Modern marketers are inundated with content about marketing automation tools that can help them generate pipeline and increase revenue. Now that Marketo, Hubspot, Eloqua, and many other platforms have become mainstream, what’s next? What can marketers do with all these federated tools to generate new customers?
I’ve found that the best marketers measure success based on the dollar value of pipeline they’re able to generate. We build tools for marketers, and when I talk to prospective customers, marketing influencers, and potential job candidates, I always ask how they measure success. The marketers that struggle the most typically answer, “I measure my success based on lead volume.” The marketers that surpass their goals typically answer, “I measure my team’s success based on dollar value of pipeline.” Marketers that struggle to reach their goals aren’t cognizant of their sales team’s ability to close deals; marketers that excel at reaching their goals work closely with sales to find great customers the team can close. Our VP of Sales, Greg Fiorindo, focuses a lot of his time on qualification: “It’s all about whether a prospect is qualified or not. At
To prioritize pipeline to find great customers, marketers need a deep understanding of how to market to the right customers. Ten years ago, lead volume was the only reasonable metric available to measure marketing success. Today, marketers have access to new data sources, superior analytics, and better integrations that allow them to generate high value pipelines.
At Radius, we call this process Marketing Intelligence. Today, we’ve released an extensive guide showcasing how to make your marketing process intelligent. For marketing teams that employ the process articulated in the guide, we believe success measurement can transition from lead volume rate to pipeline generation. The transition starts with understanding two key changes in the marketing ecosystem: (1) The explosion of data and (2) The inadequacy of disparate tools.
1. The Explosion of Data
A wealth of insights is available to B2B marketers if they are willing to dig in. Internet exploration, search, smart device usage, content browsing, and business community social activity reveals the twists and turns customers take throughout their lifetime. Making sense of big data is a challenge not only because of its magnitude, but also because of its complexity. The value of big data doesn’t stem from the volume of data you aggregate, but rather, from the relationships between the data. To extract insights from sets of data, data scientists have to take the volume, velocity, variety, and veracity of data into account; they don’t just experiment on data, they merge, organize, clean, and test data as well.
This level of analysis is tough for most marketing organizations to conduct. Most marketing organizations buy several different tools to try and employ these tactics. One tool might include Predictive Lead Scoring and another might be hiring a team of analysts that require extensive training.
2. Ineffective, Disparate Tools
Both data scientists and marketers categorize data in two large buckets: internal and external. Internal data includes attributes on leads, accounts, and activities collected by web forms, uploaded in static lists, or input by sales reps and stored in CRMs and marketing automation systems. External data includes additional signals about prospects, such as revenues, headcount, online advertising activity, social media presence, web technologies, and more. According to
For marketers to use data and analytics at all of these levels within the pipeline isn’t easy and typically leads to a ton of tools that solve the problem half-way. What is your organization doing to embrace data and simplify your process?
