Business Intelligence in Ecommerce: Why It’s Crucial to Ecommerce Success

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    Did you know that more than sixty percent of the world population has access to the internet? 

    According to Broadband Search, 4.79 billion people worldwide use the internet on a regular basis. 

    It has changed the way we order dinner, buy pet food, access entertainment, and, yes, even the way we look at business data. 

    This digital transformation presents e-commerce companies with a massive opportunity to build and grow successful businesses. 

    But, that opportunity is not without challenges. Customers have thousands of e-commerce businesses to choose from, and they are bombarded with ads on social media, streaming videos, and targeted emails. 

    There is a silver bullet that could make all the difference for ecommerce businesses — and it is business intelligence.  

    Here’s what you need to know about using business intelligence — even if your e-commerce business is still growing. 

    What is Business Intelligence?

    Business intelligence, often shortened to BI, is the practice of leveraging tools to access and sort data to present actionable insights about a business’s strategic and tactical goals. 

    For example, a banking company might use a BI dashboard to analyze data about complaints they receive and sort them by location, account type, or time period. This would highlight shifts in the frequency of complaints, such as an increase in a specific city, and allow the business to investigate the causes. 

    Business intelligence can be leveraged to better understand a massive amount of data from a variety of tools, including sales automation, chatbots, logistics, inventory management, or any other number of data-generating actions.

    Comparing Business Intelligence to Data Analytics

    Although business intelligence and data analytics are often used interchangeably, some nuances set them apart. 

    According to Mark van Rijmenam, the CEO and Founder of Big Data-Startups, the main difference between the two is the time the data is used to inform. 

    “The difference between Business Intelligence and Data Analytics lies in the fact that Business Intelligence helps in making business decisions based on past results while data analytics helps in making predictions that are going to help you in the future.”

    Van Rijmeman

    This chart provides a quick rundown of the difference between business intelligence and data analytics. 

    Ecommerce Business Intelligence: Bi Data Analytics Difference Chart

    Image source

    There are four main aspects of overall data analysis. Below is a quick primer on the stages and whether they fall under business intelligence or data analytics.

    1. Descriptive Analytics

    Descriptive analytics is the preliminary stage of data analysis that provides insights into “what happened.” In the context of e-commerce, descriptive analytics involves summarizing historical data to understand past trends and patterns.

    For instance, an e-commerce company can utilize descriptive analytics to review sales data from previous months or years, identify peak sales periods, analyze customer demographics, and evaluate the performance of marketing campaigns.

    E-commerce businesses can leverage tools like Google Analytics or Adobe Analytics to gain comprehensive insights into website traffic, user behavior, and product performance. By examining key metrics such as website visits, page views, bounce rates, and conversion rates, businesses can identify areas of strength and areas that require improvement.

    Descriptive analytics can help e-commerce companies segment their customer base, allowing for targeted marketing efforts and personalized shopping experiences.

    2. Diagnostic Analysis

    Diagnostic analysis delves deeper into data to determine the underlying causes of specific events or trends. It answers the question, “why did it happen?” In the e-commerce realm, diagnostic analysis enables businesses to uncover the factors influencing customer behavior and purchase decisions.

    For example, by analyzing customer feedback, order fulfillment data, and product reviews, e-commerce companies can identify issues such as shipping delays, product quality concerns, or website usability issues that may impact sales performance.

    To enhance diagnostic analysis, e-commerce businesses can implement advanced analytics techniques such as regression analysis, correlation analysis, and root cause analysis. These methods allow businesses to identify correlations between different variables and pinpoint the root causes of performance fluctuations.

    By conducting thorough diagnostic analysis, e-commerce companies can proactively address issues, optimize processes, and enhance the overall customer experience.

    3. Predictive Analytics

    Predictive analytics involves forecasting future outcomes based on historical data and statistical modeling. It aims to answer the question, “what could happen in the future?” In the e-commerce sector, predictive analytics empowers businesses to anticipate customer behavior, demand trends, and market dynamics, enabling proactive decision-making and strategic planning.

    To augment predictive analytics capabilities, e-commerce companies can leverage machine learning algorithms and predictive modeling techniques. By analyzing historical sales data, customer interactions, and market trends, businesses can develop predictive models for accurate sales forecasts, identify emerging market trends, and optimize inventory management.

