You’re staring at your screen, trying to determine the point value for email opens. Should it be one point or two? Zero? You move on to forms. You go with your intuition: ten points.
Lead scoring allows you to identify your most interested prospects based on their engagement with your content. People earn higher scores when they take action: opening an email, submitting a form or clicking a link to a whitepaper.
You can use sores to determine when to assign leads to sales, to segment your audience for emailing purposes and to maintain your database. But, as with most marketing automation features, there are some complexities to discuss (and some swampy territory to avoid).
A scoring model determines the number of points you want to allocate for each action. Building a lead scoring model can seem like a complex task. Example: you have multiple forms at different stages in the marketing journey. Should you adjust point values for specific content pieces or keep them consistent for all forms? Should you increase scores incrementally or only with the first action?
When approaching lead scoring, I have learned some guiding principles and found some important considerations for the technical side of things.
Focusing on simplicity
A former client inherited a HubSpot account from someone who had left the company. Looking at the scoring property, I scrolled (and scrolled) until reaching the end of the long list of rules.
We didn’t know where to begin. There was no documentation. Some rules referenced lists that referenced other lists. Deleting a rule would remove those points from anyone who met the criteria in the past. It was…tangled.
The client wanted to make the model simpler, because, of course. In the end, we decided to just start fresh.
A broader scoring model, with fewer rules, can be adjusted more easily. It can also be documented and explained with less effort. If you start from a more general foundation, you can always incorporate more granular scoring criteria as you need it, later.
For example, you could set a standard rule of a ten-point increase for all form submissions versus varying the points for each individual form, which gets tedious and confusing. Or, you could adjust the scoring for a group of forms (e.g. top funnel, middle, and bottom). (In HubSpot, scoring for a group of forms can be automated through naming conventions, lists and workflows.)
Pardot makes simplicity, well…simpler. The default scoring model lets you adjust the values for a predetermined list of actions. Actions like email opens, email link clicks and form submissions line the left-hand side. In the right column, you can set the point values for each row. In HubSpot, where each rule has to be added individually, complexity is all too common.
Documenting your lead scoring model is key for maintenance, optimization and potential job transitions. I recommend using a spreadsheet, where you can list actions in one column (e.g. Form submissions, email opens, email link clicks, page views) and scores in the next column.
This provides a single location for all of your scoring criteria and point values. At some point, you might forget and find yourself wondering, “How many points did we decide on for the Contact Us forms?” With a handy-dandy spreadsheet, you’ll know where to turn.
Building your lead scoring model: a few things to consider
One factor to consider is whether you want scores to increase incrementally. Should a lead get points for their first email open only? Or should their score increase with every email open?
Incremental scoring is built into Pardot. When you set a score for form submissions, that amount will be added each time a lead submits a form. In HubSpot, incremental scoring involves some extra configuration.
Both platforms handle scoring model changes the same way: changes will apply retroactively. So, if you decrease the score for form submissions from 20 points to 10, scores will drop for anyone who submitted a form in the past, immediately and across the board.
When setting your scores, the right point values will vary depending on your content and your audience. I tend to think about the level of interest indicated by a particular action. I often set one point for email opens (not always a strong sign of interest) and around five points for form submissions.
Protip: Wondering why not just make form submissions 100 points? It can be tempting. There’s something satisfying about scrolling through a list of high scores – look how successful your marketing is! Reigning in that urge, though, makes your lead scoring more meaningful. Setting a high point value for one action allows scores to creep up while not always reflecting the person’s interest. Lower values require more points of engagement in order to achieve a higher score.
Making use of scores once your model is in place
You can use lead scores to build your email recipient and suppression lists, maintain your database and assign leads to sales. You might build a list of leads with a score over twenty for a bottom-of-the-funnel email with a free demo offer. On the other side, you could send an eBook on industry best practices to your audience with scores between five and ten.
Lead scores can also be helpful for suppressing folks from your emails. After a month, if Jamal has a score under five, it could be a sign he’s not interested at this time. You could create a Smart List (or Dynamic List in Pardot lingo) to populate with records that were created over thirty days ago with a lead score of zero. This could serve as a suppression list for emails. You could use a similar list (maybe extending the time frame) when identifying records to remove from the database.
Or, instead of building a suppression list, you could automatically decrease scores when leads haven’t engaged in some time (ex. If someone hasn’t opened an email in thirty days, decrease their score by five points). This could be done through negative scoring in HubSpot or by using automation rules in Pardot. By decreasing their scores, disengaged leads will automatically be removed from your dynamic lists (those that filter by score).
Scores can also be used to move folks to a MQL status and to trigger an assignment to sales. Many organizations use marketing qualified lead (MQL) to indicate that a lead is ready to talk to a salesperson. You’ve done your work, creating stellar content and delivering it at the right moments, and are now giving the green light for the next step. (A latte, cookie, or some other treat is in order.)
Finding the right score to move someone into an MQL status usually requires some trial and error. Seeking feedback from sales could be an effective way to determine if the score is too low or too high. In a previous role, we used a target score of twenty to trigger MQL. This was based on a model using relatively low point values (one point for email opens and five points for form submissions). It can be helpful to map out some potential pathways for reaching your target score.
A final caveat or two…
Don’t forget to consider whether your high-scoring leads are anticipating a direct outreach from someone in sales. Asking for an opt-in ahead of time through a checkbox could help set the expectation (and maintain compliance).
It’s also important to remember scores are just one data point. They can help with gauging a lead’s interest in your content. But a high score may not always equate to interest in becoming a customer. (A score of 100 from Julie could be a sign of serious interest. It’s also possible her son took over her laptop and really liked clicking the submit button.)