According to a GEM (Global Entrepreneurship Monitor) report, 3 startups are created every second. So, while you were asleep at least 0.8 million startups were created! Or shall we say, 0.8 million leads came up from nowhere? Even if 0.1% of these were relevant to your business, you still have approximately 860 leads to contact, assuming you sleep 8 hours a day. Leaving the numbers behind, the most important problem that businesses are and have been facing is the lack of ability to differentiate between high and low-quality leads because the speed at which market is growing is rapid.So, companies started to come up with their own strategies to handle this problem and the one solution that really emerged was the concept of lead scoring.
What is Lead Scoring?
Lead scoring is a methodology to rank your leads on the basis of their probability to convert into a customer. Inbound Mantra has been one of the first in the HubSpot Partner community to offer Lead Scoring (Manual, Predictive and Blended) to its clients. In simpler words, we give a score to every action that a lead performs on our website, app or elsewhere and use it to prioritize our leads. For e.g: If maximum score a lead can get is 1 and 90% of our customers are from the U.S., then we can
- Give 0.3 score for spending more than 10 minutes on our platform.
- Give 0.5 score if the lead filled the contact us form.
- Give 0 score if the lead is from Russia (because 90% of our customers are from the U.S.).
This is what we call rule-based lead scoring and one could develop different scoring strategies that were relevant to their businesses and prioritize their leads accordingly. What do you think? How beneficial will this approach be for your business? Well, in the longer run, not much.
- Rules are not granular enough.
- It can take months to get your rules right.
- Rules can be based on gut-feel, ignoring the actual pattern.
- Rules do not consider lurking variables (hidden features that affect the data).
- How many rules can you actually define?
So, these are some of the reasons rule-based lead scoring is becoming a concept of the past. With these shortcomings, businesses are now moving towards what is called Predictive Lead Scoring.
What is Predictive Lead Scoring?
The obvious question that arises here is, how is lead scoring predictive when we know what to track and how to score? Yes, we still track a certain set of activities that lead performs but we do not score them now, in fact we let the machine identify the most important attributes or behaviors of an incoming lead. The algorithm will not only identify important features but will also give us the freedom to add in more features.
- With rule-based scoring, you could define only a certain set of features, but with predictive scoring the algorithm is open to any number of features as long as the data quality is good enough. (Features are lead's activity and characteristic data, like lead source, session time, no. of clicks, forms filled etc.)
How does it know which features are important
Well, that's Machine Learning! We feed it historical data, this data would contain all the actions or behaviors taken by a lead at any point of time. Now, since we know which lead remained a lead and which converted into a customer, we'll add this information into our data-set. The algorithms will then do their part by identifying and looking for various patterns in the data and filter down the most influencing features. Now that you've understood what is predictive lead scoring and how it can provide better flexibility in detecting patterns, let's have a look at some of the companies that provide predictive scoring tools.
Predictive Lead Scoring Companies
Madkudu offers 2 products at the moment, Lead Scoring and Smart Forms. Lead scoring works by identifying the lead behavior on your platform and in addition to it, demographic data is also captured. I'm not sure how demographic data will be applicable unless they compare it with some previous data points, which they haven't mentioned anywhere on their website, the same applies for the firmographic data, there's no explanation as to how they judge what a good number for company size is or how it gives importance to certain locations or anything, with all this incomplete information, think twice before pursuing it.
On the other hand, they also offer smart forms, they are basically linked to various 3rd party sources which enriches the incoming lead data with some extra metrics and it instantly qualifies or drops them from the marketing funnel. The platform is only limited to lead prioritization and enrichment, there's no sign of pre-built email templates or engagement strategy for leads. It could be a good tool to start with if you're a new brand and do not require a detailed flow of your lead's journey.
Datafinder also does everything that any product listed on this page can do. They don't provide anything unique in their product suite. I've requested them for a demo walk-through but haven't received any response till date. The pricing model's flexibility is the only unique thing I could find out for this platform, which is based only on the number of records processed. You can customize everything to anything, like number of records, type of data to track, number of attributes to track, API calls, amount of data required to enrich your leads and so on.