    Predictive analytics can help e-commerce companies personalize marketing campaigns, recommend products to customers based on their preferences, and mitigate risks associated with demand fluctuations or supply chain disruptions.

    4. Prescriptive Analytics

    Prescriptive analytics goes beyond predicting future outcomes to recommend optimal actions to achieve desired objectives. It addresses the question, “how should we respond to events in the future?” For e-commerce businesses, prescriptive analytics offers actionable insights to optimize operational efficiency, enhance customer satisfaction, and maximize profitability.

    E-commerce companies can leverage advanced optimization algorithms and decision support systems to generate data-driven recommendations. These recommendations may include pricing strategies, inventory replenishment decisions, promotional tactics, and personalized marketing initiatives.

    By integrating prescriptive analytics into their decision-making processes, e-commerce businesses can streamline operations, minimize costs, and capitalize on growth opportunities.

    5 Main Business Intelligence Functions

    How is business intelligence used? Well, it all depends on your business, the data you have access to, and what information you want. The five main functions of BI include reporting, OLAP, analytics, data mining, and benchmarking. Here is what those mean for your e-commerce business.

    1. Reporting

    Reporting plays a crucial role in business intelligence by providing stakeholders with actionable insights derived from data analysis. In the context of e-commerce, reporting enables businesses to track key performance indicators (KPIs), monitor sales trends, and assess the effectiveness of marketing campaigns. E-commerce companies can utilize reporting tools to generate customized reports that visualize data in intuitive formats, such as charts, graphs, and dashboards.

    E-commerce businesses can implement interactive reporting functionalities that allow users to drill down into specific data subsets and explore trends at a granular level. For example, reporting dashboards can display real-time sales data, inventory levels, and customer engagement metrics, empowering stakeholders to make informed decisions in a timely manner.

    Reporting capabilities can be integrated with external data sources, such as social media analytics and customer relationship management (CRM) systems, to provide a comprehensive view of business performance.

    2. OLAP

    OLAP, or Online Analytical Processing, is a powerful technology used for multidimensional analysis and data exploration. In the e-commerce landscape, OLAP enables businesses to analyze vast datasets from multiple dimensions, such as product categories, customer segments, and geographical regions. By slicing and dicing data along different dimensions, e-commerce companies can gain deeper insights into sales trends, customer behavior, and market dynamics.

    E-commerce businesses can deploy OLAP cubes to create multidimensional data structures that facilitate complex calculations and predictive forecasting. OLAP cubes allow users to navigate through hierarchies of data dimensions and perform ad-hoc analysis to uncover hidden patterns and correlations.

    OLAP technology can support advanced analytical functions, such as trend analysis, outlier detection, and what-if scenario modeling, enabling e-commerce companies to anticipate market trends and adapt their strategies accordingly.

    3. Business Analytics

    Analytics encompasses the process of collecting data, analyzing data, and interpreting data to derive actionable insights and inform decision-making. In the e-commerce sector, analytics plays a pivotal role in understanding customer behavior, optimizing marketing efforts, and enhancing operational efficiency. E-commerce companies can leverage ecommerce analytics tools to track website traffic, measure conversion rates, and segment their customer base for targeted marketing campaigns.

    E-commerce businesses can implement predictive analytics models to forecast future sales trends, identify potential churn risks, and personalize the shopping experience for individual customers.

    By harnessing advanced business analytics techniques, such as machine learning algorithms and predictive modeling, e-commerce companies can unlock valuable insights from their data and gain competitive advantages in the market. Additionally, business analytics can be integrated with business processes to automate decision-making and drive continuous improvement initiatives.

    4. Data Mining

    Data mining involves the process of discovering patterns, correlations, and trends within large datasets to extract actionable information. In the e-commerce realm, data mining enables businesses to uncover valuable insights from diverse data sources, including customer transactions, website interactions, and social media engagement.

    E-commerce companies can utilize data mining techniques to identify market segments, predict customer preferences, and optimize product recommendations.

    E-commerce businesses can employ machine learning algorithms and artificial intelligence (AI) techniques to analyze data and uncover hidden patterns. For example, clustering algorithms can segment customers based on their purchasing behavior, while association rule mining can identify relationships between different product categories.

