analytics combines data on buying actions and behaviors with online behavioral indicators from social media and e-commerce to give insight into the performance of various campaigns and social media platforms promoting the products and services of your company. This enables your business to forecast which clients are most likely to purchase your products and services and which channels are most likely to reach those customers. This lets you focus on the channels that have the best chance of making a lot of money. Recommendation Engines There are recommendations on YouTube, Spotify, Amazon Prime Videos, or other media sites, "recommendations for you." These customized recommendations help users save time and improve their entire customer experience. Top Data Analytics Trends That Will Shape 2022 1. Data Fabrics Architecture The goal of data fabric is to design an exemplary architecture and advise on when data should be delivered or changed. Since data technology designs majorly rely on the ability to use, reuse, and mix numerous data integration techniques, the data fabric reduces integration data technology design time by 30%, deployment time by 30%, and maintenance time by 70%. "The data fabric is the next middleware." -ex-CTO of Splunk, Todd Papaioannou, 2. Decision Intelligence Decision intelligence directly incorporates data analytics into the decision process, with feedback loops to refine and fine-tune the process further. Decision intelligence can be utilized to assist in making decisions, but it also employs techniques like digital twin simulations, reinforcement learning, and artificial intelligence to automate decisions where necessary. 3. XOps With artificial intelligence (AI) and data analytics throughout any firm, XOps has become an essential aspect of business transformation operations. XOps uses DevOps best practices to improve corporate operations, efficiency, and customer experience. In addition, it wants to make sure that the process is reliable, reusable, and repeatable and that there is less technology and process duplication. 4. Graph Analytics Gartner predicts that by 2025, 80% of data and analytics innovation will be developed with the help of graphs. Graph analytics uses engaging algorithms to correlate multiple data points scattered across numerous data assets by exploring relationships. The AI graph is the backbone of modern data and analytics with the help of its expandable features and capability to increase user collaboration and machine learning models. 5. Augmented Analytics Augmented Analytics is another data-trend technology that is gaining prominence. Machine learning, AI, and natural language processing (NLP) are used in augmented analytics to automate data insights for business intelligence, data preparation, discovery, and sharing. The insights provided through augmented analytics help businesses make better decisions. According to Allied Market Research, the worldwide augmented analytics market is expected to reach $29,856 million by 2025. 6. Self-Service Analytics-Low-code and no-code AI Low-code and no-code digital platforms are speeding up the transition to self-service analytics. Non-technical business users can now access data, get insights, and make faster choices because of these platforms. As a result, self-service analytics boosts response times, business agility, speed-to-market, and decision-making in today's modern world. 7. Privacy-Enhancing Computation With the amount of sensitive and personal data being gathered, saved, and processed, it has become imperative to protect consumers' privacy. As regulations become strict and customers become more concerned, new ways to protect their privacy are becoming more important. Privacy-enhancing computing makes sure that value can be extracted from the data with the help of big data analytics without breaking the rules of the game. 3 Ways in Which the C-Suite Can Ensure Enhanced Use of Data Analytics There are many businesses that fail to realize the benefits of data analytics. Here are some ways the C-suite can ensure enhanced use of data analytics. Use Data Analytics for Recommendations Often, the deployment of data analytics is considered a one-time mission instead of an ongoing, interactive process. According to recent McKinsey research, employees are considerably more inclined to data analytics if their leaders actively commit. If the C-suite starts using analytics for decision-making, it will set an example and establish a reliability factor. This shows that when leaders rely on the suggestions and insights of data analytics platforms, rest of the company will follow the C-suite. This will result in broad usage, better success, and higher adoption rates of data analytics. Establish Data Analytics Mind-Sets Senior management starting on this path should learn about data analytics to comprehend what's fast becoming possible. Then they can use the question, "Where might data analytics bring quantum leaps in performance?" to promote lasting behavioral changes throughout the business. A senior executive should lead this exercise with the power and influence to encourage action throughout each critical business unit or function. Use Machine Learning to Automate Decisions The C-suite is introducing machine learning as they are recognizing its value for various departments and processes in an organization either processing or fraud monitoring. 79% of the executives believe that AI will make their jobs more efficient and manageable. Therefore, C-level executives would make an effort to ensure the rest of the organization follows that mentality. They will have to start by using machine learning to automate time-consuming and repeatable tasks. Conclusion From the above-mentioned data analytics trends one can infer that it is no longer only a means to achieve corporate success. In 2022 and beyond, businesses will need to prioritize it as a critical business function, accurately recognizing it as a must-have for long-term success. The future of data analytics will have quality data and technologies like AI at its center. FAQ 1. What is the difference between data analytics and data analysis? Scalability is the key distinguishing factor between analytics and analysis. Data analytics is a broad phrase that encompasses all types of data analysis. The evaluation of data is known as data analysis. Data analysis includes data gathering, organization, storage, and analysis techniques and technologies. 2. When is the right time to deploy an analytics strategy? Data analytics is not a one-time-only activity; it is a continuous process. Companies should not shift their attention from analytics and should utilize it regularly. Usually, once companies realize the potential of analytics to address concerns, they start applying it to various processes. 3. What is platform modernization? Modernization of legacy platforms refers to leveraging and expanding flexibility by preserving consistency across platforms and tackling IT issues. Modernization of legacy platforms also includes rewriting a legacy system for software development.

