If I had an apple orchard - which I don’t - and I were in a hurry - which I always am, I would always go for the easiest fruit that was simplest to pick. After all, why would I want to get muddy boots in the corner down by the stream? Or, for that matter climb a wobbly ladder for the biggest apple of them all?
I would go for the low hanging fruit that I could reach from the ground, and I could pick dozens in a half hour.
Sure, a few might be rotten to the core but I would gain overall in terms of my return-on-effort. That completes our first session, Lead Scoring Methodology 101. Let’s shoot for the stars and graduate with Lead Scoring 105.
Lead scoring is a lazy way of doing things. It does not strip the fruit methodically from tree to tree. Instead, it uses logic - even math - to target the most probable rich harvests. Before you stress about the math, apps inside computers do most of that. If that sounds like magic let’s put lead scoring methodology to the test. Does it really work and can we prove it?
Lead Scoring 102: Some Early Evidence It Works
Petr Passinger, formerly from Kentico, thinks it works for sure. I singled him out because I have an affinity with him as a virtual apple farmer. Petr started ‘Trees for Bugs’ and ‘Dance for Trees’. You should tap on the windows of these two environmental initiatives sometime. They could be a power for good for all I know.
- 42% had greater return-on-investment they could actually measure
- 38% reported an improved rate of conversions of pre-qualified leads
- 31% believed their sales effort was more productive and effective
- 27% were experiencing faster sales cycles with less effort
- 27% were also able to better forecast sales income
- 19% thought their marketing and sales teams were working better together
So yes, lead scoring does help some - but definitely not all - Kentico’s clients single out leads with high levels of sales readiness. If you like, they were in their virtual stores to shop and they were ready to make a purchase. But why not the rest?
Lead scoring remains a statistical improbability unless we team it with real effort. The secret is the way we go about it, but that’s the topic of module 103. Only 48% of the companies in Petr’s grab sample used engagement and buyer persona match in a two-dimensional model, while 36% used a single indicator. A mere 16% deployed more than two dimensions. From where I sit, I think there should be a better way.
Lead Scoring 103: Getting Down to Nuts and Bolts
Marketing uses a variety of inbound methods to get leads onboard. The significant ones are keyword-related content on Google, email marketing, social media programs, and the fallback of paid advertising if we must. All these methods form a common stream for lead scoring purposes. At this point, it’s good idea to tag our leads with the marketing method that produced them. Having loads of leads from Facebook is no use at all if they do not increase sales. After tagging, we can get down to analyzing where to start.
Six Types of iNBOUND iNTELLIGENCE Data to Consider
- Social media missionary behavior - clicks, likes and shares with friends
- Forms of website engagement, downloads accepted, CTA’s responded to
- Email responsiveness, percentage of emails opened, clicked, and responded
- Personal demographics of individual, and company decision-maker leads
- Company parameters: industry, geolocation, turnover, consumers targeted
- Signs of spammy behavior (sloppy spelling, incomplete form completion)
It’s a good idea to bounce these parameters off sales staff and trusted customers. They should know intuitively which parameters on your list matter most.
Next, Use the Benefits of Hindsight Metrics
Run your historic customer data through a cloud service provider like HubSpot to create an attribution report. Find out which marketing content historically produced the most leads that converted to sales. Are ebooks and white papers delivering more paying customers than social media? If social media are the winners, which is better: Instagram, Twitter, Facebook ... And what about emails, how do success rates compare across our product range?
Once we combine these two elements, we start to get a good feel for the information behind our sales. But, we have a mass of data, don’t we, after every inbound marketing campaign. Now’s the time for marketing to run the numbers so sales can get the orders nailed down. It is time to get help from our old friend HubSpot, that automates lead scoring methodology going forward.
Lead Scoring 104: Creating Lists with HubSpot
HubSpot allows us so to set thresholds for lead scoring criteria, so the most promising ones end up in the job jar. I like the tool because I can run as many reports as I like, as I come to understand it better, and produce data I can really use.
It’s as uncomplicated as following these three basic steps:
1. Go to Manual Lead Scoring
Set up the lead attributes you identified along the lines above. Decide whether they are a positive, or a negative attribute (e.g. social missionary versus spam). Then allocate the weight of influence you wish to each. Continue clicking away until you have completed your attribution set.
For example, we could rank social media sites based on experience. Or decide, for whatever reason, to assign more importance to SEO than paid advertising. What’s great about HubSpot is we can’t break it because it is on the cloud out of harm’s reach. And if we mess things up, we just start over.
2. Run a Test of Your Attributes
By now, you may be feeling the system is romping ahead of your ability. So it is time to catch up, and find out whether your choices deliver results. Go back to your historic metrics and pick a half-dozen leads that turned into customers. Make sure you have two good, two average, and two disappointing.
Now load these customers’ data into HubSpot. It will search your database for their attributes, load them up, and produce scoring reports. These will tell you how well you ranked them on the system. I hope they turn out accurate. If they don’t, as the woman on Skype says dolefully, “There is something wrong with your settings”.
3. Create a HubSpot Smart Lead Report
After hopefully killing the bugs / being content with what you have, ask HubSpot to bounce all your leads off your criteria. This amazing piece of software will filter in all your leads with a score equal to, or more than the score out of ten you chose.
If this produces a pile more than you can cope with, turn the number up. If your hurdle is too tough, lower it a little. As an example ‘out the air’ if I had a team of 10 sale staff and 1,000 qualified leads, I might want to turn the volume down a bit. So there you have it: A successful marketing campaign with qualified, scored leads ready to hand over to Sales.
Lead Scoring 105: Regression Analysis for the Mathematically Minded
My brain flipped when the editor ordered a para or two about this. I am seriously math-illiterate, although Google did tip me off that logistic regression predicts the probability of an event, such as a purchase of a product occurring. The input is a simple ‘yes or no’ for each attribute. Thus, this could complement HubSpot’s fuzzy logic if I could get it to work.
If this idea turns you on here’s a handy workbook that shows you how to get started with it on Excel. But be warned: the writer ends by saying “Logistic Regression is not the simplest type of analysis to understand or perform. Hopefully, this article and video have provided a much clearer picture for you”. This one needs a geek with a cap on back-to-front or tranquilizers.
Getting Back to Math Marketing for a Moment
Math marketing, which is where lead scoring methodology belongs, applies consumer metrics to identify the most positive leads. We can use the same marketing data science techniques to test our marketing personas in order to sharpen our focus. Politicians have used the approach to single out audiences most likely to support them. Sometimes it works, and sometimes it doesn’t. Take Bill and Hillary for example, or David Cameron’s Brexit bash for that matter.
What I Loaded in Your Job Jar Today
The internet has overall been good for business. Unfortunately, its universal appeal ensures that digital marketing trawls a mixed gill net of prospects. That said, new clients and markets can come from the most unlikely of places. So it pays to sift through them scientifically with the lead scoring process. School’s out. That’s the end of it for today.
If you want to learn more about Math Marketing and Inbound, we published a book on the topic. How about them apples?