Work Smarter, Not Harder: Why Your Lead Scoring Is Holding You Back
TL;DR Lead scoring is foundational to any personalized marketing program but often falls short due to data challenges. It is also time-consuming, costly, and inflexible to the changing needs of your business. Learn how to implement lead scoring and gain sales adoption in just a few weeks, rather than months.
Lead scoring & Marketing Automation Platforms (MAPs)
Lead scoring, often accomplished with a MAP, is meant to provide a foundation for marketers like you to deliver personalized buying experiences. As a way to prioritize leads for sales teams, enable reps to send more personalized outreach, and fuel segmentation for marketing campaigns, MAPs assign a letter or number value to each lead through a point-based scoring system. And while MAPs promise this automation as a way to drive personalization at scale, it is difficult to achieve due to messy data that is not easily usable.
Why is lead scoring so challenging?
Lead scoring can be a headache and ultimately make your life as a MOps pro more difficult because it is:
- Time-consuming and costly to implement: To develop a scoring model you and your team likely painstakingly implemented scores over the course of 3-6 months (or in some cases, even longer). Lead scoring tools in MAPs are designed to be static and linear, expecting you to know how much an ebook download should be worth or the value of a specific website page visit. While internal teams may have a good feel for which activities and traits should be valued more than others, there are often rooted in opinions, not facts. Without understanding historical conversion data, it is nearly impossible to get an accurate picture of what should hold the most value, and ultimately where sales should spend their time. It’s not uncommon to spend countless hours and maybe even tens of thousands of dollars working with an agency to implement a scoring system.
- Difficult to maintain: Since businesses are changing constantly, by the time scoring is implemented, it’s likely already due for a refresh. And, once scores are set it takes months or longer depending on the sales cycle of your organization to determine what’s working and what isn’t, making it more obsolete each day.
- Inflexible: Typically scoring models don’t consider the complexities and nuances of the business (different geographies, segments, offerings, and so much more). For example, if you serve multiple geographies, there may be different target industries, company sizes, etc. within each geography. MAP lead scoring rules don’t allow for an easy way to layer in these intricacies and prioritize leads accordingly. This means as a marketing operations professional you are stuck trying to hack together automation rules and workflows to meet the needs of different internal stakeholders and teams.
Gain time back & deliver better results
At MadKudu we enable you to do your job faster and more efficiently.
We help connect disparate data systems, stitch together critical demographic and behavioral data from a wide variety of data points, and provide lead and account scores rooted in historical conversion data.
With MadKudu you can be up and running with intelligent and predictive scoring in a month or less. Your predictive model generates scores so you don’t have to, saving you critical time in your day. However, you have full access to MadKudu’s data science studio allowing you as the marketing ops pro to own as much of the process as you want.
And, you can adapt quickly to your business needs as they change. If you enter a new market or start offering a free trial, for example, you can incorporate those changes into your scoring. With data-backed scores, you’ll be armed with critical insights that will allow you to easily optimize and iterate on programs. And, your sales and marketing teams will be effective in delivering more relevant customer experiences to the customers who matter most.
You shouldn’t have to spend countless hours building, explaining, and instrumenting a scoring system that can become obsolete as the business changes and determining the efficacy of your scoring shouldn’t be difficult. As a marketing ops professional, your time is valuable and should be spent getting to the core business use case — how do we use data to surface insights, iterate, and improve on personalizing the customer journey?