“Data analytics had the biggest impact on my business. There’s no doubt about it.”
That’s what John, a retail store owner from Memphis, Tennessee, says. He started his store in 1995, and for 20 years, he was facing the problem of tracking all the inventory and their prices. He had to remember and track the availability of a product while remembering where it is kept, what’s the current price for it, and when the re-stocking would be required.
Well, this is just for 1 product. Imagine keeping a similar track for all the products in his store. Tough job, right?
Earlier, even after keeping a rack full of record books, he still made mistakes. Some products were not ordered even after they were long finished. He sometimes had the wrong number on the availability of certain products. And sometimes, he priced a product too low as he forgot to update the new price. But now, he doesn’t worry about all this.
Because data analytics software does this work and does it quite brilliantly. This technology made his life so much easier and his business so much efficient!
But how did he start with this? Well, it took a lot of time for him, as the information was not easily available. And this is exactly where we want to help you with this blog. We understand the importance of a question like- what is data analytics, and how can I use it for my business? We’ve done our absolute best to answer this question. So, with no further ado, let’s help you on your data analytics journey.
How does data analytics work?
To put it simply, data analytics work when an analytics software that has machine learning algorithms and automation capabilities run through a dataset and give out an actionable conclusion about the information it contains. Imagine you found an ancient map in the form of a structured dataset.
Well, if you let a data analytics software do its work, you’ll probably find whether this map leads to a treasure or is it some child’s work! We can give tens of examples (even some serious ones) to answer your “what is data analytics and how does it work?” question, but we think you already have other exciting questions in mind! Very well, then. Let’s keep going.
Types of data analytics
There are 4 different analytics. Here, we’ll start with the simplest one and notice that the more complex an analysis gets, the more value it brings.
Descriptive analytics:
Descriptive analytics answers what happened. It gets raw data from various sources to give valuable conclusions about the past. However, findings from this analytics simply signal that something is wrong or right, with no explanation.
Diagnostic analytics:
Diagnostic analytics gives detailed insights into a particular problem by using historical data to analyze against other data and answer why something happened.
Predictive analytics:
Predictive analytics talks about what is likely to happen. It uses the insights from descriptive and diagnostic analytics to detect clusters, exceptions and to predict future trends.
Prescriptive analytics:
Prescriptive analytics prescribes what action is required to eliminate a problem that can come in the future or how to take the maximum advantage of a promising trend. It uses advanced tools, like machine learning, which makes it quite sophisticated to manage.
5 reasons why data analytics matters for your business in 2021?
Here we are! After a brief intro into what is data analytics, how does it work, and its types, we’re asking what you want to ask- what good would data analytics do for my business?
Well, we have not just 1, but 5 top reasons to answer this question. See, when you’ll search something like, “what is data analytics and how would it help my business?” in your browser, you’ll probably get a boatload of results. But is that relevant for your business in 2021? Probably not, but the remaining sections of this blog certainly are! So, grab a cup of coffee, read patiently, enjoy our quirky stories in between, and then make a plan to start using data analytics based on this. Are you ready? Great, let’s start with our 5 reasons first.
To know your ideal customer
Do you remember that ice-cream truck from your good old childhood? Did you notice how the truck driver always knew where to stop? Well, he used to stop by your house because you always wanted your favorite chocolate cone (did we guess it right?). But he rarely stopped in front of a grumpy old man’s house. Why? Because the driver knew the old man ain’t his customer. So, he always focused on the ideal customer group rather than focusing on everyone.
Well, that’s exactly where data analysis helps, and if you ever ask us, “what is data analysis?”, this would be our answer (childhood memories are always the best examples!). But to invest in technology when the example proves that we can do this on our own?- If you’re thinking this, you’re thinking in the right direction.
The human mind can find your ideal customers, but not from the get-go! The ice-cream truck driver didn’t stop the truck in front of the right house with his 1st or 2nd attempt. He took an ‘n’ number of attempts to figure the right customers out, and this ‘n’ could’ve come after several years. Can you or your team give so much time for this in this fast-changing world? We reckon we know your answer.
When you use data analytics, you first collect information on people who you think could be your customers, then you understand who they are, where they come from, their age, gender, and habits, specifically spending habits. You know your ideal customer persona based on your product and offerings, and you’ll match these findings with that persona. Once this matches, you’ll know who to market to when promoting and advertising your business.
The focus can then shift on these people because they’re the ones who could turn into your customers. And you would probably want to give them the best deals!
To get dedicated customers
The Covid-19 pandemic showed businesses how bad disruptions could be. The work culture changed abruptly, and companies didn’t have much time to set up what’s necessary. Customers kept churning till the count went to zero. And finally, many businesses had to shut shops or took huge losses from which they’ve still not recovered.
“Hope for the best, prepare for the worst”- This is what 2020 taught business leaders. So, asking “what is data analytics?” and starting with it is the best way to prepare for the worst. Investing in exciting data analytics trends would give your organization the ability to create an extremely personalized experience for your customers (Here’s how SurveySparrow can help you improve your customer experience). Experience that can make their lives easier, better while also keeping them safe!
Well, RXR Realty did exactly that when they adopted data analytics and technology to create a “Lab” that developed an app to give personalized services like move scheduling, deliveries, and heating and cooling information for tenants living in their apartments. This became possible because they harnessed every customer’s data to understand what they most need and when do they need it?
