How to leverage technology solutions for data-driven decision making
Business intelligence, data analytics, and data collection are all common topics. All sectors of businesses, including ecommerce are investing heavily into new technologies that allow data collection and analysis.
This is because data-driven decision-making is becoming more important for ecommerce businesses, as they strive to understand their customers, make tactical business decisions, stay ahead of the competition, and use data to drive them.
While most businesses know the importance of using data to provide business insight, many are not aware of best practices for using data to support business results.
This post will discuss the data challenges that ecommerce businesses face, the best combination of technology solutions and strategies to provide valuable insights. We also show you examples of BigCommerce merchants using data solutions and insights in order to propel their business forward.
The challenge: Too much data, not enough insight
A report from Forrester titled "Data Literacy Matters" shows that 90% global data and analytics decision-makers are now focusing on data insights to improve business decision making. According to the same report, 91% of organizations say they have difficulty using data to improve business insight.
Companies are keener than ever to invest in data and understand its importance. Many still struggle with turning data into insights and actions.
A Forrester states that 60% to 73% of corporate data is not used. data from Statista also shows that 25% of companies have too many data.
Technology solutions can help you create a data-driven company.
Technology Solutions that can help you make data-driven decisions
Merchants can use the right combination data solutions to generate insights that enable them to make data-driven business decisions and provide customer experiences that are beneficial for their businesses.
Learn more:
1. Data warehouses
A data warehouse is a central repository of data or data catalog that integrates data from many sources. Strong data warehousing architectures can help businesses get valuable data points.
Data warehouses are not just for large enterprises. They can also be used by small businesses to collect information that is relevant to them. All sizes of businesses can use data warehouse tools. Although the term "warehouse” is often associated with a physical location, there are many tools that can be used online. They can also be scaled to any size you require.
Google BigQuery is an excellent example of data warehouse. BigCommerce has developed a native integration to for merchants with Enterprise and Pro plans.
Google BigQuery is used in conjunction with Google Cloud Storage. This fully managed data warehouse is a RESTful web service and offers cost-effective, scalable storage. The tool is accessible to a wider audience thanks to its generous freemium tier, and easy-to-use interface.
2. Business intelligence solutions
Data warehousing can be considered part of business intelligence. What is the difference between a business intelligence solution and a data warehouse? Data warehouses allow you to store data, while business intelligence solutions enable you to analyze that data in concrete ways to support data driven decision making and forecasting.
These tools allow you to take all the data you have and create dashboards that make sense for your teams. These tools are just a few examples:
- Google Data Studio provides powerful data visualization tools that allow your team to examine your data. It is free and tightly integrated into Google BigQuery. BigCommerce merchants have the option to use pre-built reports in order to get started using Google Data Studio.
- Tableau is a data visualization tool that aims to help anyone understand their data.
- Microsoft PowerBI is a leader in business intelligence solutions. The solution is provided by Microsoft and provides interactive data visualizations that can be interpreted using simple dashboards.
3. Customer data platforms.
Customers today don't just shop at one store and then go on with their lives. Before making a purchase, they research and shop on multiple platforms and sites. Customer data platforms are used to track the omnichannel customer journey.
Customer data platforms (or CDPs) collect customer data in order to create customer profiles which can be used to inform marketing efforts. They collect information from customers at every touchpoint, and then aggregate it for use by other business intelligence systems.
Your business can avoid data silos with CDPs. They will ensure that your teams are well-informed about your customers, their shopping habits, and their motivations. You can better market to your customers and solve their problems if you have a better understanding of their needs.
Segment can be used as an example of a CDP. It integrates with the BigCommerce platform and other business intelligence tools. This allows you to view your customers in unified views across all products and channels.
4. Personalization.
Businesses can transform from a one to many customer marketing strategy to one that uses personalization solutions. Personalization solutions allow you to create unique experiences for every customer through dynamic content, product recommendations and discounts, as well as offers and other incentives. These are just a few examples of personalization solutions available in the BigCommerce partner network:
5. Analytics.
Analyzing how customers interact online can provide powerful insight into what is working and what isn't on your ecommerce website. Analytics is a systematic computational analysis of data that can be used to measure metrics across marketing, sales, and search.
These are just a few examples of BigCommerce analytics solutions:
BigCommerce offers an open platform for data
All of the above data solutions share one thing in common: They rely on one another to function. Business intelligence doesn't come from one tool. It is achieved by multiple tools working together to collect, store, analyze, and interpret data into actionable insights. This is where data sharing between systems is important.
Communication is the key to unlocking the data's potential. This is communication between data tools. It is pointless to store and collect data if it can't be analyzed. It's pointless to have it analyzed if it isn't viewable in meaningful ways for your team.
BigCommerce embraces an openness philosophy. This allows you to have full control over your data, and the ability to use the solutions that have the greatest impact on your business. We call it our Big Open Data Solutions.
Big Open Data Solutions offers a complete product suite that includes both native and best of-breed partner solutions. It allows merchants to use online store data to analyze, understand, and share customer behavior information to improve decision-making and business performance.
How BigCommerce customers are making data-driven decisions
These are just a few examples of BigCommerce merchants using Big Open Data Solutions for insights and decision-making.
1. 1.
Origin is an apparel and nutrition brand which handcrafts its products in Maine's mountains. They have been optimizing their tech stack in order to keep up with channel growth. The company leveraged BigQuery integration and prebuilt Data Studio reports to harmonize consumers data from multiple sources in their omnichannel strategy.
BigCommerce's BigQuery integration enabled us to provide clear, actionable data and avoid (error-prone) manual reporting to help us make better business decisions. It has been crucial in unifying our data, providing the insights needed to make the best investments," Sid Martin (Systems Analyst at Origin).
2. Garrett Wade
Garrett Wade is a leading provider of hand tools for the garden. The BigCommerce integration with BigQuery was a game changer for the company's analysts.
BigQuery integration allowed the company to see actual data right away. According to the company, they spent very little time cleaning or normalizing data. They were also able to use the data to validate the accuracy of our testing environment before we launched. The company was able to immediately develop vetted reports, which allowed them to give the development team the time they need to tackle more complex report work.
It is both efficient and cost-effective for the two-person development team of the company to be able analyze shoppers' behavior and then produce detailed reports in Tableau from one location.
When we were considering BigCommerce as our platform provider we didn't consider the integration with Google BigQuery. However, after using it for several years, I can confidently say that this feature has confirmed that we made the right decision with BigCommerce. John Chan, Inventory Planning and Business Intelligence Analyst at Garrett Wade Company, said, "I highly recommend."
3. Fore Ladies Golf
Fore Ladies Golf is a women-owned business that provides high-quality golf clothing for women. It launched on BigCommerce in 2018 with great success. Jessica Benzing, the owner of Fore Ladies Golf, quickly recognized that she needed a better solution for analytics and reporting to help her build a data-driven strategy.
Jessica turned to Glew to see what was working and what wasn't. She was also able to determine what she needed to do in order to continue scaling. Glew gives Jessica a view on her top KPIs for analyzing Facebook and Google Ads campaigns. It also provides inventory reports to help with budgeting and maintain consistent stock levels. Customer segmentation data is used to target VIP customers and discount shoppers.
The Key Takeaway
Data is power. Data is becoming more important as consumers expect more personal experiences through ecommerce and shop in more omnichannel channels.
It is crucial to have an ecommerce platform that supports you data-driven strategy. BigCommerce believes open SaaS will be the future. Data is an integral part of this vision. It is important to be able choose the right data solutions, from warehousing and analytics to support your business intelligence goals. Also, having data solutions that can easily communicate with one another will help you create a more efficient data strategy.
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