Automating your Lead Scoring Process

Automating Lead Scoring

In today’s fast-paced sales environment, millions of potential buyers can find your business online. As you step up your marketing efforts and increase your online presence, a steady flow of leads, interested in your brand starts coming in! If you're using marketing automation and a CRM, your amazing content is constantly feeding your funnel, and generating more leads automatically.

For this inflow to have a net-positive effect you need to adapt and scale your processes – as the number of leads goes up, the importance of identifying the quality of leads increases as well. You have limited resources and scaling up to personally interact with each lead is impossible. We need to quickly segment out high conversion potential leads, so the finite human resources available are allocated towards moving these leads along the sales pipeline. Lead scoring helps with this!

Lead Scoring assigns leads quantitative values indicating their “hotness” or potential to convert. This objective process simplifies and streamlines how your team prioritizes leads, depending on their actions and behaviors. The best part? Once you pinpoint the intuition and qualification triggers your team uses, the scoring can be automated to update dynamically so you always know which leads to focus on and are empowered to work more efficiently and quickly.

Stats-Lead Scoring

How did sales teams always do this?

Assessing buyer intent has been around long before automated lead scoring – In fact odds are you already do this in some way, whether it’s a manual review, or a spreadsheet, or looking for certain phrases in calls.  As with most things in Marketing Automation, first, identify your current manual process and then think about using your Martech stack to automate and scale these processes. Use a process-centric approach instead of feature-centric.

So what does this manual qualification look like? Each salesperson probably has a massive excel file, with thousands of contacts they are in charge of. They then contact each person individually, hoping to close a sale – sounds like finding a needle in a colossal haystack.

Since lists aren’t dynamically updated, and there is no coordination or transparency between salespeople, there are tons of discrepancies between each list. Handoffs become a nightmare and nobody knows the definitive status of each lead. Salespeople are forced to work in silos. Our figurative needle in the haystack needs to be found by checking every single strand individually. This always starts with chaos and can lead to full-blown anarchy! In the process, you lose deals and resources are wasted on unqualified buyers.

Source: Hive9

But with modern marketing and sales tools like FunnelBud, these spreadsheets (and the possible anarchy) are a thing of the past. Once set up, the lead scoring is completely automated. While it requires some initial collaboration and brainstorming to identify triggers, once in place, it can help you cherry-pick the best qualified high potential leads and allocate available resources at each stage in the sales pipeline accordingly. In our figurative haystack, lead scoring becomes a magnet to quickly zero in on each needle in the pile.

So what is Lead Scoring?

Simply put, lead scoring quantifies the quality of leads in your system, so resources are used more effectively, focusing on leads that have the highest probability of converting.

A high lead score reflects a lead’s high level of engagement or fit with your target demographic. It is indicative of their interest in your brand and ergo their probability of converting. Conversely, a low lead score indicates the lead has lost interest or isn’t a good fit,  and hence has a low conversion probability.

Lead scores can be a super-effective tool for teams across your entire pipeline and can simplify handoffs. Marketing can quickly qualify Marketing Qualified Leads (MQLs) for the sales team and sales in turn can provide personalized, memorable experiences to the best fit leads. Increasing the chances of closing each deal while reducing the resources spent, hence increasing your ROI.

Once we’re able to identify the actions that indicate buying intent, the lead scoring process can be automated to award points for these actions and segment leads based on a range from interest to intent.

Lead Score Triggers

Why is lead scoring important in your Martech stack?

In a modern inbound marketing machine, lead scoring makes sure you use your technology and personnel as effectively as possible. As your marketing team starts putting out content to attract your target audience, leads start increasing exponentially. Of course, not all of these leads are qualified buyers, and some will be lost at each stage of the sales process.

With this exponential growth, scaling a manual qualification process requires investing more and more resources, without guaranteeing the proportional returns. Lead scoring is the more efficient and scalable way to qualify – using the actions leads have taken with your site and content, it filters out ones that have the highest probability of buying. With these leads identified and segmented out, your limited resources can be spent more effectively, capturing deals where you have the highest probability of converting. 

Lead Scoring can also provide your team with signals for when an inbound lead is ready for more targeted and personalized communication directly with a salesperson. For instance, a new lead may be scared away if they receive a call from a salesperson in the very early research stages. On the other hand, a lead who has viewed a custom pricing page, or requested a quote would appreciate the personal communication at that stage.

How does Marketing use Lead Scoring?

Whether using an outbound strategy, an inbound strategy, or a hybrid, most marketing teams generate large quantities of leads from their campaigns. Since this is usually the first interaction most people have with the brand, the lead list has not been checked for quality yet and not all of the leads will be qualified to move on to the next stages of the process. 

