How data analytics can boost your sales figures

If you think data analytics is something IT guys hidden away in the basement office do, think again. Big data and everything that comes with it, data analytics in particular, is one of the biggest opportunities for increasing your sales figures.

What? How? Why? And… when did that happen?

Don’t worry, a lot of us feel like that since Industry 4.0, the latest tech revolution hit us in the face and left most of us stunned, gasping for air.

Luckily, as with all the previous industrial revolutions, you don’t have to understand how exactly something works. You just need to know how to use it.

It happened within the last few years, and if you tend to skip news articles that feature words like “tech,” “blockchain,” and “artificial intelligence,” it’s no wonder you missed the big news.

It’s OK. Luckily, as with all the previous industrial revolutions, you don’t have to understand how exactly something works. You just need to know how to use it.

That’s a relief for all of us who work with the internet and yet have no idea how all those tiny bits of data travel around the world.

The basics of data analytics

There are a couple of terms and concepts you need to be familiar with before you can start using data analytics to boost your sales.

Big data

While industry experts are still struggling to come up with a detailed common definition, there’s a short version most of them seem to agree on.

Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

In plain English, big data means large and complex data sets that are too big for traditional software to manage and process. However, big data is a huge help for businesses when it comes to decision-making and informed choices.

Data collection

Data is all around us. You can collect big data from virtually anywhere. Your sales software, social media accounts, website, and all customer transactions are a gold mine when it comes to data collection.

But simply collecting it is not enough. Not at all.

Data analytics

Collecting big data won’t help you save money and gain more customers. You’ll need data analytics to tell you what to do with all the information you gained from big data.

Analyzing your data can help you reduce costs, optimize schedules, convert leads into customers, better target your audience, and much more.

Now that you’re (sort of) familiar with the basics, it’s time to see what data analytics can do for your business.

Better customer personas

Information gained from big data can help you create very accurate buyer personas.

Do most of your big customers hold degrees in neuroscience? What papers do they read? Where do they go for a coffee? Do they drive a car or commute via train?

Customer personas are essential for targeting your marketing campaigns. It’s common sense, really: if you know which papers your prospective customers read, you can select those publications for advertising.

But without big data, you can only speculate about your customers’ preferences, based on sporadic customer surveys or (even worse) educated guesses.

Targeted marketing

Data analytics can give you a very accurate picture of customer behavior, which helps effectively target your marketing efforts and special offers to real customers’ real needs.

Various customers have varying tastes. Following a certain customer’s history allows you to gain insight into their preferences, enabling you to tailor your offering to their exact needs. But who has time to follow each and every customer?

Following a certain customer’s history allows you to gain insight into their preferences, enabling you to tailor your offering to their exact needs. But who has time to follow each and every customer?

Big data does. Analytics gives you invaluable insight into each customers’ journey. For example, Customer A buys Product Z with Product H on a weekly basis while Customer B gets two boxes of Product D in the first week of every month.

Data like this helps you narrow your offering and personally target each and every one of your customers. Isn’t that every retailer’s dream come true?

But big data analytics doesn’t stop at existing customers.

Predictive analytics

Would you like to know the future? In lieu of a crystal ball, you can rely on predictive data analytics. It’s the simplest trick in the book: based on data collected in the past, you make assumptions about the future.

For example, if the number of customers visiting your store rose significantly in the weeks leading up to Christmas, you can assume this is going to happen next December as well. Of course, you don’t need big data to tell you that, simple common sense will do.

A small mom-and-pop shop won’t buy as many supplies as a giant retail store. But that doesn’t mean you can’t try and encourage them to buy more.

But predictive analytics based on big data can tell you much more. Analyzing your sales data can help identify patterns and features of the most promising sales leads.

For example, did you know that most of your biggest customers buy your products from a certain line in a specific order? For some reason, it’s always Product C, then Product A, and then Product B.

So the next time you spot someone seriously checking out Product C, you can start assuming they may turn out to be your next big customer and offer them an incentive to go ahead and buy the whole line right away.

Boost low value accounts

Do you know why one customer spends ten times as much as another? Well, time to find out. Data analytics allows you to spot underperforming accounts and target them specifically.

It’s obvious that customer needs and abilities differ. A small mom-and-pop shop won’t buy as many supplies as a giant retail store. But that doesn’t mean you can’t try and encourage them to buy more.

Smart, personalized incentives can help boost the spending of virtually any customer. A BOGO offer, free shipping above a certain amount, better payment options, or future store credit  are just a few examples of incentives you can try with any underperforming account.

With the help of data analytics, you can figure out what makes each and every customer tick.

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