Most people have a love-hate relationship with their CRM system. Sales reps complain they waste hours each week doing data entry that isn’t used. Managers and execs aren’t happy when the CRM system does not reflect the actual sales pipeline, making accurate revenue forecasting impossible.
It comes down to aligning expectations, processes, and resources.
Your CRM system becomes a beast once you have numerous sales reps and other customer-facing staff using the CRM system. It normally needs to connect to other business software, such as ERP systems and email or marketing automation platforms. Each system pushes and pulls data, and people are always changing jobs.
The more you expect out of your CRM system the more you need to feed the machine. Even the most basic implementations require update processes or the contact data quickly becomes stale. This takes planning, processes, and defining responsibilities.
When planning a new CRM system, create an implementation timeline that starts with importing clean, accurate data into the system and put the processes in place to keep it accurate. Get this running smoothly before moving on to more sophisticated use cases. There’s nothing more frustrating, difficult to fix, and ultimately useless than layering complex data on top of inaccurate data.
Managing Your Customer Contact Data
Every CRM system implementation starts here whether you have any immediate goals or not.
Frequently when a company decides to implement a CRM system they want to jump straight to implementing and managing sales processes. You can do that, but if you don’t start with clean data you’ll likely soon be backpedaling and trying to clean up junk data in your CRM system while maintaining the data your sales team has put into the system.
Basic features: Contact management, Task Management
Implementing Sales Processes
Ultimately your CRM system needs to help sales reps work more effectively and close more accounts. Try to limit data that sales reps input to information that will help them improve their customer relationships and followup.
There are two reasons for this:
- Your main goal is to improve sales performance so you want them to use there time effectively.
- Sales reps will fear the CRM system will suck up a lot of their time and provide little value to them.
Especially during initial implementation, limit their data entry requirements to those things that will directly improve their sales effectiveness.
At the most basic level, sales reps can add notes and schedule reminders to follow up with prospects at a pre-determined date.
The CRM system is also used to manage opportunities and track progress towards closing deals.
As you get more sophisticated, workflows can be added that create pre-determined communications over time. These workflows can be a combination of sales rep emails and phone calls or other marketing touches such as direct mail.
Once you have clean data in place to can add data that allow you to make your marketing messages more relevant to customers and prospects.
There are two ways to do this… segment your contacts and send messages, or modify dynamic content within a message, to make it more relevant.
The other way is to personalize messages based on data in your CRM system.
Two ways to deliver these segmented or personalized messages are using email or marketing automation platforms, or direct mail.
Revenue Forecasting and Financial Management
CRM systems initially were focused on executives to give them better visibility on sales pipeline and revenue projections. Sales reps entered data that provided visibility on their pipelines and sales activity. Improving sales effectiveness was almost an afterthought.
While more focus is being put on increasing sales rep effectiveness, this does not diminish the value of providing visibility on sales pipelines and using the sum of all pipelines to make financial projections.
Regardless of how complex your CRM needs are, when implementing a CRM system start slowly and take the time to import accurate customer and contact data and to establish processes to keep the data accurate.