In order to help sales teams, the Marketing team qualifies leads before passing them on as Marketing Qualified Leads (MQLs). Lead scoring helps automate some of this qualification work making both marketing and sales teams more efficient. For instance, if a particular lead performs certain actions usually indicative of their readiness to buy – like visiting the pricing page, scheduling a meeting, looking at specific setup pages in a help guide, or even reading blog posts comparing your competitors – this can tell marketing that they are ready for someone from sales to contact them personally to understand their needs and close a deal.

With these signals, marketing teams can take an educated guess that this particular lead is now ready to close. However, monitoring these actions for thousands, or even hundreds of leads is virtually impossible and would take up all the time of your marketing team. So with a lead scoring system, when set up effectively, we can look for these actions automatically and simply pass a manageable percentage of system qualified leads to a human for further qualification – drastically reducing the resources needed and increasing your ROI.

Okay, but how do I set it up?

As with most things in marketing automation, the golden rule is – make the system fit your needs, not the other way around. Setting up your lead scoring is a continuous and dynamic process that you should be calibrating as you learn and your processes evolve.

Looking at your existing data is a great starting point. Remember – the most useful and time-saving automations are ones that emulate repetitive manual work and as a result eliminate it. To set up the lead scoring mechanism accurately, you’ll need to coordinate with various touch-points leads have in their buyer’s journey – because they can provide tremendous insight into what leads go through at different stages.

Start off by identifying a few leads who converted into customers. If you have an ideal customer profile or persona, aim to pick as many of those as possible in this test group.

For instance let’s say you find trends in the sample set like:

  • 80% of the sample looked at the pricing page just before buying

  • All users look at the blog post comparing competitors

  • 90% of serious buyers provide an address

You can then reasonably hypothesize that:

  • Existing leads who look at the pricing page are lending towards buying and should be contacted by sales

  • All buyers look at the competitor analysis page, however, so do all non qualified leads – hence this is not a buying signal (however, this can be a trigger to send relevant nurture content)

  • Unlike “window shopping” leads, serious buyers provide a mailing address. This action, along with regional filters for your service area, can be a qualifying signal indicating high buying potential

Using your data list down such trends and weigh their correlation to how qualified the leads performing the action are (ex. Lead gets 5 points on visiting the pricing page; if they have a mailing address add 3 points; if they are in Chicago, Illinois add 2 more points).

Lead Score Triggers

You should also look for negative signals. Using the above methodology, collect a data set of leads disqualified by your team and find trends among them compared to the rest of your database. For instance –  Leads with a Gmail address are not serious buyers (B2B businesses do this); or leads who visited your blog, then don’t engage with any other content in the next three months have lost interest. These signals indicate a lead is not likely to convert and your team could spend resources elsewhere to achieve results.

With a few of these positive and negative signals, you’ll quickly have the beginnings of your automated lead scoring system. But this is a continuous process – Keep looking for such signals across all teams, use a test group to confirm if they are indicative of buying intent, and add them to your scoring mechanism. Eventually, this grows into a robust, dynamic and accurate metric for your teams to use when allocating resources to leads.

This secondary qualification can (and should) be automated as well! This ensures your sales team get the highest quality of leads and they can focus on what they do best – closing deals and ringing that sales bell.

Just like we did for the MQLs, collaborate with your sales managers to identify the qualification (and disqualification) metrics they look for in their manual process and find trends in the actions SQLs that converted took. Once identified, these conditions can be used to trigger increases and decreases in the lead score for SQLs.

So what does this all mean for me?

Lead scoring is a great way to better allocate resources and get a high ROI from them. Chances are you already use some sort of mechanism to qualify your leads, however, with some work and analysis, it’s possible to emulate and automate this mechanism, saving your teams a lot of valuable time. Additionally, your lead score can act as a measurable metric to help you optimize your approach to marketing and selling, by identifying what works and what doesn’t.

While Lead Scoring systems can be built to accommodate even the most complex qualification metrics and intricacies you can imagine– it’s best to start small and easy, and then continuously build from there to make your system better and as accurate as possible.

If you’re looking to get started with Lead Scoring, Marketing Automation, and increasing your ROI while building the scalable and effective marketing and sales machine you always wanted, feel free to book a no-obligation consultation with us.

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About the Author

Gaurav Jagiasi

Gaurav, the youngest Project Manager at FunnelBud, has extensive experience working with lean startups and emerging businesses. He enjoys advanced strategy planning and implementation; and automating complex processes into robust, scaleable systems. Gaurav studied Systems Engineering and Design at the University of Illinois Urbana Champaign.

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