They’re going stronger than ever in 2021, as they’re planning to ensure customer safety and well-being with their use of data analytics in research in the new normal. Now tell us, why won’t their customers be loyal to them?
To get speed
“When Covid first struck, it took us months to adapt to the new way of working.”
If that’s your company’s story too, don’t worry, you’re not alone. It happened with almost every business, but not all of them! Why? Because some businesses had well-analyzed data about their customers, employees, and different business functions, using which, they took quick decisions and slowed down their downward slide. And they had this “well-analyzed” data because they had an answer to the “what is data analytics and why does it matter?” question. They leveraged it to create solutions and took quick actions that made the difference.
Goldman Sachs did the same thing with their digital consumer business, Marcus. As, when the pandemic hit, they peeked into the data they had analyzed, predicted who could not pay their loans and credit card bills, and based on their history, Goldman Sachs allowed them to defer on these repayments till normalcy came. The best part, they took this decision in just 72 hours! Their popularity has increased multifold with this one smart and fast decision that data analytics helped them make. Impressed yet?
To forecast and fulfill the demand
One of the first areas that got badly hit with the onset of the pandemic was the supply chain side. There was no particular information about the type and quantity of demand for a certain product. Why did that happen? Because companies weren’t using the collected data to predict or identify the demand. And they were like this well before 2020. So, the pandemic just aided in the disruption. But the primary reason was leaders not knowing what is data analytics and its crucial importance in a business?
Even if your supply chain survived in 2020, you would never want such disruption with your business, right? Well, the online furniture store, Wayfair, did a brilliant job to prevent such turmoil by sharing the analyzed supply chain data with their customers. This way, customers already knew what was there in the inventory and what wasn’t.
They also knew what would be available in the coming weeks, as Wayfair was able to forecast based on the demand and supply data. So, customers planned their purchases accordingly, and the complete buying experience was seamless. Going forward, that’s how you’ll get happy customers. Forecast demand with the help of data and business analytics technology in 2021, and there would be no poor customer experience. Trust us on that.
To predict future
Whenever the question “what is data analytics?” would come up, there would be a word called “prediction” in its definition. So you, as a business leader, have time to address and rectify a minor problem or change before it becomes too big and starts hurting your revenues.
Amazon, Zara, Uber, and many big organizations are investing a hefty sum in building efficient algorithms using powerful data analytics technologies. To do what? To predict customer and employee behavior in the future, observe any misalignment in data to see what effect it’ll produce eventually, and test future products to see if they would succeed or fail. Powerful and efficient predictions would be a game-changer for companies adopting data analytics in 2021. Won’t you agree?
Ask these 7 questions to develop the right data analytics strategy
The question of what is data analytics and its usefulness for your business in 2021 is covered till now. But the question of how to use data and business analytics in the best possible manner remains. This is what we’ll cover in this section, as asking these 7 questions and brainstorming them over with your team would help you come up with the right data analytics strategy.
A strategy that’s tailor-made for your company’s requirements and needs. And a strategy that would help your company climb the ladder of growth in 2021 and beyond. So, let’s raise the curtains on this.
#1 What goals would data analytics help achieve?
Before thinking about any past data, it would be best if you and your teams could sit down and identify the goals you want to achieve with the help of data analytics. Answering this question would set the right expectations from the start.
#2 What type of data would be needed?
Well, those who say that data is the new oil aren’t wrong! Because the type of data you and your team choose to analyze would be the type of result you’ll get. So, this question needs appropriate discussion.
#3 What data analytics technologies would work best?
You need to have a very clear discussion on this because if you know the answer to what is data analytics, you probably know that without the right technology and algorithm, it’s just 2 plain words. So, choosing the right technology among the host of options is imperative.
#4 How would the analysis take place?
With this, your teams need to ponder how the analysis would actually take place. Whether the structured data, like website click, would be analyzed first, or the unstructured data, like email conversations? Or, a mixture of both these types would be combined and run for analysis? We know, we’ve asked questions rather than giving answers here, but whatever needs to be done for clarity should be done, right? (Another question!)
#5 How would the insights and reports be presented?
Analyzing the data to find actionable insights is one thing, but presenting it is a different job. Your teams need to decide the exact way they’ll present the breakthroughs from the analysis, and how they’ll highlight the actionable points.
#6 To whom would your team present these insights and when?
A project head or a Chief Data Officer (CDO) along with a fixed timeline would help your company get the right results from the data analytics process. And even though when you first learn about “what is data analytics?”, these 2 aspects don’t come up, going forward, this is how you’ll always stay ahead of your competitors!
#7 Who would handle what, and what are the KPIs?
Answering the first part of the question would keep the entire data analytics process on track, and setting the right KPIs would keep the entire process efficient. Simple it may sound, finding the right answer to this might just take you the longest.
Here’s the end, but this is just the start!
2.5 quintillion bytes. That’s the amount of data each one of us approximately creates every day. This data is as texts, photos, videos, searches, and even your tweets. Surprised by the number? We would be more surprised if, after reading this blog, you still decide to ignore the power of data and business analytics!
Because 2020 clearly showed why every business needs it to process their vast data. And we think this year’s going to be big for data analytics technologies.
More and more leaders have searched, read, and learned about “what is data analytics?” and everything related to that. And since you’re also a part of this group after reading this blog, it’s time to take some action and bring a data-driven culture to your company. Till then, don’t stop!
