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Business Intelligence for Ecommerce
A Full Overview
ScienceSoft applies 19 years of experience in BI and 21 years in ecommerce software development to help businesses build effective analytics solutions to get fast and intuitive insights on customer behavior, marketing campaigns, pricing strategies, product portfolio, and more, for consistent business growth and profitability.
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Ecommerce BI: The Essence
Ecommerce business intelligence (BI) provides insights on sales, marketing, fulfillment, inventory management, finance, customer support, and other aspects of an ecommerce business. It can enable analytics of different complexity: from tracking basic KPIs like a conversion rate and average order value to ML-powered optimization suggestions for marketing campaigns, product portfolio, and more.
- Main integrations: ecommerce platform, CRM, inventory management software, ecommerce fulfillment software, payment gateways, and more.
- Users: managers and specialists in sales, marketing, customer support, inventory, and merchandising; financial analysts.
- Implementation costs: $50,000–$1,000,000, depending on a solution’s complexity, number of integration and data sources, advanced capabilities, and more.
- ROI: up to 130% in three years after solution implementation.
Key Features of an Ecommerce BI Solution
At ScienceSoft, we develop reliable ecommerce intelligence solutions tailored to our customers’ needs. Below, ScienceSoft’s consultants list the features that are most frequently demanded by our ecommerce clients.
Ecommerce data processing and storage
- Automated ingestion of structured and unstructured data (e.g., customer data, transaction history, inventory levels, social media activity) from internal and external data sources.
- Cost-effective storing of all data types in a data lake.
- Automated unification and cleansing of all data formats, including text, video, and images.
- Aggregation of all data in a highly structured data warehouse ready to be used for historical analytics.
- Batch and real-time ecommerce data processing.
- Automated customer segmentation per gender, age, geographical region, etc.
- Calculating customer-related KPIs: CSAT churn rate, repeat customers, customer lifetime value, etc.
- Analyzing customer behavior: e.g., best traffic-generating channels, page-scrolling patterns, most frequently opened pages.
- Identifying the most profitable customer segments and lookalike audiences for efficient targeting.
- Spotting customer service or product flaws: late shipment, complaints, returns.
- Analyzing payment patterns: percentage of payment retries after failure, number of filed chargebacks, etc.
- Analyzing user-generated content (e.g., product reviews, social media comments).
- Tracking of sales KPIs: sales growth rate, daily sales outstanding, average purchase value, etc.
- Analyzing sales performance per customer segment, brand, in-app/in-browser purchases, etc.
- Predicting sales per customer, product, campaign, brand, etc.
- Tracking product/brand/SKU performance metrics: traffic attraction, penetration rate, etc.
- ML-powered range planning.
Pricing analytics
- Price sensitivity calculation.
- Identifying underpriced/overpriced goods, missed upselling opportunities, etc.
- Dynamic price optimization depending on elasticity, competitors’ prices, season, markdown strategies, etc.
- Automated calculation of price decrease amounts for discount and markup strategies optimization.
- AI-powered suggestions on personalized discounts based on the analysis of customer purchase history.
- Identifying and setting a free shipping threshold.
Ecommerce marketing analytics
- Analyzing the performance of marketing channels and activities.
- Identifying product affinity in order to shape upselling and cross-selling strategies.
- Developing loyalty programs based on continuous customer behavior analysis.
- Calculation of the supplier quality index and other KPIs to choose the most reliable suppliers.
- Getting insights into supply chain performance: e.g., cash-to-cash cycle, perfect order rate.
- What-if analytics to predict possible supply chain disruptions and mitigate risks.
Inventory management analytics
- Automated monitoring of inventory categories: low-stock, on-hand, aged, perishable, etc.
- Automated calculation of inventory-related metrics: inventory turnover rate, out-of-stock bounce rate to identify the best-selling and underperforming units.
- ML-powered demand prediction for multi-echelon inventory optimization and over-stock/out-of-stock prevention.
Ecommerce fulfillment analytics
- Dynamic monitoring of order lifecycle stages: drop, packed, in transit, delivered, etc.
- Analyzing historical data (orders per customer segment, SKU, brand, etc.).
- Tracking fulfillment KPIs (e.g., order picking accuracy, order picked per hour, on-time shipping rate).
- AI-powered forecasting of order fulfillment demand.
- Visual data representation via easily customizable charts, graphs, maps, and diagrams.
- Interactive data exploration with filtering, slicing, dicing, up and down drilling capabilities.
