In today's hyper-competitive business landscape, a canned sales pitch is more likely to lead to the person on the other side of the line hanging up on you mid-sentence than an encouraging "please, tell me more."

Company data is the solution to fixing poorly targeted sales efforts. When you only connect with companies when there's a data-driven reason to do so, and tailor your messaging according to the prospect’s situation and needs, you'll significantly improve your hit rate in every step of the sales process.

Salespeople and gold miners have a lot in common. No, I don’t mean the tireless ambition, the deep-rooted desire to be successful, and the unstoppable drive for precious minerals. Instead, salespeople and miners share one key activity: prospecting.

The terms prospect, lead and buying signal are all well-known to B2B sales professionals, but their differences can be unclear. In part, the reason is that different CRM and marketing automation providers are using the terms in different ways. That's why we feel a clarification between prospect, lead and buying signal, and their roles in sales process, seems appropriate.

Our definition is very close to the framework used by HubSpot among others, and helps unify the conversation within a sales team, and further enhance sales and marketing alignment, or smarketing. Be sure to clarify sales terminology in your sales playbook!

During outbound’s period of greatness, the sales department at pretty much every company outnumbered the marketing department by far. As inbound grew stronger, marketing departments did the same and some companies came to only trust inbound activities to drive business to the company.

Today, the fastest growing companies in the world are doing both outbound and inbound, the frontrunners combining these two processes with a strong data-driven approach.

The most successful sales organizations are the ones working systematically. To do that you have to have clearly defined goals, KPIs, and relentlessly measure and monitor how your sales and marketing efforts contribute to help you reach them.

This is why performance sales development teams have well thought out KPIs that are being tracked daily, weekly and monthly.

With modern technology, the question is not what you can measure, but what you benefit from measuring. Following the right metrics will help you as a sales executive evaluate the performance of your team and steer them in the right future direction. Measuring the wrong or additional metrics will simply take precious time away from the things that matter.

Sales prospecting used to mean purchasing a static lists of prospects from one of the many vendors out there offering these.

In today’s hyper-competitive sales landscape static lists based only on basic firmographics don’t cut it for salespeople who aim for strong sales figures (don’t we all?). High-performers within sales use dynamic data and more data-points provided in a smart sales prospecting platform when looking for new accounts to approach with their offer.

Often when we talk about sales prospecting we talk about outbound sales prospecting. This is the process of finding new companies that match your Ideal Customer Profile, companies that you should reach out to and try to persuade into becoming your customers.

In this article, we'll instead focus on inbound sales prospecting. Inbound sales prospecting is, simply put, about scrolling through leads that marketing automation workflow provides.

Sales prospecting based on guesswork is not only tedious but also expensive. Experienced salespeople can expect to spend 7.5 hours of cold calling to get ONE qualified appointment, according to a Baylor University study.

By trusting data instead of your lucky star, you can increase the quality and efficiency of your outbound sales prospecting significantly and improve your call to meeting hit rate. But it can only be done if you have a deep understanding of your Ideal Customer Profile.

To succeed with data-driven outbound sales prospecting, you’ll need a scalable solution for collecting data about your current customers and prospects. Then you’ll have to apply machine learning to it to generate useful insights about the companies. Machine learning, a sub-category of Artificial Intelligence, is basically an enormous correlation engine.

Whether it’s to monitor marketing or to keep track of customers, technology in B2B these days cannot be escaped. The technologies that companies use leave digital footprints, so-called technographics, that can help you as a salesperson understand their identity or future direction.

The decisions companies make regarding technology can reveal useful account insights on prospects’ intentions, their priorities and the way they want to run their operations. Using technographic data in sales prospecting refers to salespeople’s attempts to better understand their prospects by analyzing their technology stacks.

A company’s industry, number of employees or location doesn’t reveal much about its needs and interests. This type of company information is often referred to as firmographics. It has significant value to salespeople who target companies in a specific industry or a chosen size-range as it allows them to quickly filter promising prospects out of a longer list of potential customers. However, firmographic data doesn’t reveal enough details about a company's organization and current situation to help you find those hidden gems you should go after right now.

If you’re a salesperson in forefront you combine firmographics, technographics (data showing a company’s online profile and technical tool-box, etc.) and insights from buying signals when sales prospecting.