Against technology, marketers can’t win so hire those who know their space, and how to interpret metrics – metrics that are cross-functional. The data that marketers must analyze to make decisions at scale requires a framework that can ingest, join and analyze in seconds. An open and extensible solution could deliver innovative predictive, real-time, and AI-based analytics capabilities for extracting real-time, actionable insights from massive business and customer data volumes. But what if the tech is bought and invested in without a framework and marketers in place?

This blog summarizes the marketing metric streams to illustrate how digital, traditional, and social media efforts impact the entire business in the future of marketing. Additional information is provided to guide the marketers in shaping their own frameworks utilizing both advertising and sales metrics that could be interpreted with the pre-defined goals.  If you do not have time to read this blog, bookmark now to read later so that you could gain a new perspective on the way to compare cross-functional metrics.

So, campaign metrics need to be supplemented by other metrics with broader enterprise applicability. By far the dominant ones we see are sales and customer satisfaction (e.g., revenue growth, net promoter score). This seems to be where the majority of today’s marketers are concentrating their efforts. And beyond the technology, there are disconnected point solutions from websites to service ticketing platforms to sales productivity. 

There is a crisis of disconnection in marketing as not all marketing is truly marketing and not all is needed. 

This marketing metrics roadmap below from HBR simply misses the Artificial Intelligence angle now but could easily be administered to the marketing organizations. Would this map be interpreted? For the product marketers, could it answer which product features need to be added to take advantage of the generative Al? For corporate or service marketers, could it map out if AI-based targeting yields clear benefits, and how can this be accurately tested? Is AI-driven ad personalization worth the effort? Marketers need to be able to support various sequences and various audiences, products, or brands. Often their product tools are not enough and connectors are external, often costly so pulling data from multiple-touch points becomes cumbersome, tiring, and demotivating. 

Marketing Technology (MarTech) Automation

Implementing a digital media measurement strategy based on a measurement framework is often expected by medium to senior-level marketers who work with operations or development teams to ensure consistent tracking and measurement across platforms. They are responsible for full-funnel digital media performance analysis and reporting, partnering with digital channel teams to develop actionable insights to guide media optimization. Serving as subject matter expert on digital media performance analytics leads to hours spent in performing cross channel measurements to evaluate and refine activity, including test and learn, conversion lift studies, and deeper analysis as well as evaluating customer journeys and data signals across the customer lifecycle that will inform audience targeting and media flighting. These lead to the design and data visualizations for enterprise marketing performance data reporting. This is where marketing technology automation comes into play for marketers.  

If we consider the KPIs, automation brings transparency to growth opportunities. What’s driving the average revenue per customer higher? If the company has a subscription model, it could bring out if there are more active platform users than paid seats for seat expansion. Some of the metrics to consider are as follows:

• Active users: any user taking specific actions in a given time period in a portal that has a modular subscription. These could be found within the account holders (active users vs paid seats on a contract).
• Paid seats: paid sales or service seats. 
• Average subscription revenue per customer: often utilized in conjunction with the total cost of ownership for customers to show subscription revenue in a given time period. 
• CAGR: compound annual growth rate (CAGR). A positive CAGR could be based on strong ASRPC growth and retention performance.  

It is also important to understand the ASRPC growth and how it was driven and by whom. Was it from a front office unification as the automation will help bring data from multiple sources, automate processes and workflows and get better insights from more sophisticated data sets? When the loyalty emails go out from marketing to the current customers with updates on features and/or new features per customer requests, you could look at the changes in the active vs paid seats and the usage percentage of the paid features, the account requests, inquiries, service tickets to know what feature and/or service bundle to offer to them? Some of these metrics for magical marketing insights stem from are:

• Customer Retention Rate
• Customer Lifetime Value
• Net Promoter Score
• Customer Satisfaction
• Engagement Rate with Additional Responses
• Email Open Rate
• Repeat Purchases and Referrals

With automation, will the company be able to break down the metrics and corporate/product insights and quantify the drivers of an uplift highlighting laggard sales, churn, etc. beyond macroeconomics? How would the automation of multi-point technologies affect e-commerce or advertising?

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