Don’t rely on guesswork. Know who your buyers will be.
As B2B marketers, we all know that having a lead scoring system to identify sales-ready leads or potential buyers is critical to running successful demand generation programs and to maintaining marketing-and-sales alignment. But implementing a lead scoring system that actually works is easier said than done. With Mintigo, you can now have lead scoring models that leverage the power of predictive analytics and big data to help you find your buyers faster. No more guessing.
How It Works
1. We start with what you know
Leveraging your CRM and marketing automation data
You probably know some things about your leads: Which campaigns they’ve seen, where they clicked and what they filled on your form. We leverage this valuable data to start building your predictive model.
2. We add what we know
Adding thousands of online marketing indicators
Mintigo collects and continuously updates thousands of data points on millions of companies. This information includes public information on financials, staff, hiring, technologies, marketing and sales tactics as well as semantic analysis of the company’s digital footprint. The result – a 360-degree profile of each lead in your database.
3. We apply predictive analytics
Crunching massive data with machine learning to crack the CustomerDNA™
Mintigo takes your data, our own data, and your highest value leads and uses machine learning to find your CustomerDNA™, the set of indicators that make them unique compared to all of the other leads in your database. The result is a set of indicators and a scoring model that can predict the likelihood to convert.
4. We score your leads database
Identifying your most valuable leads
Mintigo uses your unique predictive scoring model to score your existing leads and every lead that enters your funnel in your Marketing and Sales systems such as Eloqua, Marketo and Salesforce.com. This has direct impact on your revenue—Now you know which leads to send directly to Sales and which ones to keep nurturing.