3 Success Factors to Insights-Driven Automation

Most marketers do not have a technology problem. In fact, we’ve crossed the chasm of a few years ago, when technology could not keep up with marketers’ vision of customer engagement. Now, we have so much technology, we can’t utilize it strategically and we struggle to integrate it.

Most marketers do not have a technology problem. In fact, we’ve crossed the chasm of a few years ago when, technology could not keep up with marketers’ vision of customer engagement. Now, we have so much technology we can’t utilize it strategically, and we struggle to integrate it.

At the same time, marketers do not have a data problem. There is more data than we can manage or use wisely.

Marketers do have an optimization problem when it comes to using their technology and data to generate meaningful insights. Many of us struggle with how to prioritize our integrated marketing technology, practices and teams in order to generate the kinds of insights (a key output of many of our technology and data solutions) which will move the needle for the business.

There are three factors to this challenge.

  1. Analytics must be integrated with campaign management.
  2. Content must be created to solve problems.
  3. Insights must be scored and prioritized.

First, We Have to Get the Analytics Closer to Our Outbound Messaging. Personalization is the key to successfully creating relevance for each customer, so the analytics can’t happen off to the side. It has to be integrated with our IMM/campaign management solution so that each customer and prospect will be connected with content that is important, and available at a time that will resonate.

We can pretty easily automate our marketing response to insights. Programmatic buying has been around for many years and is expanding beyond search to Web display, ad re-targeting and campaign management (outbound) solutions. The rise of the DMP (or DSP)—platforms which allow utilization of consumer data across websites—provides great benefit to marketers looking to serve customers and prospects as they interact with any combination of owned, earned and paid media. This is helping us identify the anonymous and known people in our marketplace. Yet, the insights from interactions with branded messages across the ecosystem are not yet accessible fast enough or completely enough to allow marketers to be nimble in serving customers. We have to get these programmatic insights back to the main IMM “hub” and the campaign messaging platforms.

We need automation to also serve the process. Marketing operations efficiencies like workflow and social CRM require these insights at scale. While truly integrated IMM on a single platform is nirvana, the marketing technology landscape is huge. Real engagement often requires a few tools that will work together.

Second, Our Content Creation Machines Have to Focus More on What Sells and Our Brand Purpose. Too much content is created simply because it’s interesting. That is not a high enough bar. If your product is water, then the content needs to be all about fire. Content has to create need and speak to the “Why” of what you do, not the “What.” Why brands produce a product is usually about vision, value, need and satisfaction. Look at those heartwarming Super Bowl ads—do Dove products make you a better dad? No. But the brand is about being true to yourself and to celebrating your own personal values. So the advertising content worked.

If 2015 has a theme in marketing, it’s got to be personalization. Of course that means something different now than it did 10 years ago, when we first started really considering what is possible with custom-branded experiences. Effective personalization now means curating the content that will resonate with each customer’s individual needs. Automation technology makes this possible through content blocks and integrated native advertising units.

Third, We Need More Discipline About the Types of Insights That Will Help Us Do More Effective Marketing. I’ve always found in marketing analysis that certain demographics have clear preferences in tone, pace and language when interacting with a sales rep or brand. We can capitalize on these preferences to increase sales and connect the right rep with the right type of customer.

One way to solidify the discipline is to have some sort of mantra or brand promise that is very clear, and so all analytics work can strive to generate insights that are true to that brand promise. Remember the Coca-Cola’s Content 2020 Manifesto? Auditing your landscape of opportunity and focusing on the areas that have the most impact on revenue and market share will help you identify the kinds of insights that are most meaningful for your business.

Granted, this task is complicated by the fact that much of our data is channel-specific and measures the effectiveness of campaigns against previous campaigns. We need more insights around the impact and engagement of individual customers. Silos are still present, and organizational structure can severely limit marketers’ ability to learn about the customer-level engagement. One way to bring the team together is to score insights as they are applied to the business (much as we score leads). Did this move the needle? Have we improved our reach or response? Are key audiences engaged? It’s not just a volume game, but an engagement game with priority, high-value customers.

With these three success factors in mind, marketers can use the technology they have in a test and learn methodology to help better understand how automated insights can grow the business. Once the key drivers are identified, we can start to also assess current technology and pare down the options for improving the integration and efficiency of your organization.

Are you automating the use of insights that help personalize the customer experience? Please share your success factors in the space below.