Which Marketing Metrics Matter?

The ability to measure is a sure sign of a quality organization. As marketing technology permits access more data, the gap between excellent marketing organizations and those deficient will widen — defined, in part, between those that measure well and those that do not.

To have a bigger impact on the business, marketing executives must learn which metrics matter – and to whom.  When marketers get swamped with data, they often report the wrong things to the wrong people. As one CEO told me, “The day I care about how many clicks our Web site gets is the day I lose my job!”

Three Levels of Metrics
IDC’s Hierarchy of Marketing Metrics describes the business context of what marketing measures
and reports. It parses metrics into three categories that correspond to the types of decisions made at various organizational levels and highlights the links between them. The three categories are:

  • Corporate-level metrics: Used at the highest level of the company to manage company productivity and performance as a whole.
  • Operational-level metrics: Used to manage marketing resources and asset productivity, forecast the performance results of core marketing processes, and diagnose the “red” areas on the quarterly business review (QBR) charts.
  • Execution-level metrics: Root metrics produced by marketing tactics; used to manage and optimize the marketing tactics and to coalesce to produce operational-level metrics.

Managing the Business vs. Managing Programs
Magic happens when marketing executives grasp the critical difference between operational-level metrics and execution-level metrics. Both are critical, but for different reasons. Execution-level metrics measure the results of marketing programs. They are used for optimization (did we increase conversion rates?), for testing (did emails with this color outperform?), and for customer behavior analysis (what offer should come next?).  Execution-level metrics are also those that form the basis for operational-level metrics.

Operational-level metrics map the inner workings of marketing into the language of business. Each major function in a company (finance, marketing, HR, R&D) is a specialty area with its own private language. Converting each function into “business speak” by using metrics ensures that the company executives can collaborate to run the business as a whole.

Making connections between the inner workings of marketing as described by execution-level metrics and the operational metrics needed to run the business is hard. Calculating an operational-level metric requires inputs from multiple execution-level metrics, sometimes as many as 30! However, this mapping is the only way to tie the tactics of marketing to things that matter to the corporation’s productivity (profits) and performance (revenue and market share).

Data offers an opportunity for marketing to have a greater impact on the company’s goals and therefore greater power within the organization. To realize this opportunity, marketing leaders must invest in the skills, discipline, and tools needed to master data at both the execution level and the operational level.

 

If Content is Still King, Data is Heir to the Throne

Content marketing is becoming a primary strategy to solve the challenges of massively scaling and diversifying marketing channels. But content does not naturally support both scale and diversity at the same time. The only thing that scales as endlessly and cost effectively as the digital world is data. As a result, data marketing is on the rise and will ultimately inherent the throne as the core strategy for modern marketing. What is data marketing? It’s using interactive data to directly influence or add value to your prospects, customers, and partners. Think of it as content marketing without the editorial. Data marketing is already fueling the rapid growth of content marketing. The best pieces of content marketing are typically wrapped around a compelling piece of (static) data. The key is that stripped of editorial, data must become interactive and not only deliver personalized insights but capture and bring user input back. 
Modern business solutions are increasingly deployed in the cloud on SaaS platforms that capture every transaction of every user. SaaS vendors are finding huge value in these datasets. They provide empirical evidence of best practice, efficacy, and cost effectiveness. Marketing and sales automation vendors can show their customers and prospects what types of campaigns result in the greatest lead generation, the highest value and velocity through the pipeline and the greatest return. They can tell them what type of social media content and cadence is most effective on which social media channels. This insight represents enormous value-add over and above the operational efficiency the systems provide.
Consider the power of this model applied to channel marketing. A SaaS platform for channel enablement can offer partners a single point of access to content repositories, transaction systems, execution environments, (inbound and outbound marketing, sales process tools) and social networks. If it’s constructed properly it provides a place for partners to get work done, not just a library to read about how to get stuff done. For smaller partners that lack infrastructure and staffing resources this is an invaluable resource. As they use the platform it captures:
  • Engagement – who’s downloading what how often from the platform
  • Transactions – deal registration, order submission, billing update, MDF reconciliation.
  • Execution– the number of leads their marketing has produced, how leads are progressing through their pipeline
  • Social interactions – groups they join, how they participate, what SMEs they interact with.
  • Performance data – closed deals, order value

