It’s no secret that Marketing Automation has become a necessity and a powerful tool for modern marketers.
If set up correctly, you can gain valuable insights into the digital body language of your prospects, develop rich personas, tailor meaningful conversations and send better quality leads to your sales team.
The end result is more meaningful conversations, higher conversion rates and more closed deals! Not to mention, your marketing and sales folks will see sparkles when they gaze into each other’s eyes.
Sounds pretty good right? The reality though is that most companies haven’t found a way to leverage the capabilities of their marketing automation platform to its full potential. And with the sheer size of marketing automation platforms, marketers are always on the hunt for tips, tricks and shortcuts that might help make their lives just a little bit easier.
Today, I will talk about some of the common marketing challenges, shed some light on best practices and share some of my secret hacks to help you optimize your marketing automation efforts.
It all starts with your data
Most marketers are so focused on developing marketing campaigns and creating content that it becomes very easy to lose sight of the foundation of any marketing strategy – the data.
If you find yourself suffering from low engagement rates, you need to start by looking at your data. After all, what good is a campaign without an audience?
Without clean data, it becomes a daunting task for a marketer to segment their audiences into personas, score their leads, and develop effective personalized content. Not to mention, if there are no governance and business rules around capturing and standardizing data, you run the risk of further polluting your database with dirty data which will negatively impact your campaigns in the long run.
The most common example of this practice is uploading cold lists into your database that have not been vetted or looked at for quality.
My Advice: Ditch the data dump methodology and stop uploading cold lists. Yes, I can see you from here—don’t do it, don’t upload that list! Instead, develop a process and structure to capture data and keep your data clean.
Here’s a few things you might want to consider:
- Integrate relevant systems.
- Standardize your data.
- Develop business rules, logic and governance around data collection.
- Minimize requested information through progressive profiling.
- Append data from existing systems.
- Extract data from existing fields.
- Maintain a data cleanse process regularly.
Hacks: You may also want to consider leveraging features like lookup tables as a way to transform fields such as job title into roles, for instance, so you can view the data you actually require. In addition, implementing a contact washing machine as a best practice can help normalize data and maintain a clean contact database.
Lead scoring isn’t a magical system
Lead scoring isn't a magical system that will tell you if a prospect will turn into a customer. It’s to help you identify leads that are sales-ready, leads that match the ideal profile of someone you actually want to talk too.
Most marketers make the error of rating and building lead scoring systems without having spoken to Sales or getting any kind of alignment. The result is Sales and Marketing debating endlessly over the quality of leads. Defining the criteria to identify an ideal prospect and assigning weights to help profile leads is one part of the challenge. The other side is how to capture that data, test the lead scoring model and refine it based on feedback.
My Advice: There are two components to this process.
- The first part of this exercise is to develop a series of interviews/workshops with Sales to identify a common set of traits and attributes that marketing would want to collect to help profile a sales-ready lead. This is the alignment piece of the puzzle.
- The second component that most marketers forget about is looking at closed opportunity data of won accounts and existing customers to identify common traits and engagement attributes of successful opportunities. This is the predictive modeling part of the puzzle.
This two-pronged approach helps ensure that Marketing has correctly identified the solid profile of a sales-ready lead by looking at both the firmographic and behavioral attributes that make up a qualified lead from both a qualitative and quantitative lens.
Hacks: You may also want to consider leveraging features like page tags to help group and organize engagement activity for lead scoring and lead nurturing. In addition, you will also want to leverage the CRM reporting framework to gauge the performance of your MQLs and SQLs, which will allow you to determine how effectively your lead scoring model is working so you can gather feedback to make the appropriate changes with every iteration.