Both Marketing and Sales Automation are crucial to the success of B2B sales.
|Purpose||To automate the creation and nurturing of a lead by delivering the right content at the right time based on action previously taken (or not taken) by the prospect.|
To provide intelligence on the buying intent and readiness of marketing created leads and automate the handoff to the next step based on lead scoring and grading.
|How it should work||Should be set up to send targeted messaging to a targeted list in the right logical sequence, grade and score the leads based on the action they took and their profile (title, company size and industry, etc.), and automatically flag the right high-scoring leads in the system that Prospecting and Sales work with.|
|Purpose||To automate, facilitate, and accelerate the time consuming and expensive one-on-one new customer-acquisition related activities in which your Prospecting and Sales teams typically engage.|
|Used by||Prospecting, Sales|
|How it should work||Marketing Leads should only be made available in the CRM used by Prospecting and Sales when that lead is ready to be further qualified.|
The system should enable the Prospecting team to see their high-priority work views (those they have already contacted but have not yet fully qualified) separately from their general prospecting pipeline (those they haven’t touched at all or are still pursuing to make first contact).
The final status of the lead here is SQL (Sales Qualified Lead), which means the lead is qualified and has agreed to a meeting with a sales rep.
The system should be able to do validation and ensure that all the necessary fields are filled out.
The system should automatically assign the lead to a sales rep and send the rep a notification email without the Business Development Rep having to do anything further than changing the status when all fields are completed.
Such automation ensures data integrity, accelerates sales, and avoids human error.
Figuring out how much to pay for Automation
There are several marketing and sales automation tools available, and at significantly varying prices. The question is, how much should you pay for a given automation tool?
The answer, generally, is that it depends on what you need—more capability and flexibility comes at higher prices.
However, we think that a better answer comes from considering its impact on the productivity of your various teams. Remember that your payroll is likely the single largest expense category for your company. You should seek to automate anything that improves productivity (improves the ability of the same employees to do more without working longer hours).
Here is a simple analysis to make the point. Let’s assume that your average, fully burdened salary for a member of your marketing/prospecting/sales team is $50,000 per year.
Product A is clearly far cheaper than Product B. However, Product B can improve productivity by 10% while Product A can improve productivity by only 5%. In the end, Product B is the superior value since the question is not just how much the product costs, but how much impact it has on your operations. The last line compares the two numbers by dividing the net value by $50,000 to arrive at the net productivity gains.
| Product A || Product B |
|Fee / user/ year ($)||300||1,800|
|Productivity Gains (%)||5%||10%|
|Productivity Gains ($)||2,500||5,000|
|Net gains ($)||2,200||3,200|
|Net gains (%)||4.4%||6.4%|
The Issue with Data—What is too much versus too little
One of the recurring problems we come across is that the management’s need for data is at odds with its need for employees to keep their work simple and efficient. If you want a lot of data, then you are asking your people to spend more time on data entry and less time on what should be their primary work. Automation can help free your employees from carrying out mundane, repetitive tasks, allowing them to do more valuable work.
The key is to get the data you need as a natural outcome of the work they do. This is a lot easier said than done, and any system that you use must be thoroughly evaluated before implementation.
The first step is to identify the essential data you need to qualify a lead and move her through your sales stages. This should not require much data, but it should be clear to all your teams that without this information, they are likely to waste a lot of time and effort trying to engage the wrong people.
On top of that, there may be additional data you want to collect, but be judicious and let employees provide this in a free text format rather than forcing them to enter into discrete fields. You are far more likely to get useful information this way, since forcing them to enter data could prompt them to just click on something to get past your validation.
The end goal is twofold: to provide employees with reports and dashboards that help them manage their day-to-day productivity, while you gain insight on what is working and what isn’t.
Make these two goals converge, and you will have plenty of high quality—and useful—data.
Read about the final Critical Success Factor, “List Management”.