Access to this data can be offered from the platform through the development of a few simple forms and reports. The more data partners provide, the greater the level of analysis and insight they get in return. This information can be used to identify best practices of the top performers and shared (in aggregate) with other partners to help them run their businesses, resulting in better overall performance of all partners.
By utilizing pure data as collateral, companies can deliver highly targeted proprietary insights at scale much more efficiently than they can with content. While the role of content will in no way diminish, companies that master the art of data marketing will have greater levels of engagement, retention, and revenue with all their key constituents than those that rely exclusively on content marketing. 

Data, Marketing, and Supply-chains: Insight from the IBM Smarter Commerce Conference

Envisioning your role within a larger context opens up possibilities. “Marketing” is mostly an internal work categorization. So, why limit your vision to marketing’s traditional box? The IBM Smarter Commerce conference is unique. It isn’t really a marketing conference. Instead, marketing is placed within the context of the overall commercial supply chain – a view I support.

Customers do not readily distinguish interactions from specific company departments.  IBM says that 74% of customers regard the post-purchase experience (such as retail fulfillment, or the cost of service in technology purchases) as critical in vendor selection. What possibilities open up when marketers with this broader supply-chain vision – and access to supply-chain data – start applying these tools to modern marketing? Here are a few insights I picked up from the early experts at the IBM Smarter Commerce conference.

  • Marketing works better when delivered as a service. “Marketing should be so helpful that customers would be willing to pay for it,” said Jay Baer, event MC and author of the new book, Youtility. Baer says that your competition for attention isn’t just businesses like you but everyone! Only if you are useful will the customer keep you close. Among the interesting case studies of marketing-as-a-service highlighted at the event was insurance company USAA. USAA provides customers with an “auto circle experience“.  Although they do not sell autos, USAA offer buyers free services at each step of the car-buying process: research on cars, auto evaluation tools, and various purchasing services.  Once USAA builds trust, then they offer their for-profit insurance services. USAA’s extensive database of car ownership and usage stats directs them when to promote these services thus stimulating purchases. My take-away: Think beyond your own product and even outside of your own company. Offer services that customers will view as unexpected but delightful and highly useful.

  • Personalization must actually benefit the customer. People do want personalization and will go to some effort to get it. But people like personalization only if it benefits them. If it only benefits you or if it has unintended consequences, personalization will backfire. Big, powerful, data engines can do really horrible things to people if you aren’t careful. A major retailer explained to me how data elements have differing degrees of confidence. You will know some things for sure (maybe a person’s age), but many more things are merely estimates. This retailer used to send hyper-personalized emails (13 million variations!) But this resulted in frantic calls such as, “Did my identity get stolen? You know everything about me, but I didn’t buy this!” The combination of highly accurate data mixed with the semi-accurate can spook people. Now this retailer sends only 10 versions of their campaign.

  • Every interaction is a link within the context of a communication supply-chain. Don’t look at each discrete message, or even each campaign, as a unique event with a direct link to the end result. Marketing is not a candy machine. Instead, view each as a link in a chain of events each of which leads to other actions.  The most important data attribution task is to discover that chain– what activity in which order and through which messaging channel tends to lead to another event. For example, social media tends to drive to search rather than directly to your website.  Mobile scanning tends to drive buyers to a physical store or to a desktop purchase. 

Managing your marketing as an element in a supply-chain will not be easy. Some of the challenges include delivering on true omnichannel capability, inconsistent fulfillment of content, inconsistent service delivery, and gaining visibility across the customer interactions.  However, this vision brings you closer to the customer’s point-of-view and thus opens up more possibilities for competitive differentiation and revenue success.