Analytics seems to have a different meaning depending on person, place, and context. That’s not necessarily a bad thing. Having multiple viewpoints lets us develop a bigger picture, and it opens our minds to new possibilities and paradigms. At the same time, it’s easy to get stuck in “analysis paralysis.” We end up unsure of where to begin, what to measure, and how to monitor. Which metrics matter most? What information will be most beneficial for our teams and our organization? How do we harness this information to make advancements with our marketing efforts?
These are hard questions that can be daunting, and often, they stop us from making real progress. With that in mind, I’d like to offer you a simplified approach for considering the metrics and analysis that’s best for your business. Ultimately, you’ll want to utilize all three types of analytics, but everyone needs to start somewhere. Whether you are just beginning your analytics journey, or you are somewhere in the middle, you may benefit from considering these three focal areas and why they are important.
Engagement-driven metrics are where most people start their analytics journey. These metrics tell you how customers are interacting with your marketing efforts. They will give you a sense of how specific campaigns, emails, nurtures, ads, and other online and social efforts are performing relative to each other and in the absolute. Metrics such as open-rates, click-rates, and conversions become important for assets such as emails and landing pages. For your website, you may be looking at bounce rates, time-on-page, referring sources, visits, and conversions. In your social channels, likes, favorites, shares, and direct messages become the main source of analytics.
All of these metrics have one thing in common – they help you analyze what’s driving engagement and what’s not. They are critical to understanding which messages resonate, which digital assets have the greatest draw and momentum, and which social campaigns get the biggest attention. Knowing this information will help you tweak visuals, copy, messaging, placement, and interactions, among other things. They are also critical for A/B testing and multivariate testing. If you’re looking for a place to start with your analytics, begin by pulling engagement-driven metrics that will help you craft your marketing approach.
Impact-driven metrics utilize the foundation of engagement-driven metrics, but tie them back to specific conversion goals and/or revenue. With impact-driven metrics, we’re looking to understand how specific campaigns or programs directly impacted the bottom line. Did a specific campaign increase revenue? Did we achieve a higher ROI? Did we increase the number of SQLs? MQLs? Were we able to increase velocity through the sales funnel? Exactly how did these campaigns impact the goals we’ve set?
Impact-driven metrics are harder to measure. They require a level of closed-loop reporting which allows for proper attribution across various campaigns and touch points. It typically requires an integration of sales data with marketing data to properly measure how specific marketing efforts align with sales outcomes, and whether that impact is reflective of pipeline or closed deals. Most importantly, it requires a lot of upfront thinking regarding opportunity stages and alignment, campaign attribution, contact association, and responses. It’s also critical to define your goals prior to every campaign launch, ensuring your marketing technologies are aligned and integrated to deliver the proper information.
If you’ve already mastered your engagement-driven metrics, and you’re ready to tackle impact-driven analytics, start by assessing your current goals in relation to conversions and ROI. From there, audit your marketing technologies and their capabilities to align the data required to properly attribute conversions across campaigns and contacts/accounts. You’ll likely need to bring in stakeholders across various teams, including marketing, sales, CRM, analytics, etc.
Action-driven metrics take analytics and data and put them to work. This kind of analysis is forward-thinking instead of backwards. In other words, action-driven analytics give you the power to offer messaging and content specific to your customer’s behaviors and/or interests. In some cases, this is done through machine learning and artificial intelligence. In other cases, you’ll drive decisions and actions based on segmentation strategies that utilize profile and behavioral data harnessed from your analytics systems. Either way, the use of action-driven analytics helps you ensure your customers receive the exact content they need, when they need it.
If you’re exploring action-driven analytics, a good place to start is with your current marketing technologies. Dive into the capabilities of your marketing automation, analytics, DMP, etc. systems to see how you can best pull and harness behavioral data across your website, apps, social networks, etc. Armed with various cluster analyses that drive your audience segmentation, you can start to build interactions and recommendations based on specific and timely customer interests. Depending on your marketing technologies, you may have the power to provide real-time online recommendations, personal messages, SMS alerts, etc. based on customer interactions.
This level of analytics is typically the most complex, especially if the right marketing technologies and tools are not in place. I recommend that you start by identifying your current toolset and capabilities, the integrations among these systems, and your ability to harness this data in real-time across your marketing channels.
Bring It All Together
Which types of analytics you utilize will heavily depend on your internal capabilities, processes, people, and technologies. As with anything, you should start with your goals in mind. What are you trying to accomplish with your analytics? What do you need to measure in order to ensure you are hitting your goals? From there, dive into your marketing technologies and internal capabilities to uncover what’s possible and what may be a challenge. Work on a short-term plan and a long-term roadmap to build capabilities and complexities.
If you’d like to discuss how to best build an analytics roadmap, or you need assistance with structuring, harnessing, or managing your data and analytics, Relationship One is always here to help. Contact us for more information.