What if I told you, you could increase your conversion rates, make the sales team happy with their marketing leads, and increase communication and rapport between sales and marketing? Sounds like a dream!
Enter Lead Scoring.
What is the benefit of lead scoring?
At a high level, lead scoring has the potential to tell you who is most likely to convert from a sales call – that low hanging fruit if you will. Behavior score tells you who wants to do business with you based on the actions they’ve taken on your site, whereas demographic scoring will look at who your company has determined to be a best fit for your business.
Why does lead scoring matter?
Lead scoring is one of the best ways to tell your sales team that a person is ready for outreach, or that a current customer may be interested in other products or services. It can be integrated with your lifecycle to indicate a person’s level of readiness – engaged, qualified, or on the flip side – stagnant/disqualified. It helps to prioritize people for outreach, and if done right, increases trust between the sales and marketing teams. Either way, it is all automated, which is the best way to provide value.
How should a company optimize lead scoring?
Analyze existing data
Pull reports on the people involved in opportunities and try to categorize job titles, industries, countries, company size, job roles, etc. If you already have personas built out, it’s a great place to start, but sometimes going directly to the data will show you a better story. Check activity history prior to conversion, sources or UTMs, to see if there’s a common first touch, last touch or pattern that helped push them to an opportunity stage.
Talk to Sales
Sales is critical to the lead scoring process. Sales is your client, and they need to have a seat at the table, and without buy-in from them, this will be a lot harder. You do not need to ask every sales rep at the company, just someone who is willing to provide insightful input on what they look for.
Create a spreadsheet and indicate the actions and demographics you’d like to score on. Determine a threshold for passing over to the sales team and base scoring on percentages of that number. For a first pass, don’t overthink it – you can turn this on and have it running in the background to see how it’s working and if it’s a good indication for “fit” before rolling out to the sales team.
Test some combinations out, too – see what an ideal candidate looks like based on your scoring model vs. mid-tier vs. bad candidate. What actions, if any, do they need to take to pass over to sales? What happens when a bad candidate takes a lot of actions? This will help confirm or update your current method.
Keep it simple
- Reduce triggers:
- Demographic scoring is fairly static and can be done at any time. Integrate it with a some sort of initial processing program to reduce “person is created” triggers and to time demographic scoring to run after enrichment to get the most accurate information.
- For high volume behavior scores (clicks, page visits, etc), reduce to nightly batches.
- Use program level tokens: Keep all the data in one place for easier scoring updates
- Analysis paralysis will keep you from launching when really, you just need to start collecting data to work off of.
- Every campaign is not a priority. If you’re sending over every record that engages at any level, your conversion rates will drop, and sales may not want to continue to work marketing leads.
While a combined Person Score (behavior + demographic = person score) can indicate sales readiness individually, my personal favorite solution is to do alphanumeric Person Ratings to give a better idea of what the person did to become qualified.
It’s a super simple set up with just a few additional fields. Bucket demographic scores from A-F (or whatever makes sense to you), and bucket the same for behavior scores from 1-7 (again, or whatever makes the most sense based on your scoring). When demographic score or behavior score changes, run the program to assign a rating. When these change, run Person Rating to concatenate the two. Voila! What used to look like “Person Score= 100, call right away” now looks like “A4” (really great fit for the company, hasn’t done a ton of activity) or “D1” (Not a great fit but they really love our company).
Integrate with lifecycle
Use person score/rating to drive pre-sales lifecycle stages such as engaged or qualified. When a person has become nurtured or recycled, reset their behavior score so they have to take some time to bubble back up. For disqualified, reset all of their scores and restrict from scoring again to avoid confusion.
This one’s hard to do without an ABM tool, but not impossible. If there’s a list of target companies or if your CRM is associating leads with accounts and can indicate it on a field, use these to increase scoring. I’ve seen subtle increases and immediate MQLs – do what’s best for your business.
Schedule time to review the amount of records in each scoring bucket or rating and where they’re at in the lifecycle to indicate if adjustments need to be made.
Scoring is never finished; the number one biggest mistake I see is to treat scoring as a static and final project. Scoring should be shifting frequently to adapt to your business personas and changing behavior in the market. Seeing a lot of high scores in disqualified/nurture stages? Seeing low scores getting converted? Time to adjust.
Any data is good data to start from for scoring, but the above tips will help you get the most value out of your lead scoring. Lead scoring is at the core of a lot of marketing efforts and can be an easy way to communicate automatically with the sales team and increase trust and conversions from demand gen activities. Don’t sleep on lead scoring – optimize asap!