    By harnessing the power of data mining, e-commerce companies can gain deeper insights into customer needs and preferences, leading to more targeted marketing strategies and enhanced customer satisfaction.

    5. Benchmarking

    Benchmarking involves comparing key performance metrics and processes against industry standards or best practices to identify areas for improvement and drive organizational excellence. In the e-commerce sector, benchmarking enables businesses to evaluate their performance relative to competitors, identify strengths and weaknesses, and implement strategies for continuous improvement.

    E-commerce companies can benchmark various aspects of their operations, including website performance, customer satisfaction levels, and fulfillment efficiency.

    E-commerce businesses can leverage benchmarking data to set performance targets, track progress over time, and drive strategic decision-making. By benchmarking against industry leaders and top performers, e-commerce companies can gain valuable insights into emerging trends and best-in-class practices.

    Benchmarking can serve as a catalyst for innovation and process optimization, helping e-commerce businesses stay ahead of the competition and achieve sustainable growth.

    Business Intelligence For All Business Sizes

    Business intelligence is not just for large companies. In recent years, cloud computing has made business intelligence far more affordable for small companies. Using business intelligence software and dashboards combined with ecommerce analytics can help smaller businesses to gain insights they need to scale faster — and make them more competitive.

    E-commerce Businesses are Adopting Business Intelligence

    In 2104,  1.5 billion people shopped online. By 2021, there will be an estimated 2.14 billion online shoppers around the world. 

    That explosion of online shopping provides e-commerce companies with an opportunity — but not all businesses will be able to rise to the occasion. 

    However, the most successful e-commerce businesses are already leveraging BI to help: 

    1. Accurate Decision-Making

    Business Intelligence allows e-commerce businesses to make data driven decisions based on statistical facts, rather than guesses. For example, a company could see how many customers abandon their cart and analyze real time data to understand why.

    2. Drive Revenue

    BI gives access to sales trends based on customers’ preferences, reactions to promotions, online shopping experiences, purchasing behavior, and other patterns and trends that impact sales. All of this information can help ecommerce stores maximize revenue. 

    3. Operational Efficiency

    Business intelligence looks at all types of data and can help the e-commerce businesses uncover errors and quality issues that result in lost productivity in sales, customer attrition due to call center dissatisfaction, higher bounce rates, and so forth. This data makes it easier for companies to uncover — and fix — bottlenecks.  

    4. Gaining a Competitive Advantage

    Data helps companies understand what strategies work— and what doesn’t. Using reports and benchmarking, e-commerce businesses can uncover opportunities for improvement, providing them with a competitive edge

    5. Managing business and spotting problems 

    BI allows businesses to get a high level or detailed view of real time data. This makes it far easier to spot challenges as they arise — but before they impact the bottom line. For example, a rise in churn may be noticed when it first starts to increase, rather than after the company has lost half its income.

    Using Business Intelligence in E-commerce

    E-commerce is fast becoming a critical component of our global economy, and ecommerce business intelligence can be leveraged to help your company take advantage of that growth. 

    Here are a few of the most useful reports to better understand your business and your customers. 

    1. Inventory Report

    BI powered inventory reports can track not just what you have in inventory, but also where that inventory is located, how long it will last, and the overall value. Reports can be sorted by day, week, month, or year to inform critical supply and ordering decisions. 

    2. Sales Report

    When it comes to sales, data can make all the difference. BI can help your business track the performance of individual salespeople, the number of total leads, qualified leads, where those leads come from, and which months most sales are made. 

    3. Margin Analysis

    If you are wondering how much a specific product makes you, then you will look at data about profit margin. Using BI, you can see how margin applies across accounts, locations, channels, and much more. This data can help businesses hone in on their most profitable customers and build a business plan to increase overall profit. 

    4. Marketing Report

    Marketing strategies like PPC and SEO create a ton of data. However, that data often remains siloed in the tool that gathers it. BI allows brands to pull all that data into one tool where it can be analyzed and leveraged. 

    Tips For Integrating Your Ecommerce Business Intelligence Software

    To succeed with business intelligence (BI), it’s imperative for businesses to foster a culture of commitment and understanding across the organization regarding the importance and utilization of BI tools.

    To streamline the implementation process and maximize the benefits of BI, consider the following five tips below.

