Company Information

The most visited websites in the world are—of course—well-known websites for most of us. In the Top 10, we find websites such as Google, Youtube, Netflix, Facebook, and Baidu. No surprises there.

Comparatively, the Top 10 most visited websites in specific categories such as SaaS, FinTech, E-Learning, and Cryptocurrency, or the most common CMS, Analytics, and E-Commerce technologies used by the world’s most popular websites are probably less well known for most of us. However, that needn't be the case. This kind of specific information doesn’t have to be less well-known or harder to get a hold of.

In fact, we’ve recently added data concerning the 7 million most visited websites in the world to our company database, which makes it easy to get a hold of this kind of detailed website information. This dataset, combined with our proprietary industry data, allows for the effective analysis of website popularity across many different sectors. Let’s take a look.

The International Data Corporation (IDC) forecasts that the yearly global spending on digital transformation will reach $2.8 trillion in 2025. For the uninitiated, digital transformation refers to the adoption of digital technologies by a company, and it is generally pursued in the hope that these newly-adopted digital technologies will provide efficiency gains and customer intimacy.

The aforementioned statistic clearly highlights that the demand for digital technologies that improve existing business processes is, to say the least, significant. The growing demand for digital technologies presents an unprecedented opportunity for companies that are able to provide products or services that help businesses achieve these digital transformations.

Growth or revenue creation can be fueled by two mediums: selling to a new customer or selling to an existing customer. We’ve written about using data and analytics when prospecting and selling to new customers, but how does it translate when selling to existing customers? Now, it’s time to cover customer analysis so you can determine real upselling opportunities. 

Upselling to customers has traditionally had an unpalatable nuance to it. The sole objective has been to get the customer to buy more. I can’t help but think of that car salesman who’s aggressively overselling that four-door executive saloon, packaged in full options when your only need is to get from place a to b.

Knowing your customer in and out by way of effective customer analysis is what separates a pleasant buying experience from an unpleasant one. You’ll understand what your customers need and how to alleviate their challenges and pains with the right solutions.

Let’s get to it without further ado. 👇

Entering a new, unknown market is like being the new kid at a new school. The possibilities are endless when it comes to making new friends, or in the business world - finding new customers. Still, getting that first great connection can be more challenging than expected.

“Data-driven” is a popular term in the business world these days and it makes sense why: data is the helping hand that decision-makers have been needing. Data helps you troubleshoot your organization, understand your performance, and make better business decisions. It can’t come as too much of a surprise then that data is also of huge benefit for salespeople! By using the right data, salespeople will know whom to contact, when to contact them, and why to contact them. Knowing these things is part of what makes data an invaluable resource for the modern salesperson.

You’ve probably heard the term ‘data’ before. You’ve also probably heard that this thing called ‘data’ can help you make better and more informed decisions, as well as improving your performance. But have you ever been told what exactly business data actually is? Or what different types of business data are? Or how to implement its use? But, before we even get to that stage, have you ever been told where to find this data?

Even if your answers to any of these questions were no, then there’s no need to worry! These are all questions that this article will help you find an answer to so that you can become confident on the topic, more data-driven in your work, and see an improvement in your performance.

Nobody likes ads. And yet, we’ve never seen—and created— as many ads as we do today. If nothing else, the internet gave us the omnipresence of targeted ads.

Technology made it possible to create ads so personal and hyper-targeted that we tend to believe our devices listen to us at all times. The truth is algorithms know us better than we know ourselves. They’ve learned from the websites we visit, the articles we read, the people we follow, the products we purchase. All that data combined drives the ads we see in our social feeds every day.

In business-to-business, a similar experience is not that simple. For starters, in B2B there isn’t a single individual buyer. What a person reads, sees, or does in your website and social channels is only one piece of the puzzle. Behind every employee, there’s a company with its own challenges, needs, and decision-making processes.

Looking to sell in Europe? Find a company list and reach out, right? Well, not exactly.

Information has become our most valuable commodity. Skimming the top five results of a Google search makes us feel like an expert in any field, with enough knowledge to make an informed decision about our purchases, our health, the books we need to read, our whole life, or simply, our next dinner menu. Similarly, informed decisions drive the already long and sophisticated B2B sales process.

Sell. More. Faster. That’s the ultimate goal of any sales organization. In practice, this means round-the-clock pressure for salespeople to hit their quota, close more deals, and increase revenue. Salespeople are no strangers to stress.

But if stress starts to escalate out of control, and sales targets seem as challenging as climbing an eight-thousander without supplemental oxygen, you need to re-examine your sales process and figure out the stages you can tweak to boost productivity.

Customers come in all shapes and sizes. The type of company data you look at and the methods you use to make sense of it should depend on the nature of your business and your ideal customer profile.

When you're about to set up a framework for your data usage, you should first ask yourself about the resources you allocate to acquiring one single customer. Are your sales and marketing resources allocated to dozens, hundreds or thousands of customers or prospects? Depending on the answer, you'll need different types of company data and data analytics methods to improve your total sales.