Technology solutions can easily help make data-driven decisions
Data-driven decision making (DDDM) is a method of collecting information on the basis of quantifiable goals or KPIs, evaluating patterns and facts from these findings, and implementing strategies and measures that benefit the company in a variety of ways. In general, data-driven decision-making involves achieving key business goals by relying on verified, explored data rather than fueling it.
Examples of data-driven decision making
Increase in sales at Amazon
Amazon uses data to determine which goods to recommend to consumers based on previous purchases and search activity trends. Amazon’s recommendation engine is guided by machine learning and artificial intelligence rather than arbitrarily suggesting a product. According to McKinsey, 35 percent of Amazon’s customer purchases in 2017 could be traced back to the company’s recommendation algorithm.
Leadership development at Google
Google continues to place great emphasis on what it calls “people analytics”. Google collected data from over 10,000 performance reviews and linked it to employee engagement rates as part of Project Oxygen, one of its well-known people analytics measures. Google used the data to identify the usual habits of high-performing managers and develop training programs to help them improve those skills. As a result of these initiatives, the average manager preference ratings rose from 83 percent to 88 percent.
Real estate decisions at Starbucks
After closing hundreds of Starbucks stores in 2008, then-CEO Howard Schultz promised the company would take a more scientific approach to attracting new stores.
Starbucks partnered with a location research company to identify suitable store sites based on demographics and traffic trends. Before decisions are made, the organization consults its regional teams. Starbucks uses this information to evaluate a site’s chances of success before making a new investment.
Technology solutions for data-driven decisions
Customer data platforms
Customers these days rarely visit a single store, make a purchase, and then move on. Before making a selection, they do research and comparative purchases across a variety of websites and platforms. Customer data platforms are used to track the omnichannel customer journey.
Customer data platforms or CDPs collect information about customers in order to create customer profiles that can be used to control marketing activities. They work by collecting data as customers go through each touch point and aggregating it for other business intelligence tools to use.
CDPs can help your business avoid data silos by making sure all of your employees know who your customers are, how they shop, and what motivates them.
A data warehouse is a centralized repository or data catalog that contains integrated data from many sources. A good data warehousing infrastructure can provide a company with important data points.
Data warehouses can be used by both small and large companies to collect the information that is important to their operations. Data warehouse software can be used by companies of all sizes. While the name “warehouse” conjures up images of a physical location, many solutions are cloud-based and therefore perfectly suited for scaling to the desired size.
For companies with BigCommerce’s Pro and Enterprise subscriptions, Google BigQuery is a fantastic example of a data warehouse that BigCommerce used to create a native interface.
Business intelligence solutions
Business intelligence includes data storage. So how can you tell the difference between a database system and a business intelligence system? Data warehouses are just storage tools, but business intelligence solutions allow you to analyze data in concrete ways to aid data-driven decision making and forecasting.
These technologies can help you organize your large amounts of data into panels that make sense for your different teams. Some examples of these technologies are as follows:
- Google Data Studio is a data visualization tool that lets your team explore your data in new ways. One of its advantages is that it is free and tightly linked to Google BigQuery. To get started with Google Data Studio, BigCommerce companies can use pre-built reports.
- Tableau advertises itself as a data visualization tool that aims to help everyone understand their data.
- Microsoft Power BI is the market leader in the field of business analytics tools. The system operated by Microsoft provides dynamic data visualizations and easily understandable interfaces.
Organizations can use personalization solutions to move from a one-to-many customer marketing plan to a one-to-one plan. You can deliver personalized experiences to each consumer with customization solutions that include dynamic content, product suggestions, offers and discounts, and much more. Personalization tools on the BigCommerce partner network include the following:
- Lime stains
- Dynamic yield
Knowing how your customers are doing online can provide valuable information about what works and what doesn’t on your ecommerce website. Analytics, at its most basic level, is the systematic computer analysis of data that can be used to track metrics across the web, marketing, research, and sales.
Here are some examples of BigCommerce partner network analytics solutions:
- Google Analytics
- Trend analysis
How BigCommerce customers make data-driven decisions
BigCommerce’s connection with BigQuery has proven “game changing” for Garrett Wade, a top manufacturer of high quality woodworking and hand tools for the garden.
Thanks to the interface with BigQuery, the company could immediately start looking for real, correct data. According to the company, cleaning up and normalizing the data took relatively little time. In addition, they were able to use the data to confirm the correctness of the test environment prior to our launch. This also allowed the company to produce verified reports quickly, which gave the development team time to focus on the more demanding reporting tasks.
Fore ladies golf
In 2018, Fore Ladies Golf, a women-run company dedicated to providing quality golf apparel for women golfers, made a successful debut on BigCommerce. Owner Jessica Benzing, on the other hand, quickly understood that she needed an analysis and reporting solution to develop a more data-driven approach for her company.
Origin, a handcrafted apparel and nutrition company based in the mountains of Maine, has refined its IT stack to keep up with channel expansion. As part of its broader omnichannel strategy, the company used the BigQuery connection and pre-built Data Studio reports to unify customer data from multiple sources.
It will be crucial to have an ecommerce platform that enables your data-driven strategy. BigCommerce believes that Open SaaS is the way of the future and data is an important part of it. Being able to choose the data solutions that best support your company’s intelligence goals, from storage to analysis, and how they interact with one another can make all the difference in developing an optimized data strategy.