The use of Big Data by ecommerce companies is increasingly common. To stay competitive, many companies, especially larger ones, use extensive datasets to better understand their customers and provide services, recommendations, and experiences tailored to each individual. For many online stores, therefore, it is not a question of whether to use Big Data solutions; it’s a matter of what tools to deploy and how much to spend on them.
In this article, I’ll provide an overview of the Big Data choices for most ecommerce merchants, along with approximates of how much each option costs.
Option 1: Hire Data Scientists
An e-tailer can choose to go the in-house route and hire people to handle its data needs. Making sense out of customer data requires three things: collecting data, analyzing and presenting the information, and spotting trends that would enable the company to take action.
All these tasks cannot typically be accomplished by a single person, which is why merchants would likely need a build a team of data scientists to take care of their data needs.
How much would this option cost? According to Glassdoor, an employment site, a data scientist (in my home city of Los Angeles) makes from $70,000 to $115,000 per year. This is a heavy investment for any small business owner and oftentimes it is difficult to see the return immediately.
Aside from employees, you would also need to think about the systems — such as scalable databases — you should have in place. As Carl Forrest, co-founder of DataSetGo, a data-consulting and analysis firm, told me, “You need to be sure that your systems are robust enough so that as business grows, your systems and processes can handle the increased loads. Using massive Excel spreadsheets as the central database for your finance department is not scalable.”
That’s why it essential to hire someone who can design a solid system for your business.
Option 2: Outsource Data Needs
Another option would be to outsource your Big Data needs. A retailer can seek the help of firms and let them crunch the numbers and generate insights, so the retailer can focus on selling products, taking care of customers, and growing the business.
Outsourcing is usually more affordable than hiring a team of data scientists; it can be a better choice for smaller ecommerce merchants.
The cost for this option will largely depend on the types of data you have along with how much information needs to be analyzed. Are you just analyzing your email subscriber list? Are you tracking on-site behaviors? Do you need social media data analyzed as well? Take these into consideration then find a company that can fulfill your needs.
For example, VOZIQ, a business intelligence company that focuses on monitoring social media conversations and data, offers monthly packages from $1,000 to $5,000. According to founder and CEO Dr. Vasudeva Akula, VOZIQ comes with an “analytics platform, proven industry analytics frameworks, and most importantly, a team of data scientists (PhDs) and business professionals who work as an extension of the core team.”
Carl Forrest of DataSetGo says that his company’s “monthly fees vary depending on the size of the data and the business’s requirements.” Using a $25 million (revenue) business as an example, he stated that quantitative marketing analytics — including Google Analytics, search engine optimization, and AdWords management — would cost roughly $4,500 per month. Data management, including cleaning and ETL (Extract, Transfer, Load) would cost $3,500 per month; while reporting and analysis with interactive dashboards would cost $4,500 per month.
“This looks like a significant amount of money but the reality is, it’s about on par with what you would be paying for just a data scientist,” Forrest noted.
Option 3: Use Free or Inexpensive Tools
Merchants on a budget can choose the do-it-yourself route by making use of tools, such as Google Analytics, Crazy Egg, and KISSmetrics. These solutions enable you to track visitors and customers, to create more effective campaigns and serve them better.
One downside to this option is that most analytics tools, while simple and affordable, can be limited and may not provide enough insights to understand your shoppers at a more advanced level. In addition, creating one-to-one campaigns that incorporate data from various sources (i.e., email, mobile, social, ecommerce, brick-and-mortar) can prove to be challenging.
For example, say you rely on the analytics that come with your email service provider to learn more about your shoppers. While your email provider may provide data on open and click-through rates, predicting customer behavior or automating campaigns at an individual level will be time consuming and difficult. As a marketer, I want to know where email subscribers with the highest click-through rate came from — such as Facebook ads vs. organic search on Google. This kind of insight would require more sophisticated tools.
Still, using such tools can be a good starting point and is immensely better than doing nothing.
Bottom Line: Get a Handle on Your Data
According to DataSetGo’s Forrest, while data needs can be expensive, the price tag for not having understanding your data can far outweigh the costs of the solutions or people you take on.
Aside from identifying “inefficiencies that saved clients $600,000 in three months,” Forrest noted that businesses that don’t take the steps to understand customer data could lose their competitive advantage.
“You will lose market share. You will not be able to effectively identify your core customers, let alone tailor individualized marketing campaigns for them,” he added.