Turning data into profit
Turning data into profit
See how probability-weighted sales forecasts, market segmentation, and new lead scoring models helped a growing B2B company sharpen strategy and target their most profitable markets.
Learn how machine learning and survival analysis helped a B2B services firm predict which leads would close — and how fast — to prioritize sales efforts with confidence.
Ready to unlock the power of your data? Let’s get started — it only takes 2…
Uncover hidden trends and improve outcomes with data analytics. This real-world case study shows how logistic regression and predictive modeling reveal what drives success—insights every business owner can use to boost retention, performance, and equity.
High-growth businesses prioritize understanding their most valuable clients. By identifying metrics like revenue and purchase frequency, you can refine your Ideal Customer Profile. Engaging directly with these clients unveils insights that can enhance your marketing strategies, paving the way for attracting similar customers.
A fast-growing B2B firm uncovered hidden sales opportunities and high-converting contacts by analyzing regional trends and decision-maker behavior. This case study shows how data-driven insights powered smarter investments, faster closes, and a clearer path to growth.
Even if you’re not a data or a numbers person, there’s a lot you can learn using simple tools and spending just a little time investigating the information you already have. So where do you even begin? Read on for starting points.
This checklist is designed specifically for B2B businesses offering professional services that want to leverage data to fuel growth.
It outlines a simple, step-by-step approach to establishing a data-driven culture within your organization — from setting clear objectives to scaling your practices as you grow.
In today’s business landscape, data has become one of the most valuable resources a company can have – especially for small and medium-sized businesses (SMBs). In 2006 British mathematician Clive Humby remarked that "data is the new oil": like crude oil, raw data on its own isn’t very useful, but when refined (analyzed and processed), it becomes incredibly powerful.
