Lead scoring has been around forever and mostly unchanged.
At Breadcrumbs, we have reimagined lead scoring and brought up to date with the current understanding of the customer journey and the importance of recency and frequency of behavior to the signal’s value.
But there is a whole other dimension that hasn’t evolved with lead scoring models: current solutions and most of the thinking around lead scoring centers around acquiring new customers.
Don’t get me wrong; lead scoring is ideally suited to sniffing out high-intent leads and getting those into the hands of salespeople while they are smoking hot. Especially if you can use recency and frequency variables to identify demand the moment it is present.
However, purchase intent is simply one outcome or objective that scoring models can help identify.
This article will discuss three more revenue-focused approaches to scoring at different customer life cycle stages:
- Expansion scoring models: up-sell & cross-sell
- Retention scoring models: using retention markers to accelerate revenue
- Adoption scoring models: using product usage data to create enhanced lead scores and prevent churn
Revenue-Focused Approaches To Lead Scoring
While it may sound like a basic concept, starting off with lead scoring models aimed at revenue expansion is a solid strategy for your first attempt at creating a model of your own.
There are 3 specific scoring models we’d like to bring to the forefront today – expansion scoring models, retention scoring models, and acquisition scoring models.
Expansion Scoring Models: Upsell/Cross-Sell
If you work within the eCommerce or sales sphere, the terms upsell and cross-sell might be very familiar to you. These terms relate to a very specific marketing strategy where you market add-ons (upsell) or related products (cross-sell) to those who have already purchased from you.
As consumers, we see examples of this in our everyday lives. Given Valentine’s day is coming up, our friends at 1-800 Flowers are using this fact to increase their own revenue with upselling.
After adding a flower arrangement to your cart, 1-800 Flowers automatically suggests several relevant add-ons to help make that special someone’s day even better. This is essentially the online equivalent of putting candy bars by the checkout counter.
Now, if we relate this to the topic at hand (lead scoring), we can use factors like upsell or cross-sell opportunities to create an enhanced lead score.
In this case, all of the data points necessary to identify customers with a propensity to upgrade or add on complementary products or services should exist within your existing database. It should be more true for expansion and retention as it implicitly requires an existing customer base.
A co-dynamic approach, fit and activity, will work just as well in this scenario.
Your current customers have likely provided you with rich data from a demographic/firmographic perspective. You can map this against customers who are already using the product mix or tier you are trying to sell.
If it’s a new offering, you will use the Ideal Customer Profile (ICP) that informed your new offering.
The approach to your model’s activity component will somewhat depart from how we typically think of activity when building acquisition models.
Although engagement with marketing may still play a part, think of a web visit to the product page for the thing you are trying to sell. A larger part can and likely should be a combination of product usage and third-party intent data.
As an example, let’s say you are a SaaS billing platform that offers Tax Compliance features at your highest plan tier.
Let’s say you have a user that has recently visited a blog post titled “Is SaaS taxable in California”, their install base is growing across many tax jurisdictions, as demonstrated by your product data, and they have been on G2 crowd-researching Avalara (an automated tax compliance software).
These activities indicate a likelihood of buying a Tax Compliance offering and should be a part of your expansion model.
Retention Scoring Models
There’s an old advertising saying that should be top of mind for every company – “It’s easier to keep a customer than gain a new one.”
This has never been more true than now. In fact, over $62 billion is lost annually due to poor customer service. Retention can also impact the upselling and cross-selling abilities of your org, as you only have around a 5-20% chance of closing a deal.
It’s safe to say that it’s in your company’s (and sales team’s) best interest to measure your retention and churn rates as a part of your standard KPIs.
When it comes to retention in lead scoring models, it’s almost a reverse approach to building an acquisition model. Your analysis baseline in terms of fit and activity criteria are all of your previously churned customers.
Although fit will likely play a role here and is probably a function of customers who have a lower fit grade in your acquisition model. Activity will most certainly be a more significant part of the equation.
Again, engagement with your brand more broadly may still contribute to your score, a visit to your FAQ on how to cancel an account, for example.
For most businesses, the actual offering’s usage or engagement will often be a more robust indicator of the likelihood to churn. It could be the frequency of skipped deliveries at a subscription box business or at a typical SaaS business; it might be decreased logins.
The critical consideration here is that unlike in acquisition models where we are looking for more recent and frequent activity, in most cases, it’s a decrease in recency and frequency that will provide the churn signal.
Adoption Scoring Models
Product and service adoption is another huge KPI your team should be tracking. Overall, adoption metrics will show you how much of your product is being used (or underused) as well as help you identify the key actions that define success for your customers.
As MixPanel states, any business that benefits from repeat customers is a company that benefits from higher user adoption. For example, high adoption makes:
- SaaS buying committees or decision-makers more likely to renew
- Financial services users more likely to stick with an app
- Consumer tech users more likely to form habits around an app
- Media and entertainment readers more likely to visit the site repeatedly
- Retail and e-commerce shoppers more likely to place repeat purchases
- Telecommunications consumers less likely to churn
While the adoption scoring model is a bit more difficult to conceptualize and create, it’s also a fun use case for scoring models. It’s essentially a hybrid of an acquisition and expansion model.
In this case, instead of creating a scoring model based off of things like purchase intent, we score our customer personas by their product or service usage.
Typically to use this sort of model, the product team needs to have gone through the product development process and identified personas, pain points, use cases, and validated them with customer interviews and other research.
Essentially, you want to ensure you have correctly identified the specific features that customers use to find your product or service successful – and have data-backed information to verify.
Leveraging all of this great work, we lean on our trusted co-dynamic methodology to build fit criteria based on the personas of our top customers. For activity criteria, we would focus on a combination of broader digital engagement and product usage to predict the likelihood of a prospect/customer using a particular feature.
The big difference with adoption models is that they are typically not focused on a monetary transaction. This doesn’t mean that the model is useless – far from it. However, it does mean that the previous 2 models could be easier to prove the effectiveness of modeling in general to your team before diving in further.
Although there is still an exchange of value, as there should always be, it’s more about delivering on the promise that earned you the business in the first place. Ideally, the outcome for this scoring model is an increase in Life Time Value (LTV).
And as we mentioned before, better retention helps revenue in all aspects.
Final Thoughts: Acquisition Is Just One Objective
As I mentioned earlier, acquisition models are the bread and butter of lead scoring. In fact, it is the underlying assumption that informs most native lead scoring features and what people traditionally think of when they think of the term.
However, lead scoring at its core is simply about identifying individuals/entities most likely to take an action we define as important.
Of course it’s up to us to be able to correctly define the actions that lead to revenue acceleration and customer happiness.
That means as long as you can clearly articulate your objective, the thing you want to happen (or not in the case of churn), and have the data points to inform the scoring models, the possibilities are endless.