Conversica is more focused towards how you engage with your leads and guides you through each stage of the lead's status. So basically, it provides an AI-powered sales assistant which can automatically schedule calls for your leads, sending automated emails, pre-qualify your leads like any other marketing software. I doubt it provides any kind of predictive lead scoring, although it can tell which leads to call or do some call prioritization but it doesn't track any kind of lead journey or assess leads or give behavioral scoring. If you want to improve your sales set-up, make it more organized than you may want to give it a try but I don't expect anything other than this from Conversica, especially in case of lead scoring, enrichment or behavioral scoring.
With it's easy and quick deployment setup, Saleswings has an easy-to-use dashboard which scores each of your leads right in front of you based upon your lead's activity, helps you track them, enriches your leads and finally qualifies them. I would recommend this only if you do not want to go in detail regarding lead scoring or how a lead is interacting with your platform and just want a tool to quickly tell you if a lead is worth pursuing. It can essentially tell you what all pages the lead visited, gather insights about the company and tell if the lead is warm or hot.
I'd say it's a good tool to start with as you'll understand how a lead behaves on your website. This is the only platform that was quick to get back to me and schedule a demo to walk through of their platform.
6Sense is a detailed and a heavy AI platform for marketing automation and one of the best tools you could use to understand the buyer journey, not only this, behavioral scoring, campaign analysis and tracking leads right from their first visit to demo requests are some of the features that are nurtured through it's AI. With its heavy focus on account-based buyer journey, which of course is an important part of predictive modeling, it makes its way to No. 4. You got to appreciate the way they track the leads right from any kind of third-party source to your platform, their patented sentimental AI reconstructs the journey once it has collected all those signals. Before you get on board with them, make sure you have enough, good quality data because there doesn't seem to much scope of lead enrichment or nurturing on this platform.
Radius is yet another feature packed platform, it provides all essential tools needed to clean and prepare your data, lead scoring, account-based marketing and qualifying your leads.
It answers the following questions for you:
1. How to clean your data?
- Are the records duplicate?
- How to complete a lead profile?
2. Who is my customer?
- Maps your data and it's own pre-recorded data points to find the optimal market segment where your customer belongs.
3. Who should be in your ABM list?
4. Which lead to prioritize first?
One of the unique features it provides is "Co-Marketing", where it allows you to view opportunities from partner brands to expand your circle and hence attract more leads and can also guide you how to engage with the lead at its different stages in the funnel.
Infer is a predictive-first platform, in addition to its predictive scoring it also provides behavior scoring for its leads. Although, not much is available about what and which features they provide, how does it work or anything; they do have a very interactive interface for their actual product, as seen in one of the testimonials given by a client. Their deployment process lasts only for a few minutes and then your company is all set to go. Infer also seems to have a good hand in tracking things. It can track signals for your leads, in fact it seems to have a big bucket of signals that are essential for lead's tracking and the ones that can contribute to lead conversion. One of the unique things of infer is, their product is somehow bent to work for their every client individually and doesn't seem to follow any general approach or a centralized system to score and track leads.I would say it's a tough competitor on the sales front.
One of the leading predictive scoring platforms in the B2B marketplace, Mintigo provides various features from lead discovery, decision maker identification to predictive lead scoring. I would rate it as my first preference as it provides one of the most basic needs of a data-centric company i.e. data cleaning and preparing, although not the only reason. The way they have defined and constructed the product, essentially covers all the pain points one could encounter. Their algorithms, as they define it also allows you to complete your data (enrich your leads) which not only is a good thing for the predictive model but also the fact, that you'd learn way more about your leads than you ever did. The machine learning models are pre-built, so you won't be able to change much about the algorithm or maybe tune it according to your data but because it has been in the field for so long, it has learned most of the key indicators for differentiating between a lead and a customer. So, I think it's a good to go platform for almost any kind of company. Finally, I'd just like to say that there are a decent number of tools out there that can get your job done. What I've seen is there's a big gap between what some of these companies state and what they actually deliver. So, I'd recommend you to make a list of problems your company is facing, pick a couple of tools from the list above that are relevant and make a decision based upon your budget, and you'd do just fine!
HAPPY LEAD SCORING!