We are in the middle of a marketing revolution. With technology that makes it possible to get insight from all different types of data, it’s no longer about being just a modern marketer -- it’s about being a predictive marketer.
As marketers, we can put data science to work to better predict which prospects and customers are most likely to buy, and when, to target the best prospects with powerful, personalized messages.
But not all data is created equal.
The Trifecta of Lead Prioritization
It’s critical to look at a combination of various types of data, and view their signals as different pieces of the prospecting and customer experience puzzle. Three types of data comprise the trifecta of lead prioritization:
- Behavior: Data collected on how prospects have engaged with your brand. Think: emails opened, research reports downloaded, content viewed.
- Fit: Demographic data collected about prospects. Think: company size, growth, credit score, industry classification.
- Intent: Data collected on prospects long before they engaged with your brand. Think: keywords searched, sites visited, blogs read, ads viewed.
Capitalizing on the insights provided by behavior and fit data is not new to marketing. What really separates the masters from the novices, the elite from the average, is mining intent data from across the Web -- the data collected before a prospect engages with a brand.
Google is the king of intent data. Text ads fund its core search engine, running alongside search results. For example, if you search “cloud storage,” ads for Dropbox and ShareFile appear. These ads are effective because they leverage the intent of the searcher in real time, and can be fed into predictive models at a later date.
An Earlier Look at Your Customers
The most successful predictive marketers operate in real time by identifying initial interest expressed through search engines, social media platforms, blogs and online forums.
Intent data allows marketing teams to do a few things:
Identify Buyers Before They Find You
Marketers are good at using fit and behavioral data to score people who have already interacted with their brand. With intent data, however, you proactively identify new buyers at the very beginning of the buying cycle -- before they visit your website or become a lead.
Revive 'Zombie' Accounts
It’s not as scary as it sounds! The reality is that many people in your database have never opened an email from you or visited your website. However, that doesn’t mean these people aren’t doing research, or that you can’t incorporate information about them into a lead score. Intent data will give you the insights you need to know if a “zombie” account may be ready to purchase.
Improve Your Nurturing Programs
Intent data equips marketing teams with the tools they need to tailor and customize campaigns. For example, email subject lines can be created from individual search terms to improve open rates.
Accurately Steer Retargeting Campaigns
Retargeting efforts are catalyzed when a person views your website. The problem is that many non-buyers visit your site. With intent data, you can save time by eliminating people that do not display the browsing patterns that indicate they may be interested in buying.
While intent data are tremendously useful, remember that fit and behavioral data provide integral insights that should be combined with intent data to provide the most accurate lead identification and scoring.
Intent data simply cannot capture all the necessary insights on its own. Take two people researching “wireless headsets.” The search alone may indicate that both people are interested in purchasing. However, a closer look with fit and behavior data may show that one person is a young girl interested in purchasing an accessory for her Beyoncé Halloween costume, while the other is an IT professional working at a quickly expanding company.
We are fortunate to no longer live in a world of data scarcity. Today, marketers face the opposite challenge: data overabundance. Predictive marketers gather all of the data available to them, in order to look at the big picture. Understanding the types of data available and how the different insights work together is proven to drive sales, increase revenue and propel growth.