The task of your marketing activities is to deliver qualified leads to your sales people. The higher the quality of the leads you pass over the more efficient the sales process will be. Ideally you only want to pass over pre-qualified leads that are most likely to generate sales.
If the number of leads you're generating is small then it's perfectly reasonable to use a manual approach to qualifing those leads, or even just dealing with all of them as potential sales. As the reach of your marketing campaigns grows you'll start to generate more leads than you can comfortably manage by hand.
The solution is a lead scoring process by which each contact is awarded a number of points. The higher the point score the higher the quality of the lead. The number of points each contact has can move up and down depending on how much you know about them and how well they engage with your organisation.
Rather than have to manually score each lead it's generally more practical to automate some aspects of the ranking scheme through a set of scoring 'rules'. Getting these rules correct is the key to the success or otherwise of such a process.
You could for example decide to award points to people that complete a specific form, visit the pricing page on your website or click on links in your emails. You could also award points for contacts in specific industries or those using a corporate rather than free email address. How many points do you award for each of these activities though?
Not all contacts are created equal!
Consider the case where you're an engineering company making quite expensive 'Widgets' for the aircraft industry. You've commissioned some really good research into the widget market and you're making this available as a download in return for contact details.
As a result of your efforts you've collected contact details for 100 people. These people are now receiving your regular emails and some of them are taking you up on subsequent automated offers. They are engaged with your proposition. Your lead scoring rules need to take this activity into account and reward your most engaged contacts with extra points.
Should they all get the same number of points though?
From the data you've collected you can see that (A) works for Sky Train Industries, the biggest manufacturer of passenger planes in the world. (B) on the otherhand works for Sky Plane Models, a small producer of model airplanes. Regardless of how engaged (B) is with your content he's unlikely to become a customer!
In the case of (B) you want him to continue to receive your literature but you probably don't want your sales team to be giving him a call any time soon.
This case illustrates how you need to adapt your scoring rules based on the contacts you have rather than taking a one-size-fits all approach.
What goes up…
While careully crafted rules can be used to push up the score of individual leads it's worth thinking about the longer term. If your contact at Sky Train Industries is engaging with your content on a regular basis their score will gradually increase until they reach a certain threshold and then you'll pass the lead over to your sales team. On the other hand if their engagement drops off what do you do with their score?
If you do nothing then a contact can sit at a pretty high score in your system having not engaged with your for, say, several years.
The answer here is to decide on an aging policy for the score and then have your systems automatically degrade the score over time. For example you might decide that each month in which you have no engagement with a contact, your drop their score by 10%.
This policy provides two benefits. Firstly, if you search your contacts based on score the results are not going to be cluttered with dormant but high scoring individuals.
Secondly, you can track scores that are dropping and 'do something', such as send them a special offer or review the data you have to see why they may have lost interest in your organisation. It's possible that individual has left the organisation and it's worth the time finding a new contact in the same organisation.
As with increasing scores, the rate at which you decrease scores is likely to be different for your various communities. For example if you have highly scored contacts that are close to the sales call thresold you might want to decrease their score faster than other contacts in order to trigger corrective action faster.
Adding automation into the mix
Think about the thresholds you want to put on your scoring system. On the one hand, a score moving above 500 might be a signal that you should be passing that person over to your sales team. Dropping below 200 on the other hand might mean a special offer. These threholds should be configurable and should be able to trigger actions directly.
A high-going threshold should be able to create a task in your CRM system to schedule a sales call. Crossing a low-going threshold should be able to trigger the start of an automated 'engagement' story.
Developing your rules - the first stab
The rules you use for scoring your contacts will be unique to you, but you have to start somewhere! While you're manually tracking your contacts look for patterns that might help you identify those that are more likely to convert into clients. Some things to consider for your first iteration include:
- analyze those leads that became paying clients. What do they have in common?
- are they predominatly from specific business sectors?
- did they find you through specific channels?
- which techniques worked best to capture good leads? Whitepapers? Guest articles on third party sites?
- how long is the sales cycle from new, unqualified lead to client?
- what indicators are there that a warm lead is cooling off?
If you're starting from a small base of contacts it's unlikely in the early days that you'll have sufficient data to get your rules right from day one. It's better to be more liberal in who you qualify until you have more confidence that the rules you have correctly identify good leads.
Once you have initial rules decide on a 'test' period in which you run both your previous process and the automated scoring in parallel. In this period don't use the rules to make decisions but look for correlation between what the rules are telling you and what happens with a contact in practice.
Keep your rules under review
Once you have your initial rules, you've run through your test period and are happy with the results you're getting it's still necessary to periodically review your settings. Things you need to consider are:
- do I need adjust how I categorise my contacts?
- are the thresholds correct? Are the right leads being passed through to sales?
- too many poor leads and the thresholds may need increasing
- too many lost opportunities and they may need to be lower
- has the behaviour of my leads changed over time such that I need to adjust the rules?
- are their easy ways to quickly disqualify a new lead?
As with all things - keep your process under review and refine as necessary!
If you'd like to understand how Lead Scoring could improve your sales process then book a free consultation.