How to use Predictive Analytics in your CRM for Truly Data-Driven Decisions?
Successfully implementing Predictive Analytics for data-driven decisions in your CRM requires more than just software.
Every successful sales team wants to become data-driven. Companies that successfully execute predictive analytics in their CRM are easy to identify.
They take care of their salespeople and successfully utilise their current data and processes. They employ the standard software and adapt them to their situation. Finally, they introduce Predictive Sales to CRM step by step and learn from their experience.
I have seen, worked and led over 40 Predictive Analytics CRM projects so far. While every company I was involved in was trying to become more effective, not everyone managed to take more decisions using data.
In this article, I will summarize the best ways of achieving the success of being data driven.
First, I will discuss how to transform your account management methods based on predictive analytics. I will assume that you want to employ an out-of-the-box predictive sales software instead of building your solution.
Second, I will discuss how to improve customer relationships based on predictive analytics. This article will not go into detail about the future role of salespeople, but I touched up on some ideas.
Change your Account Management Processes based on Predictive Analytics.
You have decided to implement AI-based predictive analytics in your sales organisation. You are convinced that this type of technology will give you a competitive advantage and move your team forward. Proper implementation of this technology is essential for you. Understanding how to use predictive analytics in your CRM for truly data-driven decisions is critical for you.
Predictive Analytics in your CRM helps your salespeople become more efficient than their competitors. The central idea of this article is the role of predictive analytics and artificial intelligence in CRM. AI does not replace humans. AI-based Predictive Sales Software do not replace salespeople. This type of technology supports and enhances the skills and abilities of your team.
Therefore, to successfully implement the best predictive sales software in your CRM, the interaction between your team and the technology should be the focal point. The second crucial aspect to consider is the current situation itself. All companies are distinct from one another. While account management processes are all different, here are some clues as to where to start.
Your current situation is defined by the assets you have: your sales processes and your customer relationships management system. A straightforward recommendation is to start from where you are. Don’t fall into the trap of thinking that none of what you have built over the last few years can be supported by predictive analytics. Successful executives adapt their processes to the technology.
Implement an Out-of-the-Box Predictive Sales Software
Although every company is different, there are standard ways of working in sales. To employ AI-based predictive analytics, you need to consider customer segments and use cases first. Furthermore, do not try to develop your own AI; use an out-of-the-box predictive sales software instead. Did you build your own CRM, or are you using standard software?
Twenty years ago, when I started my career in sales, most industrial distributors and manufacturers had developed their CRMs. Today, the picture is different. Successful B2B organisations choose standard solutions they can adapt to their customer segments and sales processes. By using existing software, your sales team can minimise risks and accelerate usage. Both effects secure your success and, consequently, your career.
A critical note on sales processes: many sales executives falsely believe they do not have formal sales processes to use. Thinking that because you have never written your procedures, they do not exist is a grave mistake. Whether if it is proper or not, every company has its own methods and practices. These ways of selling have left an imprint on your sales data.
For example, consider using your ERP data. In this unique dataset, all your past sales transactions are recorded. Gold. If your goal is to use predictive analytics in your CRM for truly data-driven decisions, implementing an out-of-the-box predictive sales software using your ERP data is the best possible start.
Learn and Improve your Customer Relationships based on Predictive Analytics
Implementing the best tool for predictive analytics in marketing and sales is the first step to improving your customer relationships. Predictive analytics CRM is an iterative undertaking, even if you start with standard software. Your team needs to learn how to use the tool. Learning is best done in small steps. They key here is to be “agile”.
Successfully implementing new software in your CRM landscape will most likely require new skills and attitudes. Every experienced sales team can change their skills and attitudes. However, in some cases, new team members will bring them. Think about hiring and adding new salespeople as part of your strategy.
Finally, suppose you implement an out-of-the-box Predictive Sales Software. In that case, the software vendor will offer you a suite of existing best-practices, experiences with other customers and micro-strategies. Use them.
Define specific milestones for the implementation of predictive analytics in your CRM. Applying predictive sales can only be done in an agile and iterative manner. No company gets it right the first time. Building momentum, defining key users and ensuring that the implementation enables managed change will safeguard your success.
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How to use Predictive Analytics in your CRM for Truly Data-Driven Decisions? Summary.
Properly implementing predictive analytics in a CRM is critical for distributors and manufacturers. Regardless of whether you choose one of the best tools for predictive analytics or develop your own, adapting account management processes belongs to your agenda.
Unless your company belongs to an unsuitable segment, I cannot stress strongly enough to use “off-the-shelf” products. In the coming years, predictive analytics CRM there will become mainstream, and you will be making a safer investment. Implement an out-of-the-box predictive sales software whenever possible.
Finally, learn and improve your customer relationships based on predictive analytics insights. Whether reducing churn, improving pricing, or increasing cross-selling, your customers will also profit from predictive analytics. Make sure you take care of them.