What is data-driven marketing?
Data-driven marketing is all about analyzing big data to understand and predict customer behavior, then translating that insight into a targeted marketing strategy to lead the way forward.
Good data-driven marketers don’t assume they know best about their audience. Instead, they are continually mining customer data—whether company-generated or sourced externally—to revise and refine their understanding of who their target accounts are, where they are, what they’re looking for, and what will motivate them to make a purchase.
These marketers aren’t simply making assumptions about what worked in the past; they’re using measurable insights gleaned from market-wide metrics and individual customer interactions to look into the future and make informed predictions about their customers.
This data-driven approach makes it possible to build highly segmented marketing campaigns that put the right creative into the right channels at just the right time. The result is a more personalized and relevant experience for the customer, leading to more conversions, greater brand awareness, and ultimately a higher ROI for the marketer.
Benefits of data-driven marketing
Data-driven marketing signals the end of the old “spray and pray” approach to customer engagement. Instead of delivering a general message to a large, unfiltered audience and hoping for results, data-driven marketers are turning to big data to help them understand who their target accounts are, what makes those accounts special, and how to reach those accounts in a highly personalized and targeted way. It’s about quality, not quantity. Done well, data-driven marketing means less time spent prospecting and more time converting high-quality leads into highly loyal customers.
Those are the broad benefits of a data-driven marketing approach. More specifically, this approach can help you to:
1. Automate your research and prospecting, freeing more time for high-value work.
Now that data-driven marketing has established itself as a must-have dimension of a modern marketing strategy, the tech market has responded by offering automation platforms designed to do at least some of the heavy lifting.
Only a few of these solutions are reliably smart, insightful and accurate; the best of them harnesses the power of AI and machine learning to constantly discover, profile and monitor customer data in a “living” database that integrates with existing point solutions.
As a result, processes that were once imperfect and time-consuming (like manual prospecting) are now managed by intelligent systems drawing from millions of data points, freeing the human workforce to focus on activities that nurture and convert customers.
2. Focus on the highest quality accounts, reducing wasted effort and heightening ROI.
Using fit data, data-driven marketers can identify accounts with a high suitability for their product or service. Fit data reveals which prospects are likeliest to convert based on what worked in the past, helping marketers eliminate companies that are unlikely to purchase and, instead, target their marketing strategy on companies who fit the profile of an ideal customer.
Fit data is good, but it’s even better when layered with intent data and recency data. Intent data indicates which prospects are showing buying behavior, while recency data tells you when that behavior took place. For example, you might learn that a prospect has been reading reviews related to your product; knowing that they did this research yesterday can help you prioritize your efforts and get in front of prospects before the competition does.
Layering engagement data into this scenario is will further refine your target list; engagement data reveals when and in what ways a prospect has already interacted with your brand, giving you the opportunity to reach out with a meaningful and contextualized message.
3. Personalize your marketing.
Layering fit, intent, recency and engagement data to understand your target accounts provides highly nuanced insights that you can parlay into personalized messaging.
As everyday technology gets better at anticipating and meeting individual consumers’ needs (think of the Netflix recommendation engine), consumers are learning to expect a highly personal experience whenever they interact with a brand. By translating customer data into a targeted marketing campaign with personalized messaging, you can take advantage of this expectation and create interactions that feel “sticky” for customers, capturing their attention with relevant and timely brand messaging. The result is a higher likelihood of conversion, and greater customer loyalty over time.
An example of data-driven marketing
Examples of companies that have applied data-driven marketing to dramatically increase their conversion rates abound, from high-growth SaaS brands that rely on customer data to refine and personalize their sign-up process to big B2B brands using data to build highly targeted email nurture campaigns.
Using customer data pulled from their own CRM, they generated a fit model to help them identify prospects that shared several characteristics with their most advanced opportunities. They used data-driven AI to surface high-fit accounts currently surging on intent topics related to their business, then developed a finely segmented marketing campaign to reach those accounts at the right time, in the right way.
As a result of their data-driven insights and a validated marketing strategy based on fit and intent scores, Terminus increased their win rate after a first product demo by 125%. That’s because they were targeting accounts who were a good fit for their offering and were demonstrating a recent intent to purchase a product like theirs.
How could they know all of this? Simple—it was in the data. All they needed was the right technology partner to help them surface those measurable insights.
“We overlay engagement and intent data to get a clear vision of the buying propensity of our target accounts. Then we trigger unique campaigns based on the level of engagement the target accounts show. By focusing on progressing accounts to the point where the buying committee is showing a meaningful increase in engagement, we create more opportunities and close those opportunities faster.”
—Torrey Dye, Director of Account-Based Marketing, Terminus
EverString and sales insights
The most essential element in any data-driven marketing strategy is right there in its name: data.
But simply having data—whether purchased from a third-party vendor or generated internally—isn’t enough. Data quality is critical. At best, low-quality data could result in the wasted effort of trying to reach customers who just aren’t listening; at worst, it could result in embarrassment, mistrust and lost opportunities.
In short: the better the data, the crisper and more profitable the marketing strategy. That’s where EverString comes in.
EverString operates an AI system with the processing power of 1 million people.
By harnessing the capabilities of machine learning and AI, we offer customers the world’s most reliable high-quality, high-coverage customer data. Unlike third-party data vendors who struggle to keep inert and error-prone databases up to date using a human workforce, we use an AI system that exponentially outpaces what people alone could do. The system is constantly teaching itself; the more data it ingests, the smarter it gets.
A unified view of actionable data-driven insights directly within your CRM
We operationalize all of that data using a methodology called FIRE, which pulls together fit, intent, recency and engagement data to surface the most qualified accounts for our customers in an easy-to-use and well-integrated dashboard. Users of our platform can access FIRE scores from directly within their existing point solutions, helping them to focus their marketing strategies on qualified leads.
Ready to see how EverString’s AI system powers data-driven marketing strategies with the world’s most reliable customer data? Contact us for a free demo.