- Customizable dashboards that are convenient and secure for collaborative use.
- Self-service capabilities that enable the creation of complex visuals and reports without any technical skills.
Check the Insights You Can Get with Ecommerce Intelligence
Essential Integrations for an Ecommerce BI Solution
ScienceSoft recommends establishing the following integrations to get a holistic view of ecommerce performance and streamline data-driven decision-making:
- To analyze customer online behavior and optimize marketing, cross-selling, and other activities based on the acquired insights.
- To offer personalized suggestions to each customer based on their preferences.
Customer relationship management (CRM) or customer service (CSM) software
- To streamline customer segmentation for marketing campaigns.
- To calculate customer-related metrics: engagement, satisfaction, profitability rates.
- To identify issues affecting customer satisfaction.
- To assess marketing campaign performance and get optimization insights (identifying the most profitable markdown strategies, forecasting the efficiency of targeted promotional activities, etc.).
Social media
- To understand customer sentiment towards different products/brands.
- To assess and increase brand awareness.
- To identify major influencers across particular brands and products.
Supply chain management (SCM)
- To minimize inventory-related costs and optimize stock levels.
- To analyze supplier performance and choose the most efficient and reliable suppliers, determine the top-performing products by supplier.
- To identify optimal order fulfillment locations and shipment routes and increase customer satisfaction.
- To get insights on time, methods, and frequency of payments in order to identify customer spending habits.
Success Factors for Ecommerce BI
Combining 19 years of experience in BI and 21 years in building solutions for ecommerce, ScienceSoft outlines the key factors that determine the success of an ecommerce BI solution.
Maximized automation
To eliminate manual ecommerce data input from multiple sources and report generation.
User-friendly report generation
To allow users with any level of technical skills create or customize clear and impactful dashboards with filtering and drill-down capabilities.
Scalability
To cope with an increasing load (temporary during, e.g., special events and permanent as your business grows).
Ecommerce BI Costs and Benefits
The cost of implementing business intelligence for ecommerce may vary from $50,000 to $1,000,000*, depending on the solution complexity, the diversity of integrations, data types, the requirements for data quality, the scope of advanced capabilities, and more.
$50,000–$170,000
Basic ecommerce BI solution that:
- Enables the analysis of basic ecommerce KPIs like sales per period and average order value.
- Integrates with the key data sources like an ecommerce portal.
$200,000–$400,000
Ecommerce BI software of medium complexity that:
- Enables the analysis of key metrics across multiple ecommerce facets: sales, inventory, fulfillment, marketing, etc.
- Integrates with key corporate software (an ecommerce portal, CRM).
- Provides basic ML capabilities.
$400,000–$1,000,000
Advanced ecommerce BI solution that:
- Enables AI-powered analysis and forecasting of all required ecommerce metrics.
- Provides prescriptive analytics for product, price, marketing, CX, and supply chain optimization.
- Integrates with multiple back-office systems.
- Instantly collects and processes ecommerce-relevant data from all available channels, including social networks and competitor websites.
Get a Clear Picture of Your Ecommerce BI Budget!
ScienceSoft’s consultants will be glad to estimate the cost of your ecommerce BI solution.
*Software license fees are not included.
With an ecommerce BI solution, e-selling companies can achieve up to 130% ROI in 3 years after implementation. Other benefits include:
- Up to 30% revenue increase due to data-driven customer behavior analysis and ecommerce service personalization.
- 40%+ reduction in customer calls volume due to BI insights on customer experience improvements.
Off-the-Shelf vs. Custom Ecommerce BI Software
Even though there are several reputable out-of-the-box software options currently on the market, sometimes custom development is the most cost-effective way to fully address your analytics requirements.
In the table below, our consultants compare popular market-available software and a custom solution.
|
|
SAP BusinessObjects Business Intelligence |
Oracle Business Intelligence |
Microsoft Power BI |
Custom solution |
|---|---|---|---|---|
|
Basic ecommerce BI capabilities
?
Tracking ecommerce KPIs (e.g., average order size, sales per day, and other basic metrics); data visualization and reporting. |
|
|
|
|
|
Advanced visualization capabilities
?
Creating visuals with dynamic content, unlimited dimensions, and linked visualizations (e.g., cluster maps, violin plots, scatter plot matrices). |
The capabilities are limited in terms of visualization types and dimensions number. |
The capabilities are limited in terms of visualization types and dimensions number. |
The capabilities are limited in terms of visualization types and dimensions number. |
|
|
Advanced analytics
?