Article | April 30, 2020

In the present complex and volatile market with data as a nucleus, analytics becomes a core function for any enterprise that relies on data-driven insights to understand their customers, trends, and business environments. In the age of digitization and automation, it is only sensible to make a move to analytics for a data-driven approach for your business. While a host of sources including Digital clicks, social media, POS terminal, and sensors enrich the data quality, data can be collected along various stages of interactions, and initiatives were taken. Customers leave their unique data fingerprint when interacting with the enterprise, which when put through analytics provides actionable insights to make important business decisions. Table of Contents: Business Analytics or Business Intelligence: The Difference Growth Acceleration with Business Analytics Business Analytics or Business Intelligence (BI): The Difference Business Intelligence comes within the descriptive phase of analytics. BI is where most enterprises start using an analytics program. BI uses software and services to turn data into actionable intelligence that helps an enterprise to make informed and strategic decisions. It’s information about the data itself. It’s not trying to do anything beyond telling a story about what the data is saying. - Beverly Wright, Executive Director, Business Analytics Center, Georgia Tech’s Scheller College of Business Some businesses might use BI and BA interchangeably, though some believe BI to be the know-how of what has happened, while the analytics or advanced analytics work to anticipate the various future scenarios. BI uses more structured data from traditional enterprise platforms, such as enterprise resource planning (ERP) or financial software systems, and it delivers views into past financial transactions or other past actions in areas such as operations and the supply chain. Today, experts say BI’s value to organizations is derived from its ability to provide visibility into such areas and business tasks, including contractual reconciliation. Someone will look at reports from, for example, last year’s sales — that’s BI — but they’ll also get predictions about next year’s sales — that’s business analytics — and then add to that a what-if capability: What would happen if we did X instead of Y. - CindiHowson, research vice president at Gartner A subset of business intelligence (BI), business analytics is implemented to determine which datasets are useful and how they can be leveraged to solve problems and increase efficiency, productivity, and revenue. It is the process of collating, sorting, processing, and studying business data, and using statistical models and iterative methodologies to transform data into business insights. BA is more prescriptive and uses methods that can analyze data, recognize patterns, and develops models that clarify past events, make future predictions, and recommend future discourse. Analysts use sophisticated data, quantitative analysis, and mathematical models to provide a solution for data-driven issues. To expand their understanding of complex data sets, and artificial intelligence, deep learning, and neural networks to micro-segment available data and identify patterns they can utilize statistics, information systems, computer science, and operations research. Let’s discuss the 5 ways business analytics can help you accelerate your business growth. READ MORE: HOW TO OVERCOME CHALLENGES IN ADOPTING DATA ANALYTICS Growth Acceleration with Business Analytics 1. Expansion planning Let’s say you’re planning an expansion opening a branch, store, restaurant, or office in a new location and have accumulated a lot of information about your growing customer base, equipment or other asset maintenance, employee payment, and delivery or distribution schedule. What if we told it is possible to get into a much detailed planning process with all that information available? It becomes possible with business analytics. With BA you can find insights in visualizations and dashboards and then research them further with business intelligence and reports. Moreover, you can interact with the results and use the information to create your expansion plan. 2. Finding your audience You’re right to examine your current customer data but you should also be looking into the customer sentiments towards your brand and who is saying what, and in what parts of the region. Business Analytics offers social media analysis so you can bring together internal and external customer data to create a profile of your customers, both existing and potential. Thus, you have prepared an ideal demographic, which can be used to identify people that are most likely to turn to your products or services. As a result, you have successfully deduced the area that offers the most in terms of expansion and customer potential. 3. Creating your business plan The real-time interaction with your data provides a detailed map of the current progress as well as your performance. Business Analytics solutions offer performance indicators to find and forecast trends in sales, turnover, and growth. This can be used in the in-depth development of a business plan for the next phase of your thriving franchise. 4. Developing your marketing campaign With Business Analytics, you’re capable of sending the right message to the audience most eager to try your product/service as part of a marketing campaign. You’re empowered to narrow down branding details, messaging tone and customer preferences, like the right offers that will differentiate you from the other businesses in the area. Using BA, you have gained a competitive edge by making sure you offer something new to your customers and prospects. It enables you to use your data to derive customer insights, make insight-driven decisions, do targeted marketing, and make business development decisions with confidence. 5. Use predictive insights to take action With analytics tools like predictive analytics, your expansion plans are optimized. It enables you to pinpoint and research about the factors that are influencing your outcomes so that you can be assured of being on the right track. When you can identify and understand your challenges quickly and resolve them faster, you improve the overall business performance resulting in successful expansion and accelerated growth. READ MORE: WHAT IS THE DIFFERENCE BETWEEN BUSINESS INTELLIGENCE, DATA WAREHOUSING AND DATA ANALYTICS