Summary: We’re in the middle of a data explosion. The modern business has access to more data than ever before, and it’s only growing. However, not every business knows how to use this data to its fullest potential. In this article, we explore a few ways to get more value out of your data.
The big difference: How they use it.
For some, data is a burden. They must keep track of it, but that’s about it. Or, they have trouble managing their data. Or, maybe they’re overwhelmed because they have so much.
But for others, data is a competitive advantage. They have the processes and knowledge in place to maximize the value of their data. To them, data is the lifeblood of their business.
The question: What makes the difference? If your business hasn’t maximized your data’s potential, how can you reach that point?
Today, let’s explore this topic in more detail. Here are 5 tips to maximize your data’s value:
1. Make sure it’s clean
Now, I hesitate to mention this point as it may seem obvious. But, I include it because it’s so important, and it’s still an issue for many companies.
You can’t maximize your data’s value if it’s not accurate. This is a sore subject for many businesses because their data is floating around on spreadsheets. They can’t tell you which version is correct, let alone whether or not it’s accurate.
Before you can capitalize on your data, it must be cleaned and placed in a database. Why? It gives you a single version of the truth, and lets you control the data and user access. This will save many headaches down the road, and as explained below, make analysis far simpler.
“A business can potentially record data about every single aspect of its business, and then analyse it,” says Peter Zaborszky, Founder of BestVPN.com. We’ve recently started doing this and there are three stages to this:
1. Data cleansing
2. Data analysis
3. Building algorithms/formulas to automate the analysis.
If you are in the early stages of using data, I would recommend making sure that all the data you record is accurate. That will minimize a very expensive phase, number 1, cleansing the data to make it accurate. That will make analyzing the data much easier.”
2. Put a system in placeI realize that this may seem obvious as well, but I include it for the same reasons as the last point. It’s a necessity if you hope to maximize your data’s value, and it’s still a common problem in the business world.
Many businesses don’t have a standard data analysis system in place. Or, others have so many disparate systems, no one’s quite sure which one is correct. Or, still others have manual systems in place that eat up valuable time.
The fact is, you can’t maximize your data’s value if you have no easy way to turn it into meaningful information. Get a data analysis system in place that spans your entire business.
“It’s one thing to have business data — but it means nothing if you don’t know how to interpret it,” says Mikko Honkanen, co-founder of Vainu. “One of the biggest tips I can give is to have a system in place for how you’re going to interpret and analyze business data. Once in place, use that analysis to inform your business development decisions. I can’t tell you how many people I’ve met who have all the data at their fingertips and are still shooting in the dark in many ways when it comes to prospecting and finding sales leads. Do your homework and interpret the right data. It can really pay off.”
3. Incorporate data from external sourcesWhat if I told you that your business has access to more data than you realize? Let me explain.
When you think about maximizing your data’s value, what type of data comes to mind? Probably your company’s internal data. But, did you know there’s a goldmine of data found in external sources? As mentioned in this article, you have access to far more data than you realize.
This external data becomes a powerful resource when you combine it with internal data and create new insights. Here’s one example that illustrates the potential: The Point Defiance Zoo & Aquarium recently used weather data to predict attendance and staffing requirements. In bad weather, zoo attendance goes down–which lowers their staffing requirements. But, with the rapid weather fluctuations in the Pacific Northwest, predicting the weather is a difficult task. Using historical weather data combined with attendance records, the zoo is now able to predict attendance within a couple hundred visitors.
That’s just one example, but the possibilities are endless. Where else can you find useful data? Social media is another area full of possibilities. When you combine social data with internal data, you get a broader picture of your business.
“One way companies can harness the insights of their large datasets is through social media analytics,” says Maxime-Samuel Nie-Rouquette, Client Success Manager at Semeon. “Social media analytics sifts through relevant data from online conversations and automatically generates actionable insights for companies to use.
By comprehending online conversations, companies can understand what their consumers care about, identify who influences their consumers and leverage their influencer’s networks, and monitors sentiment throughout or during specified time periods to optimize their communication strategies.
Social Media Analytics, is important in today’s business as it holds statistical validity to the insights it detected, implying that businesses can make solid business decisions by incorporating some insights from social media analytics.”
4. Incorporate machine learning and AI
Traditionally, BI has revolved around data in a structured format–typically in a database. SQL queries run against that data and deliver results.
However, over the past few years, we’ve seen a few important trends emerge:
First, we have big data. Data is growing at an exponential pace, and shows no signs of slowing down. However, this data means nothing if we can’t turn it into meaningful information.
Second, we have a lack of data experts. As data has grown, data analytic skills have not kept up. In fact, research finds there’s a global shortage of data scientists.
Third, we have a growing need for fast data. Businesses need insights quickly, and can’t afford to wait around.
Combined, these trends are the driving force behind a huge BI trend: Artificial Intelligence (AI). As explained below, machine learning and AI has the ability to turn mountains of data into insights.
“Long before the term “big data” was coined, Albert Einstein once said “information is not knowledge,” says Dr. Michael Zeller, Senior Vice President of AI Strategy & Innovation at Software AG. “One of the challenges that business leaders face today is how to turn all the data that organizations are collecting into knowledge and, thereby, into actual business value.
This holds true for big data in general, but it becomes even more obvious in the context of the Internet of Things (IoT) where sensors and devices generate not just more data but also a variety of new data types. Rather than producing more reports and dashboards, our goal should be to enable smarter solutions through intelligent, automated decisions. Machine learning algorithms and artificial intelligence hold the key to do just that – first, to help us uncover and understand complex relationships hidden in the data, then to build predictive models that allow us to make more precise, more nuanced decisions. This forms a fundamental pattern for many use cases, including detecting fraud in the financial services industry, recommendation engines for marketing, or predictive maintenance in the context of IoT applications.”
5. Know your customerWith every interaction you have with customers and prospects, you gain valuable insights. Every time they click a link, buy a product, or contact your business, you learn a little more about their needs and interests.
Smart businesses take this data and segment their prospects/customers based on their interests. This way, they can send relevant communications at the right time.
The question is, what are you doing with this data?
While this data is available to most companies, few actually use it to their advantage. If you’re looking for a quick way to capitalize on your data, this is a great place to start.
“It’s frightening that most brands don’t target any specific customer or prospect segments, or know which high-value customers they should focus their efforts on,” says Cori Pearce, Director of Marketing Execution at WealthEngine. “Companies can gain knowledge and insight on their customers and the key to segmenting them through analytic practices such as profiling and cluster analysis. If you don’t know your best customer segments, or use effective segmentations in your communications, let this be the starting point in your analytic journey.”
These are just 5 tips to get more out of your data, but the list could be much longer. If you would like to add anything to this list, I’d love to hear it. Feel free to share in the comments.