3 Reasons “Measure Everything” Is the Marketing Technologist’s Mantra
If you are a marketing technologist who has received the green light from your CMO to invest in top marketing tools for the year, it is likely you are feeling a mix of emotions.
On the one hand, it is exciting to know you are going to have the resources you need to help your marketing team take its strategy to the next level. As detailed in a previous post on the SmartForms blog, martech solutions, starting with data management software, can align your marketing strategy with clean, enriched data to propel campaigns to exceed company goals. Naturally, having the budget to invest in the right tools is likely an incredibly exciting opportunity.
On the other hand, however, you are likely feeling a bit of anxiety. After all, you championed hard to get the right tools in place, got approval for the budget, and now it is on you to prove the return on investment to your CMO.
Do not stress. Take a deep breath, keep calm and measure on.
In fact, if you are looking for a mantra to guide your work as a marketing technologist, grab a sticky note and write this on it in all caps:
It is your job to be the data person that optimizes your martech stack for the best possible return on investment.
Content management platforms, automation tools, social media marketing solutions, and other tools help improve efficiency and accelerate the effectiveness of your marketing strategy.
However, as you know, the foundation for that martech stack is clean, quality data.
That is why data management software should be the very first tool in which you invest.
Here is a simple truth. Data management software can make or break the success of your marketing campaigns.
Just like any other tool in the stack, you need to know how to measure its effectiveness so you can easily report back on the ROI.
That is exactly what you will learn in this post. You will find three ways marketing technologists can measure the success of their data management software at every stage of the marketing process.
Sound helpful? Read on to get started.
#1. Look at Content Engagement as a Measure of Your Data Quality
It is natural that when content engagement is low, the first thing you might blame is the content itself.
At times, you might be right. Poor engagement can certainly be the result of poor content. But you would be wrong to assume that is always the cause.
As a marketing technologist, it is your job to dig deeper and figure out the root problem in getting customers to engage with your content. A great place to begin the search is with a look at your data quality.
Think about it. You could have marketers creating the best content in the world, but if it is not actually reaching your audience due to poor data quality, then what good is it?
Poor data quality affects content engagement in two distinct ways:
- Lack of accurate contact information. Of course, in the case of inaccurate or incomplete data, it is entirely possible that your content just is not being delivered to your audience. It is impossible to get engagement with your content if it never arrives in the inboxes of your audience.
- Poor customer segmentation. As you surely know, content is not universal. Different audiences need different levels (and types) of content at different stages of the customer journey. With poor demographic data, it is much more difficult to accurately segment customers to ensure they are receiving content that makes sense for them.
The inverse of this content engagement equation is true also, though. If you are noticing an uptick in your content engagement, do not assume it is that the content quality has improved; it could very well be a reflection of the work being done by your data management software to accurately scrub data of incorrect contact information and enrich the data to create a more robust profile for customer segmentation.
That is why you should look specifically at these figures when measuring the success of your data management software in relation to content marketing:
- Email delivery rate (measures accuracy of contact information)
- Click-through rate (measures accuracy of segmentation)
- Social media engagement (also measures accuracy of segmentation)
Together, those metrics give you a good idea of the influence your data management software has on your content marketing strategy.
#2. Lead Conversion Ratio Highlights The Success of Your Entire MarTech Stack, Starting with Data Management Software
It has already been established that quality data is the backbone of any successful marketing strategy.
While the way marketing technologists measure success can be broken down into a wide array of metrics, the one true metric that matters to executive leadership is revenue.
Has the lead conversion ratio increased as a result of your investment in martech?
Ultimately, when proving the ROI of your entire stack, you are going to need to find a way to tie each tool to an increase in lead conversions. Data management software is no exception, but it is also the most obvious measure because it truly affects everything else in your stack.
Here is an example for you:
Suppose you invest in a marketing automation tool like Hubspot. Your team immediately starts to see more quality leads being funneled to your sales partners as a result of improved nurture campaigns.
Does Hubspot deserve the credit for that success?
Of course! But doesn’t your data management platform deserve some credit, too?
After all, how effective would Hubspot be at nurturing leads if it did not have quality data supporting its activity?
Answer: not very.
The point is, quality data underlies your entire marketing strategy, so ultimately anytime you are seeing improvements in lead conversions, your data management software deserves at least some of the credit.
#3. How Churn and Upsell Opportunities Reflect a Top-Notch Data Management Platform
An increase in revenue might traditionally come from new business, but more and more companies are recognizing the value of marketing to existing clients to maximize lifetime customer value and reduce churn.
Like everything else in marketing, a strategy like this hinges on quality customer data. As a marketing technologist, you can leverage data from already-churned customers to forecast red flags from current customers that exhibit behaviors indicative of being a churn risk.
You can also use that data to continue nurturing customers after their initial sale to maximize lifetime customer value. Upsell and cross-sell opportunities come as a result of introducing customers to bigger value propositions from within your business and helping them solve other problems at their companies. Data management software helps you identify these opportunities and ensures nurture campaigns go off without a hitch.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization, and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean, and enrich prospect and customer lifecycle data in your business, and do it at your own pace.