Based on ScienceSoft’s assessment. Main criteria: AI-powered analysis of large amounts of data (e.g., for customer segmentation across unlimited number of categories); diversity of pre-built ML models, and the ease of new model creation and deployment. |
3.5/5 |
3.7/5 |
3.9/5 |
5/5 |
|
Integration
?
With an ecommerce platform and other business systems. |
Native: with other SAP products. Via SAP Translator Program or RFC interface: with third-party software. |
Native: with other Oracle products. Via Oracle connectors: with third-party software. |
Native: with Microsoft products. Via APIs: with third-party software. |
Seamless integration with any required business solution (including legacy software) and third-party systems. |
|
Security
?
Based on ScienceSoft’s expert assessment. Main criteria: the availability of basic cybersecurity mechanisms (data encryption, role-based user control, user authentication). |
4.2 |
4 |
4.1 |
5 |
|
Regulatory compliance
?
Ability to meet the relevant global and local ecommerce data protection standards, e.g., CCPA, PCI DSS, FTCA, GDPR (for the EU). |
Compliance with global data security standards. |
Compliance with global data security standards. |
Compliance with global data security standards. |
Compliance with all required global and regional ecommerce data protection regulations. |
|
Ease of use
?
Based on ScienceSoft’s expert assessment. Main criteria: Self-service capabilities and learning curve. |
4.2/5 |
3.9/5 |
4.3/5 |
5/5 |
|
Pricing 50 users/ 3 years of use
|
Upon request to the vendor Expect to pay initial setup fees + configuration, customization, and integration fees + maintenance and support fees. |
~$370,000 depending on the use of data integration functionality. NB: Updates and maintenance costs as well as analytics server administrator rights fees are not included. |
$200,000 with data-sharing rights for all users. NB: may require updates and maintenance costs. |
Upfront investments of $50,000–$1,000,000, depending on solution complexity. Unlimited number of users, integrations, and any required advanced capabilities included. No additional fees. |
Do You Need a Custom Ecommerce BI Solution?
Answer a few simple questions and find out whether you should opt for a custom-made solution.
Do you need ecommerce BI software with specific features (e.g., demand forecasting or customer segmentation based on user-defined parameters, or non-standard visuals)?
Do you need to integrate ecommerce BI software with multiple back-office systems or legacy tools?
Do you need to ensure compliance with the local regulations in the regions where your company operates?
Do you need security mechanisms with enhanced transparency and flexibility (e.g., the ability to track data changes or IP location information for each user of the BI solution)?
Do you have a large ecommerce BI team and want to avoid expenses associated with per-user subscription model offered by off-the-shelf software?
Do you need an ecommerce BI solution with tailored interfaces for different roles across various ecommerce departments?
Do you plan to evolve the solution with new functional and non-functional capabilities in the future (to adjust it to changing business and legal requirements, new data sources, etc.)?
Tell us more about your needs
Please answer at least one question to help us better understand your business objectives.
A custom ecommerce BI solution is your best choice
Looks like market-available ecommerce BI tools don’t fit your specific business requirements and won’t be able to provide all the expected benefits or drive high ROI. Turn to ScienceSoft to get a consultation on custom ecommerce BI software development and receive cost and feasibility estimates.
Off-the-shelf ecommerce BI software will work for you
Looks like market-available ecommerce BI solutions are a viable option to meet your data analytics needs. Turn to ScienceSoft if you need expert advice on ready-made BI tools, their implementation, customization, or integration with your corporate systems.
Consider ScienceSoft’s Services to Implement Your Ecommerce BI Solution
Consulting on ecommerce BI
We will recommend BI functionality and integrations for your case, design architecture, select the tech stack, and give expert advice on security and compliance. You also get a detailed project plan with exact cost and ROI estimates and a risk mitigation plan.
Implementation of ecommerce BI
We can design and promptly deliver a secure, scalable BI solution that is tailored to your business specifics and can be easily adjusted in the future. To ensure high user adoption and smooth software evolution, we are ready to offer long-term solution support and maintenance.
About ScienceSoft
ScienceSoft is an IT consulting and software development company headquartered in McKinney, Texas. Since 2003, we help ecommerce companies build robust BI solutions to get fast and intuitive insights on customer behavior, marketing campaigns, pricing strategies, product portfolio, and more. Achieving project goals in spite of time and budget constraints, as well as changing requirements, is ScienceSoft's top priority. You set goals, we drive the project to fulfill them.
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