The “big data” hype rages on, especially for retailers anticipating the holiday shopping season. If you are among those hoping to find a sudden, near-miraculous solution to your data concerns, I have good news and bad news:
The good news is that big data is not a magic cure for sales woes. The bad news is that big data is not a magic cure for sales woes.
Data is a matter of science, and that means it’s something you can control. So while data is not going to make your sales explode for some inexplicable reason, it very well could make your sales explode because of actions you took as a result of quickly and accurately analyzing data. That’s much better than buying into some vendor’s hype about big data and purchasing a solution that’s not ready to meet your needs. But there are platforms that can help you get better access to real-time information from multiple systems at one time—you just have to know what you’re looking for.
Here are five things retailers need to know about big data:
1. Big data isn’t what you might think it is.
If you said that big data is massive data sets that require specialized tools to analyze, you’re not wrong. But the way businesses are gathering, storing, accessing and using data is rapidly changing. Where they once relied on databases and servers, retailers are now moving their data to cloud storage where it can be accessed from anywhere by the right people, at the right time.
But that doesn’t change the fact that the data is trillions of rows long and is often incongruent from one source to another. Retailers are solving that problem with cloud-based analytics platforms that can pull specified data types into visualizations in real time, so even though you aren’t a data scientist, you can see exactly how your metrics are performing at any moment.
The face of big data is changing, so don’t give up yet if you’re pulling your hair out trying to find a better way to get the information you need.
2. “Big data” is not for everyone, yet.
If you’re struggling with putting together a data strategy, don’t feel like you’re behind the curve. The big data hype makes it easy to believe every company is orchestrating a mind-blowing big data strategy. At Domo we’ve seen that most companies are still struggling to find value from the “small data” and while they know what big data is, most are unsure about how to harness it and put it to use.
You may not have systems kicking out trillions of rows of data at all—and that’s OK. You can derive incredible value from the data you already have, if you can see it in context.
3. It can show you new, incredible insights.
Speaking of seeing data in context, retailers shouldn’t limit themselves to the data they own. There are many factors that impact your sales. Is it raining? Could be great if you sell umbrellas, and damaging if you sell swimsuits. But external factors aren’t typically so cut and dried, and you need to combine your historical sales data with third-party data so you don’t get blindsided.
What we’re saying is that the real value of this data revolution is being able to overlay multiple data sources to see the story that emerges among the data sets.
When your business data lives in isolation, you only get part of the story. Retailers need to identify relationships between different data sets, which often tells a more compelling and comprehensive story and allows you to manage your business more effectively.
4. Data takes work to get value from it.
“Big data is generally not neatly formatted and today data scientists spend up to 80% of their time cleansing and preparing data,” said Ping Li, an investor with Accel Partners, in a recent article from Tech Republic.
Depending on the size of your organization, your team could be dealing with terabytes or even petabytes of data. And when you get data from multiple sources in the mix, your team has to reconcile disparate, incongruent values across multiple tables. Translation: it takes a lot of work.
5. But it doesn’t have to be time consuming.
The old-school method for handling big data—storing it all in databases and putting data scientists to the grind for hours and hours—is rapidly coming to an end. As retailers move data to the cloud, they are able to automate the reports that their scientists produce. That doesn’t mean data scientists are going away; rather, it means that once you define the information you need, you can quickly get information you need instead of spending hours digging through spreadsheets.
You get what you need when you need it, and scientists become true analysts rather than report generators.
So what’s next?
Simply put, getting control over your retail data—no matter what size it may take—will inevitably help you grow your retail business. But be careful that you don’t let the data drag you down in never-ending analysis and reporting. Data is there to make your retail business function more efficiently, so the last thing you want is to lose efficiency in an effort to gain it.
How have you wrangled your data? What are some of the benefits you’ve seen, and what’s still missing? I’d love to hear about it in the comments.