    1. Business Needs

    Ensure that the features offered by your chosen business intelligence (BI) tool align with your specific business needs and requirements before implementation. Verify compatibility for accessing and extracting data from specialized sources like PPC platforms to maximize the tool’s utility.

    2. Amount and Quality of Data Sources

    Assess the origin and integrity of your data sources meticulously. Determine the margin of error associated with your data to gauge its reliability accurately. Remember, the quality of your insights hinges on the quality of your data, emphasizing the importance of data accuracy and completeness.

    3. User Experience

    Delve into the user experience aspect while evaluating BI platforms. Prioritize platforms that offer intuitive interfaces and streamlined workflows to enhance user adoption rates. A user-friendly BI solution ensures that stakeholders can easily access and leverage insights, maximizing the value derived from your BI initiatives.

    4. Training 

    BI tools can provide a wealth of information — which can become a challenge when users don’t know how to use them. Create a training program to ensure people know how to access the data they need and make sure they understand not just how to access data, but how to apply it. This can be especially useful when looking to hire freelancers or bring in outsiders to your team. 

    5. Get Buy-In

    Everyone in the business — from executives to customer service providers — needs to be on the same page about the importance and use of BI.Focus on how business intelligence tools will make their job easier and help the business grow not just the type of data it provides access to. 

    Choosing The Right Ecommerce Business Intelligence Tool

    You want to find the right for your e-commerce business. But, there’s a problem — there are dozens of BI tools on the market all with different price points and features. How do you know which will give you access to the data you need to scale? 

    Here are a few features you will want to look at. 

    1. Ad Hoc Analysis

    Ad hoc analysis empowers businesses to swiftly address specific inquiries or issues by examining data in real-time. For instance, companies can promptly evaluate the impact of a recent marketing campaign on ecommerce website traffic or sales figures.

    2. Dashboards

    Dashboards serve as centralized hubs where stakeholders can uncover insights at a glance, fostering informed decision-making. By incorporating interactive elements, such as filters and drill-down functionalities, dashboards enable users to delve deeper into data and extract valuable insights tailored to their needs. For example, a sales dashboard might show overall sales metrics but also allow a sales manager to see detailed data about a specific salesperson, time period, or region.  

    3. Real-Time Analysis

    Real-time analysis provides businesses with timely access to data insights, enabling them to respond promptly to evolving market conditions and consumer behavior. By leveraging real-time reports, organizations can capitalize on emerging opportunities and address challenges swiftly, enhancing their competitive edge in dynamic markets.

    4. OLAP Tools

    OLAP tools offer businesses the capability to analyze multidimensional data sets, providing a comprehensive view of various business aspects. By integrating data from diverse data sources like marketing platforms and CRM systems, OLAP tools enable companies to uncover hidden patterns and correlations, facilitating more informed decision-making.

    5. Data Visualization

    Data visualization plays a pivotal role in transforming complex data sets into intuitive representations, enhancing comprehension and decision-making processes. For instance, heat maps and scatter plots offer visual insights into customer behavior, allowing businesses to identify trends and patterns that might otherwise remain obscured within raw data.

    The Future of Ecommerce Business Intelligence

    BI is already helping e-commerce businesses make strategic business decisions faster. However, as technology continues to evolve, what can businesses expect? According to SelectHub, Machine Learning and AI will allow BI software to become increasingly self-sufficient in the coming years. 

    Other trends e-commerce companies should be on the lookout for include increased collaboration, integration, data usage, and the ability to store far more data than ever before using cloud-based storage solutions. 

    Why You Need Ecommerce Business Intelligence Tools

    Ecommerce business intelligence involves gathering and processing large amounts of complex data for the purpose of supporting strategic business decisions. It provides structured, data-driven answers to questions like “What happened?” and can help e-commerce companies make more strategic decisions about future growth. 

    Ecommerce business intelligence is not just for largest e-commerce companies — even small and growing e-commerce businesses can use BI to better understand how marketing, sales, AP, and other data-generating departments are impacting growth. 

    Successful BI implementation requires looking for an easy-to-use ecommerce analytics tool, getting buy-in from stakeholders, and ensuring staff has adequate training. 

    Ecommerce companies that want to stay competitive in the coming years should look to implement business intelligence tools and BI software today.