How to choose the right Client Relationship Management (CRM) solution

Many businesses today rely on client relationship management (CRM) systems to segment data and target clients. Despite the need for a reliable solution, most CRMs are impractical and sometimes even hinder user productivity.

In our many years of experience, the biggest of these problems (and most other software systems) is ease of adoption. CRMs were made to help users scope and keep up with their contacts and projects. Ironically with most CRMs out there, the opposite is true. They're clunky, difficult to learn, and counter-productive since they usually require you to remember to manually enter data or synchronize contacts. Overly convoluted systems can hinder the sales process and consequentially averse team members from even using the "solution". In order to have effective adoption it's imperative to have a solution that your team will actually love to use!

So how does one decide which CRM will work for their team? Understand this; most employees need a system that eases their workflow and maximizes their productivity. If users reject the existing CRM system, you need to take a step back and reassess what the problem is. Does it require too much manual data entry, does it not automate tasks well, are integrations to third party applications limited? These are all important questions to ask before you make a decision on which CRM to purchase. Focus on your team's needs and more importantly, on existing pain points. We see many CRM solutions pretending to be cloud and easy to use -- don't get blinded by their shininess because they're worthless if your team won't even use them.

Using a CRM that reduces, or altogether eliminates, manual data entry is incredibly important. Studies have shown that on average, sales rep spend nearly 6 hours a week entering activities and contacts into a CRM. This cripples performance and eats up valuable time. Copper scrapes contact information from your inbox to pre-populate it in your CRM so that you can add email addresses, phone numbers, and other contact data with a simple click of a button. You can also automatically link to all related emails, files and calendar events across the entire company. It's a powerful CRM that saves heaps of time while mitigating data inaccuracies.

Simply put, use a CRM solution that is easy to adopt, easy to implement, and easy for your team to use. Our recommendation is Copper. It's a true cloud based CRM that is by far one of the best looking, functioning, and usable CRMs out there! It was purposefully built to seamlessly integrate with the tools many sales teams are using, such as G Suite. It's not only an aesthetically pleasing CRM, but one that's very easy to work. If you know how to use Gmail, you know how to use Copper - there's barely a learning curve and your team will be delighted to use it. Copper knows very well that sales teams spend most of the day sending messages, scheduling meetings and creating follow-ups via email, so they created a system that resides right into your inbox so once you download the Gmail or Inbox Chrome Extension, every communication is in one centralized place.

With Copper, users reap the benefits of enhanced customer acquisition and retention, sales automation, and a repository of all customer information. It works perfectly from small to medium sized businesses to larger companies like Udacity and Peugeot. It's a scalable solution that helps get the job done simply and beautifully. Have a feeling your team could be more productive? Click here to try Copper for FREE or contact us to learn more.

Machine learning in G Suite - How it increases productivity

Humans have been evolving rapidly over the last few centuries; from the agricultural age, to the industrial age, to now the information age. As we evolve so do our tools and the ways we interact with them. Take G Suite for example. Just over the last few years, G Suite has evolved from more than just an email and contacts solution, it now has the capacity to anticipate your business needs and facilitate collaboration and productivity at an unprecedented level.

Formatting documents, email management, and creating expense reports. These are just a few of the common time-consuming tasks that negatively affect productivity. Time spent working on tasks that do not directly relate to a creative output is costly and is referred to as 'overhead'. Unfortunately, huge overhead is common in most businesses and hinders valuable potential. According to a study by Google in 2015, the average worker spent roughly 5 percent of their time actually coming up with the next big idea. The remaining 95 percent of the time was dissolved in the form of formatting, tracking, analysis or other mundane tasks. With all these tools and efficiencies, one would think the percentages would be reversed. To make this possible, Google introduced what's known as machine learning.

What is machine learning? Essentially, machine learning algorithms observe input examples and make output predictions based on data. In G Suite, machine learning makes your workday more efficient by handling menial tasks, like scheduling meetings, or by predicting information you might need and surfacing it for you, like suggesting Docs for example.

Ever notice how you received less and less spam over the years with Gmail? One of the first applications to use machine learning was Gmail. Historically, Gmail used a rule-based system, meaning Google's anti-spam team would create new rules to match individual spam patterns. With over a decade worth of data and using this process, Gmail improved it's spam detection accuracy to 99%! It's now one of the most secure and spam free email applications in the world. To take it a step further, in 2014 Google augmented the rule-based system to generate rules using machine learning algorithms instead. This took spam detection to another level which now allows Gmail to continually regenerate the “spam filter”, so systems learn to predict which emails are most likely junk. Naturally, machine learning finds new patterns and adapts more quickly than previous manual systems - it’s a great reason for why there are more than one billion monthly active Gmail users today!

The goal of G Suite is to help teams accomplish more with an intelligent range of applications, no matter where they are in the world. Smart Reply for example, uses machine learning to generate three natural language responses to an email. If you find yourself away from the office or time-restricted and are in need of a quick way to clear your inbox,  you can let Smart Reply do it for you. Click here to learn more about Smart Reply.

Explore in Docs, Slides and Sheets uses machine learning to eliminate time spent on things like tracking down documents or information on the web, reformatting presentations or performing calculations within spreadsheets. The whole point of these tools is to help the user accomplish more with less.

Another great example of machine learning is Quick Access in Drive which predicts and suggests files you might need within Drive. Quick Access intelligently predicts files based on who you share files with frequently, when relevant meetings occur within your Calendar, or if you have patterns of using files at specific times of the day. Using predictions based on recent Drive activity greatly increases a users productivity and efficiency for day to day work.

To learn more about how machine intelligence can make work easier, check out this video from Google Cloud Next with Ryan Tabone, director of product management at Google, where he explains more about “overhead.” G Suite was made to make businesses run faster, smoother, and more efficiently. If those are things you're looking to adopt for your organization, give us a shout! We'd love to hear from you and discuss the possibilities for you business IT solutions.