The Problem with Traditional Lead Scoring

By September 11, 2015
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A decade ago, marketing automation made a big splash in the B2B space as a streamlined way to engage with prospective customers. The technology enabled marketers to have all their relevant data in one place, to measure ROI, campaign effectiveness, and of course, the number of MQLs that converted into opportunities. It changed the role of the modern marketer.

Marketing automation and scoring

One of the more recent advances in marketing automation is an ability to score leads based on a defined methodology set by sales and marketing. Scoring prioritizes leads based on who is most likely to close, but is mostly a subjective process typically defined by gut feel and a subset of data .

What if your lead score could be more than an educated guess? What if you combined ALL of the data you have gleaned about your best customers across your CRM and you marketing automation system and used that model to score your leads? Think—something more accurate than just an educated guess.

It is time to re-evaluate traditional lead scoring and look for a new way to think about one of your most valued assets, your data.

Problems with the traditional lead score:

  1. Lacks precision: Traditional lead scores are mostly based on intuition. Marketers segment on 10-15 signals like title and industry, but lack visibility into thousands of other possible signals that could be very important. Even when using behavioral attributes in your scoring, you aren’t taking into consideration insight into customers who have closed and other signals around the web.
  2. Inflexible: Today’s systems do not adapt to changing requirements or market conditions. Not to mention that many traditional lead scores are often left the same for long periods of time.
  3. Doesn’t scale: Rules-based systems cannot meet the needs of large or diverse organizations. Different geographies, verticals, and product lines may require different scores. You also need to manually change these scores as you go. It’s just too complex!

Predictive scoring: how it works

Predictive scoring takes into consideration the historical profiles of your best customers and applies that data to customers already in your database. Therefore, you gain insight into which leads have the highest probability of closing. You can then use this score to be more efficient in your interactions.

EverString collects petabytes of data about 11+ million companies. This categorizes companies not just on variables like revenue and employee size, but also on characteristics like social presence, technology adoption, and management team DNA. In all we track over 20,000 signals per account.

By marrying your historical CRM and marketing automation data with external data using applied data science, a Predictive Score is created.

An account fit score helps identify how likely a specific account is to adopt your product or service, while the engagement score determines a prospect’s buying intent.

Applying data science across your entire funnel

Predictive marketing has the ability to scale up, as multiple models can be built to address focus on different verticals or company sizes. Models are retrained to constantly understand how your business has changed over the past quarter or month—so these models change as your business changes. This is a sharp contrast to traditional scoring, which has to be manually changed and updated by the marketer.

Unseen benefits of leveraging predictive: happy salespeople

The beauty of predictive marketing is that it doesn’t require an extra resource to manage the technology. This system of intelligence runs in the background to make sense of the data in your internal systems of record, like Salesforce and Marketo.

To take it a step further, it has the potential to solve issues of sales and marketing alignment.

It’s the age-old problem of sales asking for more leads, but the leads that marketing delivers have low fit and engagement. Giving your sales team leads that are categorized based on your data model enables your sales teams to spend time on the hottest leads.

Want to learn more about predictive marketing? Download our new cheatsheet now!

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