A lead’s fit with your product or service isn’t always obvious from one or two metrics, and without understanding fit and interest, you can waste valuable time and resources on the wrong leads. Lead scoring lets you focus on only the best leads by giving you a better picture of how likely they are to buy.
It’s also a great way to identify the best leads for lead-nurturing campaigns and to test your assumptions about your target market. Before getting started, find out more on why lead scoring can be invaluable for campaign optimisation and get to know the basic steps in creating a scoring system.
What’s lead scoring and why use it for campaign optimisation?
Lead scoring involves assigning numerical scores to prospects, where the higher the score, the higher priority the prospect and their potential customer lifetime value is. Lead scores can be based on profile data like demographic data and firmographic (for firms or B2B) data, budget or spend category, and behavioural data. It can also be based on the lead’s current location in your sales funnel. From this information you can score leads on things like size of purchase, likeliness to buy, and likely timeframe to purchase.
In turn, you can use lead scores to boost conversion, design targeted campaigns, and shorten buying cycles. Lead scoring enables your sales team to focus only on the highest priority leads – your “hottest” leads – so you’re not wasting resources on weaker leads that are less likely to convert.
Note lead scoring also lets you do other things. For example, you can identify the leads that need additional nurturing (low scoring prospects), or you can test whether your assumptions (based on the demographic, behavioural, and other data) are correct. You can also use lead scoring to identify your net promoters and loyal fans, so you can then reach out with incentives to maximise their impact.
When you might not need lead scoring
However, lead scoring might not drive campaign optimisation in some cases. Firstly, if your sales team isn’t overwhelmed with leads, you might not need to do lead scoring. Instead, you might want to concentrate on obtaining as many leads as you can, and you can decide to score leads at a later stage.
Secondly, if you decide lead scoring is right for you, make sure you’ve collected sufficient information to commence with it. You need to be armed with sufficient demographic information as well as behavioural data before you can score your leads.
Thirdly, if your sales team is complaining about poor leads only because you’re not on the same page about expectations, the solution could be to define expectations with a service level agreement rather than with lead scoring.
How to conduct lead scoring for campaign optimisation
You’ll want to have a lead scoring system that takes into account buyer fit, interest, behaviour, and other factors.
1. Ensure the lead is a good fit by identifying buyer personas
Your leads needs to be a good fit for your organisation, and products or services, so start with creating your buyer persona(s). Define your buyer persona according to things like demographic or firmographic data, along with their budget, authority, need, and timeline (BANT), and include the minimum criteria leads must satisfy to be a customer (such as age or location).
Go into as much detail about your ideal buyer persona as possible, as this will help inform your metrics for your scoring system.
2. List possible lead behaviour
As with the buyer persona (which is focused on characteristics and qualities), behaviour is important for identifying the most engaged and interested leads. In turn, this can be used to inform your metrics for your lead scoring in step three.
Examples of behaviours include email opens, clicks, replies, and forwards; social media shares; website visits; contact form submissions; downloads; trials; and product demos. Behavioural data tends to be more complicated than profile data, so once you have a full list, take time to identify the most relevant and useful metrics.
3. Decide on a system: determine criteria, reporting data, and points
Now you’ve got a list of characteristics, qualities, and possible lead behaviours, you can get started on what you want to measure. You won’t be tracking every type of behaviour, characteristic or quality – you’ll be tracking only the most relevant ones.
A basic template to start with could be a three-column table with criteria, reporting data, and score. For example, the behaviour (criteria) you’re measuring in a factor or metric is sign-up. The reporting data for this would be the creation of registration data. The point you assign for this could be one point.
You could add further detail by breaking up individual criteria or reporting data in terms of time (such as visited your site over the past five, 10, and 15 days), and giving these subcategories different weightings or points.
These points can be used in the context of a 100-point scoring model, like academic grading systems, or you could decide on a different total-points system. You can then designate things like a target lead score, which is a cut-off point that might be, say, 90 points or above. At this point, the lead becomes sales development rep ready.
You’ll probably need a bit of time, along with trial and error, to find out what your target lead score should be. As a general rule, that cut-off point should yield leads that have a 10% to 15% close rate within the duration of your average sales cycle.
Avoid over-complicating your system
Note your system won’t be perfect from the start, and it shouldn’t be too complicated or have too many scoring factors. By starting with a minimum viable scoring system, you avoid perfection paralysis and give yourself a foundation you can experiment on and keep refining. As a general rule, 25 and above might be too many metrics, while 15 to 20 factors might be the sweet spot for scoring leads.
Once you fill your table with a list of criteria, reporting data, and points, you’re ready to start scoring leads.
4. Incorporate lead interest into your lead-scoring metrics
Keep in mind the behaviour you choose to track in step three should reflect lead interest. A good fit doesn’t make a lead ready to buy, so track things like click-through rates, time spent on websites, and social media engagement. These types of factors are highly relevant when it comes to interest levels.
5. Ensure your lead scoring system is sufficiently detailed
While it’s important to avoid over-complicating your system, at the same time, review and refine your system so it’s sufficiently nuanced for your purposes. At the basic level, it needs to be detailed enough to help you separate the good leads from the best leads.
6. Start tracking and assigning points
Once you have a basic system setup, you can start tracking and assigning points. To simplify the process use a software tool that’s unified with, or part of, your marketing automation platform, as these platforms can help you pull and collate data from a wide range of sources.
Additionally, make sure you nurture your leads, ideally with a defined lead nurturing program or email sequence. For example, you can set trigger-based email sequences to activate once a lead reaches a given score.
7. Test and refine your lead-scoring program
Consider your current system a collection of assumptions you hold about your leads. It’s only a predictive model, but, when refined, it can be a highly accurate one that helps you achieve higher conversions while saving you time and resources in sales.
Achieve your lead scoring goals
Lead scoring can be a highly nuanced tool to guide your lead-nurturing and sales efforts. Take time to set up a system that reflects your target buyer personas, and ensure you’re scoring on interest as well as behaviour. With a sufficiently nuanced lead-scoring system you can easily prioritise your leads, drive higher conversions, and target your organisation’s resources more effectively.
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